research topics for stem students in pandemic

SCIENCE & ENGINEERING INDICATORS

Elementary and secondary stem education.

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Online Education in STEM and Impact of COVID-19

The COVID-19 pandemic led to school building closures in March 2020 and an unprecedented, near-total transition to online or alternative learning, affecting approximately 55 million students in 124,000 U.S. public and private schools (Education Week 2020a). In fall 2020, the majority of school districts continued to rely on a distance-learning model for instruction, including some of the nation’s largest school districts, such as Los Angeles Unified School District and Chicago Public Schools (Education Week 2020b). In response to these shifts in instruction, many researchers are endeavoring to understand the impact on students and are finding that there may be long-term effects on student learning (see sidebar Learning Losses and COVID-19).

Learning Losses and COVID-19: The Pandemic’s Potential Long-Term Impact on Students

Studies from the Annenberg Institute at Brown University and the Center for Research on Education Outcomes (CREDO) at Stanford University project that there may be substantial learning losses for students because of the COVID-19 pandemic. These studies estimate, for example, that some students may lose up to a full year of math learning. These studies find that learning losses are not distributed evenly among all students and that some groups of students may be more negatively affected than others, such as students from low-income households or those with disabilities. These researchers caution that the results of these projections are estimates and should be interpreted carefully. However, based on their research, they conclude that the educational disruptions caused by the COVID-19 pandemic have the potential to negatively affect student learning and education. As a result, they suggest, schools should allocate additional resources to help students, especially the most vulnerable, accelerate their learning and regain these losses (CREDO 2020, Kuhfeld et al. 2020).

A report from the Annenberg Institute at Brown University estimates that students began the 2020–21 school year with a third to a half of the learning gains in math relative to a normal school year (Kuhfeld et al. 2020). The study used data from 5 million student test scores and utilized models based on student learning loss due to absenteeism, school closures, and summer break to project the effects of COVID-19 educational disruptions on student learning from spring 2020 (when most schools temporarily closed and then shifted to online instruction) through fall 2020 (the start of the 2020–21 school year). The authors note that their estimated reduction in the expected year-to-year math gains is not evenly distributed; some students may experience little loss, while others, particularly those from low-income households and students who were already low performing, may experience greater losses. The authors estimate that these more vulnerable students may have returned to school in fall 2020 already nearly a full year behind in math.

CREDO also estimates that some students may have lost up to a year of learning in math (CREDO 2020). The researchers used information based on prior years’ achievement scores, days of instruction lost due to the pandemic, and projected learning losses associated with out-of-school time to estimate the amount of learning students lost by the end of the 2019–20 school year. CREDO provided estimates for 19 states and suggested that these learning losses could result from students not learning new concepts and not experiencing reinforcement of concepts already learned.

In a paper from the World Bank, researchers used data from 157 countries to estimate global learning losses due to education disruptions caused by COVID-19 and determined that students on average could lose from a third of a year to almost a full year of schooling as a result of the pandemic (Azevedo et al. 2020). They also estimated larger losses for more vulnerable groups, including ethnic minorities and students with disabilities, who could be more adversely affected by school closures.

In addition to estimating learning losses, researchers have estimated the economic impact of education losses resulting from COVID-19. These projections reflect current thinking about the economic impact of these losses, but they are based on economic conditions that are subject to change over time. As with learning loss, however, most researchers do agree that there will likely be some economic impact due to education losses resulting from the pandemic. A report from the Organisation for Economic Co-operation and Development estimates that the global closure of schools could lead to a 3% lower income for K–12 students over their lifetime and a corresponding average of 1.5% lower annual gross domestic product for countries for the remainder of the century (Hanushek and Woessmann 2020). A report from McKinsey Insights estimates that the average K–12 student in the United States could lose the equivalent of a year of full-time work income over the course of his or her lifetime, and these losses may be higher for Black and Hispanic students (Dorn et al. 2020).

This sections draws on education data from the Household Pulse Survey, a nationally representative survey conducted by the U.S. Census Bureau in collaboration with five federal agencies to gather data on the effects of COVID-19 on American households. https://www.census.gov/programs-surveys/household-pulse-survey/technical-documentation.html ." data-bs-content="The questionnaire is a result of collaboration between the U.S. Census Bureau and the U.S. Department of Agriculture Economic Research Service, the Bureau of Labor Statistics, the National Center for Health Statistics, NCES, and the Department of Housing and Urban Development. The Household Pulse Survey has been conducted in three phases. Data presented here are from Phase 1 and Phase 2. Each phase utilizes an overlapping weekly panel of respondents, each of whom are surveyed once per week for 3 consecutive weeks before being replaced by a new panel. Each phase is designed to be nationally representative of the U.S. population, though different panels responded in the Phase 1 and Phase 2 data collections. For more information, see https://www.census.gov/programs-surveys/household-pulse-survey/technical-documentation.html ." data-endnote-uuid="59ecfbd8-3626-4789-a2de-3966661d1832">​ The questionnaire is a result of collaboration between the U.S. Census Bureau and the U.S. Department of Agriculture Economic Research Service, the Bureau of Labor Statistics, the National Center for Health Statistics, NCES, and the Department of Housing and Urban Development. The Household Pulse Survey has been conducted in three phases. Data presented here are from Phase 1 and Phase 2. Each phase utilizes an overlapping weekly panel of respondents, each of whom are surveyed once per week for 3 consecutive weeks before being replaced by a new panel. Each phase is designed to be nationally representative of the U.S. population, though different panels responded in the Phase 1 and Phase 2 data collections. For more information, see https://www.census.gov/programs-surveys/household-pulse-survey/technical-documentation.html . Although they are not specific to STEM classes, these data offer insight into student access to computers and the Internet as well as the amount of time families spent on education during the pandemic, both in spring 2020, immediately after the transition to distance learning for most students, and in fall 2020, when students returned to school either in person or virtually. To provide context for the pandemic-related shift to digital instruction, this section also presents data about teachers’ and students’ use of technology before the pandemic. These data show that the use of technology and online instruction were not widely prevalent before COVID-19 and underscore the challenges of a shift to fully remote and hybrid learning approaches during the pandemic.

Education during COVID-19

Household Pulse Survey data help illustrate how the COVID-19 pandemic affected schools, students, and families, including how schools and districts were able to make some adjustments by fall 2020 to improve access to teachers and digital devices needed for online learning. In the first week of May 2020, adults in households with children enrolled in K–12 schools reported an average of 13 hours per week spent on teaching activities with children , with Asian households reporting the lowest amount of time at about 10 hours per week. On average, students spent about 4 hours per week in live virtual contact with their teachers, but this fell to about 3 hours for households in which the respondent had less than a high school education ( Table K12-7 ).

Average number of hours in the past week spent on home-based education in households with children enrolled in K−12 school, by selected adult characteristics: 7−12 May 2020

a Hispanic may be any race; race categories exclude Hispanic origin.

The table includes adults 18 years and older in households with children enrolled in K−12 school.

National Center for Science and Engineering Statistics, special tabulations (2020) of the 2020 U.S. Census Bureau Household Pulse Survey.

Science and Engineering Indicators

In September 2020, respondents reported how much time their child spent on learning activities in the last week compared with a regular school day prior to the pandemic ( Table K12-8 ). About half reported “as much,” “a little bit more,” or “much more” time spent, while one-fourth reported “a little bit less” time spent. More than one-fourth of respondents reported that their child spent “much less” time on learning activities compared with pre-COVID-19 instruction.

Adults who reported time that their children spent on all learning activities in the past week relative to a school day before the COVID-19 pandemic, by selected adult characteristics: 16−28 September 2020

The table includes adults 18 years and older in households with children enrolled in K−12 school. Adults in households with only homeschooled children are not included. Percentages may not add to 100% because of rounding.

A majority of respondents (85%) reported that their children had at least 2 days a week of live contact with their teachers, either in person or by phone or video ( Table K12-9 ). More than two-thirds of respondents reported that their children had 4 days or more of contact with their teacher in the last week. However, 11% of respondents reported that their child had no contact with their teacher in the last week. In addition, live contact with teachers varied by students’ household income and parental education. About 16% of households with the lowest income levels (below $25,000), as well as 20% of households in which the respondent had less than a high school education, reported no teacher contact. This compared with 6% of households at the highest income level ($200,000 and above) and 7% of households in which the respondent reported a bachelor’s degree or higher.

Adults who reported frequency of live contact of children with their teachers in person, by phone, or by video in the past week, by selected adult characteristics: 16−28 September 2020

Although the proportion of respondents indicating that their child’s classes were delivered fully online declined from 73% in May 2020 to 66% in September 2020 ( Table SK12-30 ), in the majority of households with K–12 students, the students continued to receive fully online instruction in fall 2020, which underscores the importance of understanding students’ access to computers and the Internet. The percentage of respondents reporting that a computer or other digital device and the Internet were always available for children to use at home for educational purposes increased from about 70% in May 2020 to about 77% in September 2020, although these proportions varied by household characteristics ( Table K12-10 ). For example, 44% of households at the lowest education level of less than high school reported in May 2020 that a computer was always available for educational purposes compared with 62% in September 2020. However, this was still lower than the 85% of households with a bachelor’s degree or higher who reported the same in September 2020.

Adults who reported that a computer or other digital device and the Internet were always available for children to use at home for educational purposes, by selected adult characteristics: 7−12 May 2020 and 16−28 September 2020

Adults in households with only homeschooled children are not included. Percentages may not add to 100% because of rounding.

Schools and districts made progress in providing computers to students to use for educational purposes between May 2020 and the beginning of the new school year in fall 2020. About 40% of respondents reported that the child’s school or district provided a computer for educational use in May 2020. That figure rose to 61% in September 2020 ( Table SK12-32 ). The percentage of respondents reporting that the school or school district paid for Internet services changed slightly from 2% to 4% between May 2020 and September 2020, and nearly all respondents (97%) reported paying for these services themselves in both months.

Student and Teacher Use of Technology Prior to COVID-19

Pre-COVID-19 data on eighth-grade students’ use of the Internet and computers to complete various learning activities indicate that there may have been a significant learning curve involved in the shift to remote instruction, when most schoolwork needed to be completed online. The 2018 ICILS offers insight into how students used information and computer technology for a variety of learning activities before COVID-19 ( Figure K12-28 ). Almost three-fourths of students reported using the Internet to do research at least once a week. It was less common for students to use computers for other activities, such as completing worksheets or exercises (56%), taking tests (43%), using software to learn skills or subjects (33%), and working online with other students (30%).

• For grouped bar charts, Tab to the first data element (bar/line data point) which will bring up a pop-up with the data details
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U.S. students in grade 8 who reported using information and communications technologies for learning activities every school day or at least once a week, by activity: 2018

International Association for the Evaluation of Educational Achievement (IEA), International Computer and Information Literacy Study (ICILS), 2018. https://nces.ed.gov/surveys/icils/icils2018/theme1.asp?tabontop .

ICILS also offers insight into the extent to which U.S. eighth-grade teachers participated in professional development in using information and communications technologies (ICT) for various teaching tasks before the pandemic ( Figure K12-29 ). These numbers suggest that eighth-grade teachers had some familiarity with using technology for instruction before the pandemic, although likely not at the levels needed to be fully online or responsive to the individual needs of students. About two-thirds of teachers reported participating in training on subject-specific digital resources or taking a course on integrating ICT into teaching and learning between 2016 and 2018. Less than half of teachers reported taking a course on how to use ICT to support personalized learning by students, and only a third reported taking a course on using ICT for students with special needs. About 60% of teachers reported that they had sufficient time to develop lessons incorporating technology and to develop expertise in the use of technology for teaching during the 2017–18 school year ( Table SK12-35 ).

U.S. eighth-grade teachers who reported participating in technology-related professional learning activities at least once in the past 2 years, by type of activity: 2018

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Open Access

Peer-reviewed

Research Article

STEM undergraduates’ perspectives of instructor and university responses to the COVID-19 pandemic in Spring 2020

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Allied Health Sciences, University of Connecticut, Storrs, Connecticut, United States of America

Roles Conceptualization, Formal analysis, Writing – review & editing

Affiliations Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, United States of America, Department of Women’s, Gender, and Sexuality Studies, The Pennsylvania State University, University Park, Pennsylvania, United States of America

Roles Formal analysis, Resources, Writing – review & editing

Roles Conceptualization, Data curation, Writing – review & editing

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing – review & editing

Roles Data curation, Investigation, Project administration, Writing – review & editing

Affiliation Department of Mathematics, The Pennsylvania State University, University Park, Pennsylvania, United States of America

Roles Data curation, Investigation, Writing – review & editing

• Sherry Pagoto, 
• Kathrine A. Lewis, 
• Laurie Groshon, 
• Lindsay Palmer, 
• Molly E. Waring, 
• Deja Workman, 
• Nina De Luna, 
• Nathanial P. Brown

• Published: August 27, 2021
• https://doi.org/10.1371/journal.pone.0256213
• Reader Comments

We examined undergraduate STEM students’ experiences during Spring 2020 when universities switched to remote instruction due to the COVID-19 pandemic. Specifically, we sought to understand actions by universities and instructors that students found effective or ineffective, as well as instructor behaviors that conveyed a sense of caring or not caring about their students’ success.

In July 2020 we conducted 16 focus groups with STEM undergraduate students enrolled in US colleges and universities (N = 59). Focus groups were stratified by gender, race/ethnicity, and socioeconomic status. Content analyses were performed using a data-driven inductive approach.

Participants (N = 59; 51% female) were racially/ethnically diverse (76% race/ethnicity other than non-Hispanic white) and from 32 colleges and universities. The most common effective instructor strategies mentioned included hybrid instruction (35%) and use of multiple tools for learning and student engagement (27%). The most common ineffective strategies mentioned were increasing the course workload or difficulty level (18%) and use of pre-recorded lectures (15%). The most common behaviors cited as making students feel the instructor cared about their success were exhibiting leniency and/or flexibility regarding course policies or assessments (29%) and being responsive and accessible to students (25%). The most common behaviors cited as conveying the instructors did not care included poor communication skills (28%) and increasing the difficulty of the course (15%). University actions students found helpful included flexible policies (41%) and moving key services online (e.g., tutoring, counseling; 24%). Students felt universities should have created policies for faculty and departments to increase consistency (26%) and ensured communication strategies were honest, prompt, and transparent (23%).

Conclusions

To be prepared for future emergencies, universities should devise evidence-based policies for remote operations and all instructors should be trained in best practices for remote instruction. Research is needed to identify and ameliorate negative impacts of the pandemic on STEM education.

Citation: Pagoto S, Lewis KA, Groshon L, Palmer L, Waring ME, Workman D, et al. (2021) STEM undergraduates’ perspectives of instructor and university responses to the COVID-19 pandemic in Spring 2020. PLoS ONE 16(8): e0256213. https://doi.org/10.1371/journal.pone.0256213

Editor: Filomena Papa, Fondazione Ugo Bordoni, ITALY

Received: December 15, 2020; Accepted: August 2, 2021; Published: August 27, 2021

Copyright: © 2021 Pagoto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This project was supported by grants from the National Science Foundation Directorate for Education and Human Resources to NPB (NSF #2028344) and SP (NSF #2028341). Additional support for Dr. Pagoto was provided by National Institute of Health (NIH grant K24HL124366). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

On March 11, 2020, when the World Health Organization declared COVID19 a pandemic [ 1 ], colleges and universities around the US swiftly made plans to close their campuses, send students home, and move to emergency remote instruction in a 1–2 week period. This period was rife with confusion and anxiety as many students had difficulty securing housing [ 2 ] and others were forced into living situations that were not conducive to remote instruction [ 3 ]. Some universities were criticized for how they handled the abrupt move [ 4 ]. Once courses went online, the degree of disruption intensified, with some courses more affected than others. Courses in the STEM fields (science, technology, engineering, and math) are inherently difficult to move online with no preparation or instructor training given the frequent use of laboratory experiences, group projects, and the common use of “chalk talks,” all of which present unique challenges and require the use of specialized technologies to conduct remotely. We know little about STEM undergraduate students’ perceptions of how their universities and instructors handled remote instruction under these emergency circumstances. Such insights can inform institutions’ strategies for insuring effective teaching and learning since it is likely that the COVID-19 pandemic will continue to impact higher education well into the 2021–2022 academic year.

As universities shutdown instructors had little time to pivot to remote instruction and their success largely hinged upon their previous knowledge and abilities, availability of training at their institutions, and the time available to be trained. Although much research establishing best practices for remote instruction exists, it has not been well disseminated outside the fields of educational technology and instructional design [ 5 ]. A recent survey study of undergraduate students revealed a great deal of variability in course modalities used by instructors in Spring 2020, such that 65% of students surveyed reported recorded lectures, 60% reported live lectures, 55% reported pre-recorded video, and 25% reported breakout groups during a live class [ 6 ]. One study found that course workloads also changed during the shutdown, with about one-quarter of students reported that their instructors decreased the workload while one-third reported that their instructors increased the workload [ 7 ]. Much variability was also reported in terms of grading in Spring 2020, with 60% of students reporting that they were given a choice between grade and pass/fail, 34% reporting no pass/fail option, and 6% reporting mandatory pass/fail [ 6 ]. The same study found that the proportion of students rating their course as somewhat or very satisfying from pre-shutdown to post-shutdown dropped from 87% to 59%; and only 17% said they were satisfied with how much they were learning after the shutdown. The pandemic’s disruption to higher education in the spring appears to have been substantial: 13% of students will delay graduation as a result and 40% lost a job, internship, or job offer [ 8 ]. These numbers are sure to rise as the pandemic continues through 2020 and 2021.

The pandemic will affect at least 2 cohorts of undergraduate students in the US. Research on STEM students’ perceptions of the abrupt shift to remote instruction is now needed given the unique challenges associated with conducting STEM courses online and the potential impact on academic performance and retention, as STEM courses are already notorious for “weeding out” students [ 9 ]. Research is also needed on STEM students’ perspectives on how their instructors handled the move to remote instruction not only in terms of the tools and technologies that were used, but also in how much instructors conveyed their investment in student success under circumstances that were stressful both for students and instructors.

The variability in course modality, technologies used, instructor preparedness, quality of instruction and grading in Spring 2020 point to a role for universities in developing policies that create a more cohesive approach to remote instruction and for those policies to be guided by the large body of research on online instruction. Given the unprecedented nature of the pandemic, it is unlikely that universities had policies for closing campus or how to implement campus-wide remote instruction and they had little time to create and enforce new policies. Institutional policies are now needed to guide a more seamless transition, but this needs to be data-driven and informed by students. Students’ perspectives of universities responses, including what students felt their university did that was effective and ineffective may be useful to inform policies and the development of university playbooks on how emergency responses can be more evidence-based in the future. Such knowledge could be leveraged in the context of this pandemic, future pandemics, and other emergency situations that force school closures (e.g., wild fires, snowstorms) [ 10 ].

To address these needs, in virtual focus groups, we queried a diverse sample of STEM undergraduate students about their perspectives of how their universities and instructors handled campus closures and the move to remote instruction in Spring 2020. Specifically, we asked about strategies, tools, and technologies that universities and instructors used that were effective and ineffective. Then, we asked about instructor behavior that made them feel the instructor cared or did not care about their success. Given the exploratory nature of this work examining an unprecedented event in modern history, we put forth no specific hypotheses.

Focus group methodology was selected because very little prior knowledge was available on this topic. In July 2020 we recruited undergraduate students attending US colleges and universities to participate in a study about their experiences in Spring 2020 related to the abrupt transition to remote instruction. Participants completed an online survey [ 11 ] that included questions about their demographic characteristics and participated in focus groups conducted via video conferencing software.

Recruitment

We recruited students through faculty in the Math Alliance, a national organization of faculty in mathematics, by asking them to forward a recruitment email to their students and other faculty teaching courses in the calculus sequence. Recruitment ads were also posted on Reddit in subreddits that targeted student and/or STEM interests and through course listservs. Researchers targeted students within the calculus sequence as these courses are required of most STEM majors. Interested individuals completed a brief online survey to assess eligibility. Eligible students were aged 18 years or older, enrolled full-time in a college or University in the United States in spring 2020, STEM majors, and met criteria for inclusion in one of 16 demographic-stratified focus groups. STEM majors included students who had a declared major within the natural sciences (e.g., biology, physics), engineering, mathematics, and technology but excluded students in the social sciences (e.g., economics, psychology). To create a diverse sample, eligible students were required to fit into one of 16 strata defined by gender, race/ethnicity, and SES (see Table 1 ). Students whose responses to questions about gender, race/ethnicity, or SES did not place them in one of these strata were excluded from participation. Participants reported their gender as woman, man, or with an ‘other’ write-in option; students who did not identify as women or men were excluded. Participants reported whether they identified their ethnicity as Hispanic/Latinx, and reported how they describe their race(s). Based on responses, we categorized participants as non-Hispanic Caucasian, Hispanic/Latinx (any race[s]), non-Hispanic Black, non-Hispanic Asian, or other race/ethnicity or multiracial; participants identifying as another race/ethnicity or non-Hispanic multiracial were excluded from participation. For socioeconomic status, we categorized students as low SES if they: 1) were eligible for work study or Pell grants, 2) reported that it was hard for their family to pay for basics (e.g., rent, heat, food), and/or 3) reported that parental education was less than or equal to a high-school diploma or GED and a household income of less than $75,000. Students were categorized as higher SES students as students whose parental education was a Bachelor’s degree or higher, who were not eligible for work study, were not eligible for a Pell Grant, and reported that it was not hard at all or somewhat hard to pay for basics. Students whose responses to questions about financial aid, parental education, household income, and financial strain did not place them in either of the above groups were excluded from the study.

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https://doi.org/10.1371/journal.pone.0256213.t001

Of the 416 respondents to the initial eligibility screener, we emailed the 154 who were eligible and recruited participants into gender-SES-race/ethnicity focus groups with a cap of 6 students per focus group. A total of 59 students from 34 institutions participated in one of 16 focus groups ranging in size from 2–6. Of the 34 institutions represented in the sample, 88% were public, 12% were private, and 38% were minority serving. Institutions had a mean of 30.14% of students on Pell grants (sd = 13.10). Participants received a $50 gift card for participating. The Penn State University (00014866) and University of Connecticut (L20-0060) Institutional Review Boards approved this study. Participant characteristics are shown in Table 1 .

Focus groups

Focus groups were stratified by gender (male, female), socioeconomic status (SES; low, moderate/high), and race/ethnicity (non-Hispanic Caucasian, Hispanic/Latinx, non-Hispanic Black, non-Hispanic Asian) so that participants did not experience discomfort expressing the challenges they experienced during emergency remote instruction due to being in a group with participants of differing social class, gender, or race. We conducted 16 focus groups, one group with each gender x SES x race/ethnicity group (e.g., non-Hispanic Black women of moderate/high SES). Thematic saturation was achieved with 16 focus groups. Focus groups lasted 60 minutes and were conducted by an investigator (NB, LP, KL, ND, or DW) who was paired with a note taker. To keep the focus groups as uniform as possible, the facilitator followed a script that was produced by the investigator team which reflected multiple disciplines and career stages, including 3 professors (mathematics, clinical psychology, epidemiology), 2 graduate students (gender studies, social psychology), and 2 undergraduate STEM majors. Through discussion, the team developed a list of questions about the strategies instructors used and how instructors behaved towards students during the move to remote instruction as well as what universities did and how they could have done better. The discussion drew upon each team member’s experiences and observations during this unprecedented historical event and the goal was to produce responses that could inform tangible policy changes. No research was available at the time to inform the focus group script S1 File . The final focus group script posed the following questions:

• What are some examples of strategies, tools, or technologies that your instructors used that you found to be very effective (in that they made it easier to learn) during remote instruction?
• What are some examples of strategies, tools, or technologies that your instructors used that you found to be ineffective (in that they did not help you learn) during remote instruction?
• What are some things your instructors did during remote instruction that made you feel like they cared about their students?
• What are some things your instructors did during remote instruction that made you feel like they did not care about their students?
• What are some things that your university did to help students be successful during remote instruction?
• What do you wish your university did to better help students be successful during remote instruction?

During the focus group, each participant was given a turn to respond to each question but they were not specifically asked to react to each other’s responses. When a participant’s response was cryptic, the facilitator probed for clarification. Participants were given the option of providing no response if they could not think of an answer to the question (e.g., if they found no professor strategies helpful they could say “none”).

Transcription software was used to produce transcripts that were then reviewed and edited for accuracy by research assistants S2 File . We summarized participant characteristics using descriptive statistics. We conducted a conventional content analysis using a data-driven inductive “framework” approach to coding the content into major and minor themes for each of the six focus group questions [ 12 ]. As a first step, a pair of investigators, including one who was present during the focus groups and one who was not, read through the transcripts ( familiarization ) to identify emerging themes ( identifying a thematic framework ). They then developed a codebook that was then applied to all of the data ( indexing ). Once each coder finished independent coding they met in pairs to resolve discrepancies as described elsewhere. [ 13 ] A third investigator was brought in for unresolved discrepancies. This process resulted in a total of 46 themes across 6 questions. Interrater agreement ranged from 81% to 100% and Cohen’s kappa statistics ranged from 0.202 to 1.0, with only 2 of the 46 having a kappa of < .5. This exceeds the recommended standard of 80% agreement on 95% of codes [ 14 ].

Data management and descriptive analyses of the survey data were conducted using SAS 9.4 (SAS Institute, Inc, Cary, NC) while interrater reliability statistics were calculated with SPSS 26 (IBM, Armonk, NY).

Focus group participants (N = 59) had a median age of 19 years old, 51% were women, 47% were low SES, and the sample was racially/ethnically diverse ( Table 1 ). In Spring 2020, participants were enrolled in 29 US colleges/universities, including private colleges/universities (n = 4, 14% of schools), public universities (n = 23, 79%), and community colleges (n = 2, 7%). When surveyed in July 2020, students were living in 20 US states/territories including Puerto Rico, with two students living outside the US. The distributions of responses to each question by the 16 race/ethnicity, gender, and SES subgroups are depicted in Table 2 . The representation of the 16 subgroups for each theme of each question are depicted in the S1 Table .

https://doi.org/10.1371/journal.pone.0256213.t002

Effective instructor strategies, tools, and technologies

The 59 participants provided 93 responses to the question: “What are some examples of strategies, tools, or technologies that your instructors used that you found to be very effective (in that they made it easier to learn) during remote instruction?” Two major themes and three minor themes emerged in responses ( Table 3 ). The most common (35%; n = 33) response referred to hybrid instruction, meaning the instructor’s use of both synchronous and asynchronous modalities. For instance, many participants preferred live remote lectures that were also recorded and posted, allowing students who experienced disruptions during the live portion to watch later at their convenience. The next most common theme (27%; n = 25) referred to instructors’ use of multiple tools to reach and engage students, such as discussion boards, study groups (e.g., in breakout rooms), or supplementary materials like making lecture notes or slides available to students. Specific technologies mentioned include communication platforms (e.g., Piazza, Discord, Nectir, Gauchospace, Slack, GroupMe, Blackboard Collaborate Ultra) and streaming/video conferencing platforms (e.g., Zoom, Boing, Microsoft Teams, Twitch). Minor themes included instructor’s communication strategy (15%; n = 14) such as quick and clear email responses to student inquiries; recorded lectures (12%; n = 11); leniency (5%; n = 5); and live lectures at the regularly scheduled class times (3%; n = 3). Finally, two responses (2%) indicated there was nothing the student found particularly effective.

https://doi.org/10.1371/journal.pone.0256213.t003

Ineffective instructor strategies, tools, and technologies

The 59 participants made a total of 68 responses to the question: What are some examples of strategies, tools, or technologies that your instructors used that you found to be ineffective (in that they did not help you learn) during remote instruction? About 1/5 of students (n = 14; 21%) had no examples of ineffective strategies, tools, and technologies to share. Otherwise, 5 major themes and 1 minor theme emerged ( Table 4 ). The most common theme (n = 12; 18%) encompassed any strategy that instructors used that served to increase the difficulty level or workload of the course relative to how the course was conducted pre-shutdown. Such measures included increasing the weighting of proctored exams to reduce the impact of cheating on final grades, adding new tasks such as participation on discussion boards, or changing exam and assignment formats in ways that would avoid cheating but also increase the difficulty level for students (e.g., open-ended responses instead of multiple choice or replacing exams with time intensive projects). The next most common theme (n = 10; 15%) was instructors using pre-recorded lectures. Responses cited that pre-recorded lectures that were used in place of live lectures made it harder to feel motivated to attend and harder to learn from given the lack of opportunity to ask questions in the moment. An equally prevalent theme (n = 10; 15%) was instructors’ lack of a communication strategy, tool, or technology, with examples including no formal ways to interface with the instructor or poor email responses. Another major theme (n = 9; 13%) was the use of any technologies that had frequent technical difficulties, were inefficient, required bandwidth or computer storage that not all students had, or that required more training than was provided. Examples included test taking platforms in which students experienced technical difficulties that interfered with test performance and/or the time available to take the test, dissemination of large files that students didn’t have the ability to download, use of breakout rooms with little guidance on how students should utilize the time, and the use of online tests that didn’t allow students to skip difficult questions and return to them later. The next theme (n = 8; 12%) was related to instructors’ approaches to lecturing, including the use of long-form recorded or live remote lectures, posting outdated lecture recordings, and use of poor quality recordings. One minor theme was instructors requiring attendance at live lectures (n = 4; 6%). One response was coded as “other” because it did not fit into any of these categories.

https://doi.org/10.1371/journal.pone.0256213.t004

Instructor caring behavior

The 59 participants made a total of 87 responses to the question: “What are some things your instructors did during remote instruction that made you feel like they cared about their students?” Two major themes and 4 minor themes emerged ( Table 5 ). The most common response, accounting for 29% (n = 25) of responses related to instructor leniency and/or flexibility with respect to course policies or assessments. Examples included use of pass/fail or other flexible grading policies, allowing homework to be turned in past the deadline, and allotting more time for assignments. The next most common theme (25%; n = 22) was instructor responsiveness and accessibility to students. Examples included prompt replies to student emails, flexible office hours, and frequent engagement on discussion boards. About 13% (n = 11) of responses related to instructors bonding with the class, such as through words of encouragement or just spending time acknowledging the pandemic and asking how students were coping. Similar to this theme which refers to instructors’ interactions with the entire class, another 13% (n = 11) of responses related to the instructor offering one-on-one opportunities to check in with students and provide emotional support. The next theme, comprising 9% (n = 8) of responses related to any sign the instructor put in effort to ensure the class was a success, including learning and using new technologies, expressing enthusiasm, or generally seeming to put in significant effort to maintain high-quality instruction. About 7% (n = 6) of responses related to instructors seeking student feedback on how the course was going. The remaining 5% (n = 4) of responses suggested the student could not think of any examples of caring instructor behaviors.

https://doi.org/10.1371/journal.pone.0256213.t005

Instructor uncaring behavior

The 59 participants made a total of 72 responses to the question: What are some things your instructors did during remote instruction that made you feel like they did not care about their students? Over one-quarter of responses (25%; n = 18) had no examples of uncaring behavior by instructors to share. Otherwise, two major themes and three minor themes emerged ( Table 6 ). The most common response (28%; n = 20) referred to poor communication, including unanswered emails, lack of empathy conveyed in communications, and scolding the class for underperformance. The next most common response (15%; n = 11) referred to instructors increasing the difficulty of the course, including making exams harder to offset the assumed impact of cheating, assigning more work, or grading harder. Minor themes included instructors being unprepared or disorganized (13%; n = 9), including expending minimal effort into the online format, posting assignments at the last minute, and frequently changing requirements, rules, and standards. Another minor theme (11%; n = 8) was inflexibility which included the instructor making no accommodations for students including international students, students with unreliable technology/internet access, students in different time zones, or students with special educational needs. The final minor theme was insufficient instruction or guidance (8%, n = 6). Examples included instructors posting assignments and lectures and leaving students to work on their own with no guidance, minimal or no opportunities to engage with the instructor, and minimal instruction provided for assignments.

https://doi.org/10.1371/journal.pone.0256213.t006

What universities did well

The 59 participants made a total of 116 responses to the question: What are some things that your university did to help students be successful during remote instruction? Two major themes and 6 minor themes emerged ( Table 7 ). The most common response (41%; n = 48) was classified as administrative flexibility, examples of which included university-wide pass/fail policies, waiving limits on counseling sessions, and extending administrative deadlines. The next most common response (24%; n = 28) was provision of remote services such as tutoring, counseling, and advising. One minor theme was agile response (9%; n = 10) which referred to how quickly and smoothly university services changed to meet student needs. Other minor themes included seeking student input during the process via town halls, surveys, and direct email solicitations (6%; n = 7); provision of technology such as wifi hotspots or laptops (4%; n = 5); effective communication strategies (4%; n = 5); and financial assistance in the form of fee waivers and refunds (3%; n = 4). A small percentage of responses (8%; n = 9) suggested the student could not think of any examples of what the university did well.

https://doi.org/10.1371/journal.pone.0256213.t007

What universities could have done better

The 59 participants made a total of 69 responses to the question: What do you wish your university did to better help students be successful during remote instruction? Three major themes and six minor themes emerged ( Table 8 ). The most common response (26%; n = 18) was that students wanted the university to create policies for faculty and departments to increase the consistency in how courses were carried out in terms of grading and teaching modalities. The second most common response (23%; n = 16) was a university communication strategy that was honest, prompt, clear, and transparent. The next most common response (10%; n = 7) was to improve the responsivity and support provided by university offices and services (e.g., financial aid, counseling, tutoring). Minor themes included engaging student input to crisis response (6%; n = 4), provision of technology (4%; n = 3), provide specific accommodations for international students (4%; n = 3), refund fees for services not rendered (3%; n = 2), provide opportunities for students to interact with one another (3%; n = 2), and provide more effective policies to prevent cheating (3%; n = 2). The remaining responses (17%; n = 12) suggested the student could not think of examples of things the university could have done better.

https://doi.org/10.1371/journal.pone.0256213.t008

The results of the present study revealed that generally students expressed that hybrid instruction and the use of multiple complementary resources and technologies were preferred, while reliance on pre-recorded lectures, poorly functioning technology, and insufficient opportunities to communicate with the instructor interfered with their ability to learn course material. The preference for live over pre-recorded lectures is consistent with a recent study that showed that 80% of undergraduate students said video chat and live streaming have made remote instruction better and 72% said the ability to connect with instructor and other students over live video was important [ 15 ]. Interestingly, some students valued recorded lectures due to the flexibility they provide, and this may be particularly important for them to juggle school, work and home life. However, when recordings were in lieu of live class time, lengthy, low quality, or clearly recycled from a previous semester, they were often found to be insufficient. Even though the convenience of recorded lectures was mentioned, many students voiced that it was harder to get motivated and pay attention when classes were reduced to viewing recordings. More work is needed to examine the impact of live versus recorded lectures during the pandemic on attendance/views and student engagement as well as academic performance and intentions to stay in a STEM major [ 16 , 17 ].

Results also revealed university actions that students perceived as beneficial including lenient grading policies (e.g., pass/fail), a quick and smooth response to the emergency, and remotely offering campus services. Many students reported that they experienced too much variability in policies and practices between faculty and departments which for them signaled a need for the university to step in and create campus-wide policies. They felt this would not only help them stay focused and organized but also prevent particularly egregious instructor practices such as instructors being largely inaccessible to students, conducting the entire course by simply posting lecture notes, or increasing the difficulty level and/or workload of courses. Research on student performance across multiple courses under conditions of varying modalities across courses may be needed. Another area for improvement was related to the response of university services (e.g., financial aid) during campus closures which was often cited as slow and inefficient. Research suggests that for remote instruction to be effective it must be accompanied by an educational ecosystem to support the remote learner [ 5 ]. Unfortunately, the abrupt move of campus employees to work-from-home appeared to at least temporarily affect their ability to meet students’ needs during the pandemic. Campus employees likely weren’t used to working from home but many were also likely to be juggling children who were schooling from home while attempting to do their jobs [ 18 ]. Provision of safe and affordable childcare options for campus employees have been called for in general [ 19 ] and the pandemic has revealed this need further. Universities may also need to develop protocols for an online ecosystem that provides students efficient access to services and resources when the campus is closed in an emergency. Further, some services that went online, such as telehealth student counseling, should be continued post-pandemic to increase reach (e.g., to commuter and nontraditional students) and reduce disruptions in care (e.g., winter break).

A cross-cutting theme, emerging in responses to every question we asked about both instructors and universities, was communication. Students desired communication from both instructors and universities that was responsive, transparent, timely, and empathetic. Consistent with prior research [ 20 ], when these qualities were conveyed by instructors and/or universities, students felt more aware of what was expected of them and more valued and respected. In Fall 2020, some universities were called out for harsh messaging to students that shames and blames them for COVID19 spread on campuses [ 21 ]. Our findings suggest such an approach to communication is not likely to be well-received by students. Interestingly, a survey of undergraduate students in Fall 2020 found that 37% of students said their opinion of their university declined during the semester [ 15 ], suggesting that some students have not been satisfied with how their universities have handled the pandemic.

Research has demonstrated that student-instructor and student-student interactions can promote student achievement [ 22 ], perceived learning, and student satisfaction during remote instruction [ 23 ]. Our findings on communication suggest that instructors need to create more opportunities to engage with students during remote instruction and to frequently evaluate whether their engagement plan meets students’ needs. Effective engagement strategies were mentioned by students, many of which are supported by prior research [ 24 ], included the use of formal communication platforms, quick email response times, remote office hours, offers to meet one-on-one, and live lectures that allow for students to ask questions and hear other students ask and get answers to their questions. When live lectures are not offered, the onus is on instructors to provide alternative ways to engage with students while being mindful that voluntary forms such as virtual office hours may not be sufficient to accommodate large class sizes and may be underutilized by students who are bashful, have erratic schedules, or do not wish their home environment to be seen on video.

Some students mentioned appreciating the use of novel communication platforms (e.g., Piazza) that allowed them to ask questions any time (without having to send emails), post questions anonymously, get incentivized for answering each other’s questions, organize conversations into searchable threads, and access everything via a mobile app. The reliance on email to communicate with students is proving to be insufficient as evidenced by a study that found that students who were provided novel tools to communicate with instructors and other students this fall rated their motivation and engagement with learning outside of class significantly higher [ 15 ]. The importance of student engagement is underscored by emerging research that shows undergraduate students continue to feel inadequately engaged by their instructors. A recent survey of 3,412 undergraduate students in the middle of the Fall 2020 semester found that only 40% agreed that their remote instruction experience is engaging during class time and only 32% agreed they are being adequately engaged outside class time [ 15 ]. That same study showed that 85% of students felt that instructors should foster a sense of community among the students in online courses. This signals the need for better implementation and dissemination of best practices for engaging students during online instruction [ 25 ]. Research is needed on how novel technology-based communication platforms influence both instructor-student engagement and student-student engagement and ultimately, student motivation and academic performance. Effective remote communication strategies should also be continued post-pandemic to provide more flexibility in options for students.

Two themes emerged across questions that we suspect are related. Students emphasized the need for leniency in grading, assignments, and expectations, while also expressing concern regarding increased difficulty level and/or workload of courses. Although the stress and disruption related to the pandemic likely contributed to students’ pleas for leniency, instructors should consider that pleas for leniency may also be a result of increases in difficulty level and course workload that may be occurring intentionally or unintentionally. Consistent with our findings, a survey of 148 undergraduates found nearly one-third reported one or more of their instructors had increased the workload in Spring 2020 [ 26 ]. Some practices may have created more work for students than instructors realize. For example, students reported that to avoid online cheating, some instructors replaced exams with class projects that ended up requiring more time to accomplish than the time they would have spent studying for an exam. They also reported that instructors increased the difficulty level of courses as a way to offset the impact of online cheating, by replacing multiple choice exams with free response without allocating sufficient time to complete the exam or by simply increasing the stringency of the grading curve. In addition to increased difficulty, students are reporting numerous other challenges associated with anti-cheating software, including having to read and follow elaborate instructions on how to take the test, anxiety and discomfort associated with being watched through your computer during an exam, and being accused of cheating when internet connection issues disrupt the exam [ 27 ]. Another example students gave regarding increased workload was instructors posting lecture videos that exceeded the usual lecture time. This may have occurred because nothing stops an instructor from running over time when recording a video as opposed to in-person lectures which have a hard stop time. Even when video lectures matched the length of in-person lectures, students said these took longer to digest because watching videos was more cognitively taxing compared to live lectures where interaction occurs. Class interaction breaks up the monotony of a lecture and also allows students to ask the instructor to clarify concepts and answer questions in the moment and hear answers to other student’s questions, all of which can facilitate learning [ 28 , 29 ]. Some students said they needed to take frequent breaks when watching lecture videos, rewind and re-listen to parts they didn’t absorb, and work much harder to stay focused, all of which made the time spent on the lecture go beyond the time they would spend in an in-person lecture. Interestingly, their experience was that the extra time they spent on lectures did not result in better learning compared to in-person classes, but instead, worse learning. Breaking up video lectures into short units, recording live lectures so that class interaction is captured in the video, and allowing students to interact while they are watching may be ways to enhance the experience of watching class by video. Another way students said workload was negatively impacted was when instructors posted their lecture videos at the end of the week or at erratic times rather than at class time, which made it difficult for students to manage their time. Interestingly, the problems students cited were often things that could be remedied by changing practices and/or leveraging available technologies. Inadequate instructor practices may be driving the common sentiment that remote learning is generally worse than in-person. Indeed, a recent survey of undergraduate students found that 68% said remote instruction is less effective than in-person instruction [ 15 ]. This sentiment runs counter to research on remote instruction outside of the context of emergencies which shows positive outcomes on student performance [ 30 – 33 ] and no differences in student satisfaction relative to in person instruction [ 34 ]; however, as discussed elsewhere, it is doubtful that best practices for remote instruction were being implemented widely in Spring and Fall 2020 [ 5 ].

The present study has some limitations. Though participants were diverse in terms of gender, SES, and race/ethnicity, our sample size was too small to compare results by those demographic factors and did not represent the entire range of gender and racial/ethnic diversity in the US. Further, students were asked about their experiences in Spring 2020 which may not generalize to Fall 2020 when instructors had more time to prepare. This work was an initial step conducted to inform survey questions for a larger survey study that assessed students’ experiences in Fall 2020 and disproportionate impacts of the pandemic on STEM education by race/ethnicity, gender, and SES.

Our findings revealed that many students felt universities and instructors lacked a cohesive strategy for emergency remote instruction. To be sure, few anticipated the circumstances of 2020 and students, instructors, and administrators were all under enormous stress. However, a robust literature on online instruction exists [ 35 , 36 ] and evidence points to the increasing possibility that pandemics and other natural disasters are likely to occur in the future [ 37 , 38 ]. Done well, remote instruction can actually increase STEM participation and diversity, which signals the urgent need for broad adoption of best practices [ 39 ]. Going forward, universities must require that all instructors are proficient in remote instruction. This entails provision of training in remote instruction that is consistent with best practices and the adoption of policies that incentivize faculty to gain proficiency in these skills (e.g., embed in promotion and tenure criteria, teaching awards). This would not only prepare faculty for emergency situations like the pandemic, but even more importantly, this would position universities to develop remote learning programs that are designed to increase diversity in STEM. Remote learning programs have been developed precisely for this purpose at some land grant universities, for the purpose of bringing the STEM curriculum to diverse students rather than the usual approach which involves attempting to recruit diverse students to the often rurally-located land grant universities [ 39 ]. Studies have shown this model to be successful in increasing racial/ethnic diversity [ 39 ] and gender diversity [ 40 ]. Related, remote student recruitment strategies (e.g., virtual tours) used during the pandemic to showcase the university’s offerings to prospective students and their families should continue post-pandemic to attract students who may not be able to afford to travel for campus tours. The pandemic, by hastening universities’ and instructors’ capacities to deliver remote education and services, provides a unique opportunity for universities to build upon, allowing them to reimagine their approaches to increasing the diversity of their student body.

Universities should also develop protocols for campus closure and remote instruction that incorporate 1) data on what worked well and what did not in Spring and Fall 2020, 2) the vast body of research on best practices in remote instruction [ 36 ], and 3) iterative input from their student bodies being sure to include diverse voices. University-level policies should address course modalities, grading policies, student engagement strategies, and faculty training requirements. For example, universities should consider prohibiting course modalities that are proving to be unacceptable and/or ineffective, mandating instructor training in remote instruction tools and effective student engagement strategies, and examining the relationship between course modalities and student course evaluations to identify modalities that aren’t working well or are being executed poorly.

Similarly, instructors should produce remote instruction protocols for their courses that are informed by best practices identified in the remote instruction literature. Effective remote instruction requires a design process that takes into account myriad factors including instructor-student ratio, modality, synchrony, pedagogical style (e.g., exploratory, collaborative) among others [ 5 ]. To identify training gaps on the part of instructors, research is needed to examine how instructors approached remote instruction in Spring and Fall 2020 and to what extent it reflected best practices. Finally, effective strategies should be shared in venues that reach the academic community given the lack of implementation and dissemination of evidence-based practices for remote instruction thus far. A great example of such a venue is the Facebook group Pandemic Pedagogy which currently has 32.7K members and emerged shortly after the pandemic commenced as a forum for faculty to share their experiences with remote instruction.

A plan is now needed to address the potential negative consequences to STEM education caused by the pandemic. Universities urgently need to devise strategies to 1) identify and assist students who have exhibited declines in academic performance, 2) follow-up with students who have switched out of a STEM major since Spring 2020, and 3) re-engage students who have unenrolled temporarily or permanently as a result of the pandemic [ 41 ]. A generation of college students is at risk for long-term impacts of the pandemic on their educational and economic potential. Given the disproportionate impact of COVID19 on the very racial/ethnic groups that are underrepresented in the STEM fields [ 42 – 44 ], the pandemic may cause another gaping leak in the STEM pipeline. Finally, the pandemic has presented STEM education with an enormous opportunity to innovate by leveraging the new skillset instructors and university services have developed in the past year. Every crisis brings opportunities for growth. We now must accelerate the implementation and dissemination of best practices for online STEM education with the goal of increasing diversity in STEM while also identifying and ameliorating the negative impacts of the pandemic on STEM undergraduate students.

Supporting information

S1 table. representation of subgroups of stem undergraduate students within each theme for each item..

https://doi.org/10.1371/journal.pone.0256213.s001

S1 File. Focus group script.

https://doi.org/10.1371/journal.pone.0256213.s002

S2 File. Focus group transcripts.

https://doi.org/10.1371/journal.pone.0256213.s003

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• 14. Qualitative data analysis: An expanded sourcebook, 2nd ed, in Qualitative data analysis: An expanded sourcebook, 2nd ed. 1994, Sage Publications, Inc: Thousand Oaks, CA, US. p. xiv, 338–xiv, 338.
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February 25, 2021 | Kevin Noonan - College of Agriculture, Health, and Natural Resources

Researchers study challenges underrepresented STEM students face during COVID-19

This article originally appeared on CAHNR Newsroom. By Kim Colavito Markesich. In July 2020, Professor Sherry Pagoto and Associate Professor Molly Waring of the Department of Allied Health Sciences in the College of Agriculture, Health and Natural Resources were awarded a National Science Foundation grant to study the effects of the COVID-19 pandemic on underrepresented […]

Molly Waring

This article originally appeared on CAHNR Newsroom.

By Kim Colavito Markesich .

In July 2020, Professor Sherry Pagoto and Associate Professor Molly Waring of the Department of Allied Health Sciences in the College of Agriculture, Health and Natural Resources were awarded a National Science Foundation grant to study the effects of the COVID-19 pandemic on underrepresented STEM (science, technology, engineering and mathematics) students. This pandemic is estimated to affect at least two cohorts of STEM students in an academic field that is already considered rigorous.

“We were concerned about the impact of COVID on STEM students, and we wanted to investigate what those impacts were and if there were differential based factors such as gender, race and ethnicity or socioeconomic status,” Waring says. “We wanted to understand where there might be negative impacts that are affecting certain groups of students more than others, with the idea that we can then try to counteract some of these negative impacts. Science works best when all voices are represented and we want to retain our current cohort of diverse students.”

In collaboration with Nate Brown of Pennsylvania State University and with assistance from  members in the Math Alliance , a national organization of faculty in mathematics and statistical majors, the team recruited fifty-nine students from across the United States to participate in focus groups during summer 2020. The students were equally split male and female, with half the students meeting criteria for low socioeconomic status and equal representation across racial and ethnic groups.

For students majoring in STEM fields, remote learning can be particularly difficult as learning is enhanced with hands-on or laboratory experiences. Additionally, many students that rely on employment to support their education have been affected by job losses during the pandemic. There have also been fewer opportunities for research experiences and internships as many labs were forced to shut down.  

In the focus groups, some students expressed concern that they would not be adequately prepared for subsequent semesters in STEM courses, as not all universities were prepared for remote learning and not all students were able to learn remotely.

“Moving forward, we encourage universities to develop a detailed plan in case of another emergency that would require them to switch to remote instruction,” Waring says. “We need effective strategies for remote learning and ways to connect to our students. And there are also some positives that we have learned from this pandemic, such as having faculty be more flexible. I hope we can retain some of these lessons and support those bright students of all backgrounds.”

Students were asked which instructor strategies, tools and technologies were most helpful. Hybrid learning which included both synchronous and asynchronous classes was preferred, with many students preferring live remote lectures that were also recorded and posted, allowing students with interruptions in their home environment to review later. Other tools such as discussion boards, study groups, lecture notes or slides were mentioned as well as communication platforms and streaming/video conferencing platforms.

Ineffective strategies included, increased workload relative to pre-shutdown, prerecorded lectures that did not provide the opportunity to ask questions, lack of a communication strategy, tool or technology, and little guidance on technological strategies, large files that could not be downloaded, tests that didn’t allow students to skip difficult questions and return later, long-form or outdated lecture recordings, poor quality recordings, excessive assignments such as on discussion boards, and vague communication from instructors.

Students were sensitive to feeling that instructors cared about them. Positive instructor behavior included leniency and or flexibility with respect to course policies or assessments such as allotting more time for assignments, as well as instructor responsiveness and accessibility and words of encouragement. Students appreciated instructors checking in with them and one-on-one opportunities.

Some negative experiences included instructors replacing exams with class projects that required more time, online videos that exceeded the time of regular classes, issues with responsiveness or ability to contact instructors. In addition, many students found watching video lectures more difficult than in-class instruction and needed more breaks, rewinding what they didn’t absorb. They had difficulty with focus and not being able to ask questions. Finally, students felt that some instructors were not prepared for emergency remote instruction.

“One thing that has been challenging from the faculty perspective of this is many faculty members had not received training in effective remote learning, especially last spring when many instructors had only a couple weeks’ notice to adapt their courses to be taught remotely,” Waring says. “I certainly understand the students’ perspective of their wide range of experience with remote learning.” Waring also notes the broad range of resources provided by the UConn Center for Excellence in Teaching and Learning (CETL) to support course instructors during the pandemic.

She says, “CETL has provided a wealth of trainings and individual support for faculty looking to increase their teaching effectiveness while connecting with students remotely.”

Students participating in the focus groups also shared their concerns about the fall 2020 semester, including both concerns about returning to campus and about learning remotely from home. The most common concern for students was being infected with COVID-19 and spreading it to family members. They were also worried about noncompliance to COVID guidelines by many students on campus. Additional student concerns included apprehension over instructional quality during remote learning, impacts on social interaction, lack of hands-on experiential learning, and struggles with remote learning such as difficulty focusing, inadequate technology/internet access, and family home environment.

In terms of social interaction with their peers, most students did not find that social media entirely replaced face-to-face contact but was an addition to their overall social experience. The absence of social togetherness has led to a feeling of isolation during the pandemic.

“People have become creative at finding ways to connect during the pandemic,” says Waring. “But many college students are in a life stage where social interaction is about being with your peers and making friends and romantic connections, and the lack of in-person activities has been very hard for many undergraduate students.”

Waring and team developed a survey based on insights provided by the focus groups. Then, in December 2020 and January 2021, their team recruited more than 1,000 undergraduate students from over 100 colleges and universities to complete this survey. While they are currently analyzing these data, Waring shared some of their preliminary findings.

“We expected the pandemic to decrease some students’ sense of belonging in STEM or erode their confidence and motivation to succeed in STEM. While we did see that happening for many students, we were a little surprised that for some students remote learning increased their sense of belonging, confidence and motivation to succeed in STEM. We’re interested in looking at what factors affected these students to help current and future students succeed in STEM.”

“The COVID-19 pandemic has brought many challenges in terms of public health, economics, and education, but I have been really inspired by how faculty, students and universities have risen to the challenge to continue to engage in meaningful intellectual thought and research,” Waring asserts. “I am impressed by this generation of undergraduate students that have persisted through this difficult period and I am looking forward to seeing them take the world by storm and see the good they do throughout their lives and careers.”

The research in this article was supported by a RAPID grant, Proposal no. 2028341, from the National Science Foundation.

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Science in School

Exploring stem concepts through the lens of the covid-19 pandemic inspire article.

Author(s): Tamaryin Godinho

Ideas for how to use the COVID-19 pandemic to bring curriculum STEM concepts into focus.

One of the difficulties in engaging students with science and maths teaching is that it can sometimes seem very abstract. Students often ask “when will I ever need to know this?” The COVID-19 pandemic has really brought science to the forefront of people’s everyday lives; as such, it’s an opportunity to discuss STEM concepts with students in a real-world context and demonstrate why they are relevant and important. Over the past year, we have published several articles to facilitate the discussion of curriculum topics in the context of the global pandemic, which are summarized below. 

1. Understand – Pulling together: a collaborative research approach to study COVID-19

This article from European XFEL provides insight into  how scientists responded to the challenge presented by the pandemic . The focus here is not so much on the scientific details but on how research is done, which is something most students (and adults for that matter) don’t have a clear idea of.

2. Understand – Clinical trials count on more than statistics

There has been a great deal of misunderstanding during the pandemic on the part of the public and even politicians regarding the science. This has had important consequences for public health, for example noncompliance with measures to stop the spread of infection. Some of the most serious of these misunderstandings have arisen less from a lack of knowledge of the scientific details than a lack of understanding of how scientific knowledge is gained. The hydroxychloroquine debacle is a good example, and this article explains what went wrong; what key factors need to be taken into account in  clinical research, and why headline results might not be all they seem .

3. Understand – How to understand a COVID-19 test result

Another area where there has been a great deal of public misunderstanding is that of COVID tests and how to interpret a negative test result. This is partly due to a lack of understanding of the basic concepts of specificity and sensitivity, but also due to ignoring  the influence of pre-test probability . This article helps to explain this rather counterintuitive principle, which applies to most yes/no medical and environmental tests. It also contains an interactive infographic from the BMJ to help students understand how pre-test probability affects the outcome.

4. Understand – Vaccines in the spotlight

Vaccination has been key in containing the pandemic. However, despite the fact that vaccination is a well-proven strategy that has saved countless lives over the decades, vaccine hesitancy is a real problem. The new technologies that have gone into the COVID-19 vaccines and the unusually short development times have increased people’s concerns and given anti-vaxxers additional opportunities to spread misinformation. This article explains  the different types of vaccines and how they work , and also provides some information about the development of the COVID-19 vaccines.

5. Teach –

Exponential growth 1: learn the basics from confetti to understand pandemics , exponential growth 2: real-life lessons from the covid-19 pandemic.

Maths can be one of the most difficult subjects to show the everyday relevance of, but the COVID-19 pandemic has really highlighted why it is important for people to understand fundamental mathematical principles. Early in the pandemic, it was clear that many people didn’t understand the concept of exponential growth, which is not easy to visualize intuitively. As a result, they didn’t take the infection rates and recommended containment measures in their countries seriously until it was much too late. The example that is most often used to teach this concept is compound interest, but for children who don’t really have their own money yet, this can make it seem more rather than less abstract. These two articles, aimed at students aged 11–13 or 14–16 years, explain the basic principles using teaching activities based on simple examples such as  folding paper  or the  classical story of rice grains on a chessboard . They then explain how this relates to exponential growth during an epidemic, with exercises to help students understand concepts like  R ,  R 0 , and doubling times, as well as how containment measures such as social distancing affect the rate of disease spread.

Don’t stop there

I hope that these articles, along with the online resources we’ve selected to go with them, will be useful in engaging your students and showing them the value of science. However, it doesn’t need to end there. Although epidemiology is the first field that springs to mind when thinking of science relating to the pandemic, research into COVID-19 and how to deal with it has spanned a wide range of fields, with relevance to almost all school STEM subjects (as well as some non-STEM subjects like politics and economics). There are many additional links that teachers could bring into their lessons depending on their subject and interests. For example, the fabrication of face masks involves materials and engineering, a lot of chemistry work was needed to modify RNA so that it can be used in vaccines, and the biophysical techniques that allowed scientists to determine the  proteins structures  of the viral proteins are based on physical principles like diffraction. You could even challenge older students to research something like COVID-19 vaccine development and list at least one contribution from each of four or five different STEM subjects. There is no better demonstration of the importance of multidisciplinary research.

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• MLA × Cite: MLA Format Ofori-Boadu, Andrea N., Bonku, Rabiatu, Ferguson, Alesia, Fash, Mercy, and Richmond-Bryant, Jennifer. Examining STEM Learning Motivation Challenges in Undergraduate Students During the COVID-19 Pandemic . Retrieved from https://par.nsf.gov/biblio/10410694. ASEE annual conference exposition . Close
• APA × Cite: APA Format Ofori-Boadu, Andrea N., Bonku, Rabiatu, Ferguson, Alesia, Fash, Mercy, & Richmond-Bryant, Jennifer. Examining STEM Learning Motivation Challenges in Undergraduate Students During the COVID-19 Pandemic . ASEE annual conference exposition , (). Retrieved from https://par.nsf.gov/biblio/10410694. Close
• Chicago × Cite: Chicago Format Ofori-Boadu, Andrea N., Bonku, Rabiatu, Ferguson, Alesia, Fash, Mercy, and Richmond-Bryant, Jennifer. "Examining STEM Learning Motivation Challenges in Undergraduate Students During the COVID-19 Pandemic". ASEE annual conference exposition (). Country unknown/Code not available. https://par.nsf.gov/biblio/10410694 . Close
• BibTeX × Cite: BibTeX Format @article{osti_10410694, place = {Country unknown/Code not available}, title = {Examining STEM Learning Motivation Challenges in Undergraduate Students During the COVID-19 Pandemic}, url = {https://par.nsf.gov/biblio/10410694}, abstractNote = {The COVID-19 pandemic disrupted global educational systems with institutions transitioning to e-learning. Undergraduate STEM students complained about lowered motivation to learn and complete STEM course requirements. To better prepare for more effective STEM education delivery during high-risk conditions such as pandemics, it is important to understand the learning motivation challenges (LMCs) experienced by students. As part of a larger national research study investigating decision-making in undergraduate STEM students during COVID-19, the purpose of this research is to examine LMCs experienced by undergraduate STEM students. One hundred and ninety students from six U.S. institutions participated in Qualtrics-based surveys. Utilizing a five-point Likert scale, respondents ranked the extent to which they agreed to LMC statements. Using Qualtrics Data Analysis tools and MS Excel, data from 130 useable surveys was analyzed utilizing descriptive and inferential statistics. Results revealed that regardless of classification, GPA, age, or race, STEM students experienced LMCs. The top five LMCs were: (1) Assignment Overloads; (2) Lack of In-Person Peer Interactions; (3) Uncaring Professors; (4) Lack of In-Person Professor Interactions; and (5) Lack of In-Person Laboratory Experiences. Significant relationships existed between three characteristics (GPA, classification, and age) and few LMCs to include assignment overloads. Students tended to attribute lowered motivation to Institutional and Domestic challenges which were typically out of their control, rather than to Personal challenges which were typically within their control. Crosstab analysis suggested that Sophomores, Asians, as well as students with GPAs between 2.00 and 2.49 and aged 41 to 50 years may be the most vulnerable due to higher dependence on traditional in-person STEM educational environments. Early identification of the most vulnerable students should be quickly followed by interventions. Increased attention towards sophomores may reduce exacerbation of potential sophomore slump and middle-child syndrome. All STEM students require critical domestic, institutional, and personal resources. Institutions should strengthen students’ self-regulation skills and provide increased opportunities for remote peer interactions. Training of faculty and administrators is critical to build institutional capacity to motivate and educate STEM students with diverse characteristics in e-learning environments. Pass/fail policies should be carefully designed and implemented to minimize negative impacts on motivation. Employers should expand orientation and mentoring programs for entry-level employees, particularly for laboratory-based tasks. Research is needed to improve the delivery of STEM laboratory e-learning experiences. Findings inform future research, as well as best practices for improved institutional adaptability and resiliency. These will minimize disruptions to student functioning and performance, reduce attrition, and strengthen progression into the STEM workforce during high-risk conditions such as pandemics. With caution, findings may be extended to non-STEM and non-student populations.}, journal = {ASEE annual conference exposition}, author = {Ofori-Boadu, Andrea N. and Bonku, Rabiatu and Ferguson, Alesia and Fash, Mercy and Richmond-Bryant, Jennifer.}, editor = {Miller, Eva} } Close
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Assessing the impact of COVID-19 on STEM (science, technology, engineering, mathematics) researchers in India

Nikita Mehta Roles: Conceptualization, Data Curation, Formal Analysis, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Vedika Inamdar Roles: Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Arathy Puthillam Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Shivani Chunekar Roles: Data Curation, Formal Analysis Hansika Kapoor Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing Anirudh Tagat Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing Deepa Subramanyam Roles: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing

This article is included in the Wellcome Trust/DBT India Alliance gateway.

This article is included in the Coronavirus (COVID-19) collection.

COVID-19, STEM researchers, gender, health, productivity, disruption

Revised Amendments from Version 1

This version of the paper has been updated based on the reviewers' comments. Specific changes are made as under: 1. Figure 3 is revised to improve readability 2. A report by Wellcome (2020) has been referenced in the introduction to provide more context 3. We have explicitly acknowledged that "While most of these challenges were already faced by many researchers prior to the pandemic, these issues were heightened during the pandemic." 4. We have clarified that "The survey was piloted with 10 STEM researchers who had signed up/expressed interest in participating." 5. The Procedure and Data Analysis sections have been streamlined to improve readability and reduce redundancies. 6. We have revised the use of the term "oppressed" to "underprivileged" throughout the manuscript. 7. We have synthesized the main findings from the paper and added a conclusion section as under: In an attempt to evaluate the challenges faced by STEM researchers in India during the pandemic, disruptions in terms of continuing research, impact on scientific productivity, and declining mental health were reported. Quantitative results indicated that ECRs who were susceptible to research issues like difficulties with data collection and dissemination, and methodological challenges had a large impact on their scientific productivity. Furthermore, difficulty in receiving funding led to an increased disruption of procuring lab supplies. It was also noted that better mental health among ECRs was based on less difficulty in receiving grants, lower change in scientific productivity, and more university and social support. Qualitative findings pointed towards issues with funding and increased work pressure as major reasons for leaving academia. Additionally, interviews with diverse stakeholders suggested a disparate effect of the pandemic on institute heads, suppliers, and funders.

See the authors' detailed response to the review by Katherine Christian See the authors' detailed response to the review by Vineeta Bal

Introduction

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life across the globe and presented unparalleled challenges to the world of work. Furthermore, the economic and social disruption caused by the pandemic was catastrophic (Joint statement by ILO, FAO, IFAD, & WHO, 2020 ). These effects spread across all professions, and academic personnel were not immune to it. The challenges exhibited were in terms of employing flexible teaching approaches, the need to teach courses online, using different platforms to interact with students and colleagues, and innovative ways to carry out research activities ( Superfine, 2020 ).

Since March 2020, nationally mandated physical distancing led research institutes and universities to adhere to government guidelines in response to the pandemic ( Termini & Traver, 2020 ). This resulted in unexpected roadblocks for academic personnel with regards to permitted research operations, abiding to physical distancing guidelines in the laboratory, facility closure, decreased laboratory activities, and shifting to remote working ( Termini & Traver, 2020 ). Further, studies have shown that early career researchers (ECRs), including PhD students and postdoctoral fellows, were affected at the most crucial time in their career development ( Cheng & Song, 2020 ). Researchers had to switch from working on their current research topic to focusing on COVID-19-based research, while others had to terminate or halt their research work altogether. All these changes impacted the scientist’s ability to conduct research, teach, and their scientific productivity as well. A recent report by Wellcome (2020) highlighted that only 29% of individuals pursuing a research career were secure about their job. This suggested concerns about job security among researchers. Additionally, the findings of the report revealed that poor research culture (like, discrimination, harassment, and unhealthy competition) had a significant impact on researcher’s mental health and the quality of research produced ( Wellcome, 2020 ). In light of the challenges encountered by the researchers, it is crucial to further assess how the pandemic affected this research environment.

International studies explored how researchers in science, technology, engineering, and mathematics (STEM) fields were coping with changes in routines, funding, productivity, and the like in the wake of the pandemic ( Byrom, 2020 ; Myers et al ., 2020 ). However, the few studies which assessed this impact in India had a very narrow focus such as understanding the impact on a few aspects like funding delays ( Nandita & Joan, 2022 ), or impact on teaching ( Dar & Lone, 2021 ). While past studies considered gender as a variable, other factors pertinent to India such as caste, religion, and economic background were not taken into account. Our study aims to incorporate these factors to help understand, in a comprehensive manner, the effect of the COVID-19 pandemic on STEM research scientists and stakeholders (suppliers and funders) across India.

Primary research discipline and the effect of COVID-19

The COVID-19 pandemic affected researchers in different fields unevenly ( Myers et al ., 2020 ). Fields related to the bench sciences, that required physical laboratories, and relied on time-sensitive experiments, such as biochemistry, biological sciences, chemistry, and chemical engineering had large declines in research time when compared to pre-pandemic times. On the other hand, fields that required less equipment such as mathematics, statistics, computer science, and economics reported lower levels of decline in research time ( Myers et al ., 2020 ).

Furthermore, Korbel and Stegle (2020) found that one to six months of research work had been lost due to the shutdown of laboratories and that there was a notable difference between dry labs and wet labs. Researchers working in a wet lab reported a greater effect of the pandemic on their work when compared to dry lab researchers ( Korbel & Stegle, 2020 ).

COVID-19 effects on teaching

In addition to difficulties in conducting research, there were other multitude of challenges faced by academic personnel in the domain of teaching. Some of the challenges with online teaching were broadly categorised under accessibility, affordability, flexibility, learning pedagogy, life-long learning, and education policy ( Murgatrotd, 2020 , as cited in Pokhrel & Chhetri, 2021 ). Additionally, many countries lacked reliable internet connection and access to digital sources required for online teaching as well as learning ( Pokhrel & Chhetri, 2021 ). This made online teaching extremely difficult for both teachers as well as students.

Researchers, who worked in STEM fields in Australia, reported increased challenges in student supervision due to the lack of face-to-face communication, and those with teaching responsibilities had increased teaching workload due to online teaching, thus limiting their research capacity ( EMCR Forum, 2020 ).

Difficulty conducting research online

The COVID-19 pandemic changed the way in which we conduct research ( Mitchell, 2021 ). Individuals who were the most affected were those who lack digital literacy or access to different technologies and research tools required to conduct research online ( Mitchell, 2021 ). Further, a lack of in-person communication and timeliness led researchers to use online surveys and rating scales to conduct research ( De Man et al ., 2021 ), reducing diversity in methodologies.

Clinical trials for stem cell research were gravely impacted by the pandemic as peer review processes could not be worked on without laboratory experiments. In addition, the productivity of stem cell researchers took a hit, especially those amidst a career transition ( Kent et al ., 2020 ).

The transition to remote working made it necessary for researchers to have a certain minimum level of digital literacy. Findings from Yazon et al .'s (2019) study revealed a strong association between faculty members’ digital literacy and competence to their productivity in research. An increase in understanding, finding, and using information on digital platforms was positively related to faculty members’ ability to conduct research, complete, present, and publish a research article.

In addition to the need for digital literacy among educators, the introduction of virtual laboratories for engineering education involved special training of educators to conduct lab classes. This transformation was received well by both teachers and students ( Kapilan et al ., 2021 ).

Impact of COVID-19 on early career researchers (ECRs)

Scientists at all stages of their careers were impacted by the pandemic; however, early career researchers were significantly vulnerable. A significant impact of the pandemic on ECRs was noted in terms of research productivity, timeline of conducting experiments and research studies, insufficient funding, and interaction with other scientists ( Termini & Traver, 2020 ). The consequences of these effects were especially severe among the ECRs as it is a crucial period for development and advancement of their career. COVID-19 restrictions led to limitations in collaborative research, informal exchange of ideas, community building, and training offered by the traditional laboratory setting. Furthermore, researchers had insufficient funding due to which they were unable to continue research work and provide scholarly contributions. For some researchers, time-sensitive experiments (e.g., those involving frozen materials) or premature termination of experiments had a negative effect on their studies and also prevented submission of manuscripts due to delays in research work ( Termini & Traver, 2020 ).

In many cases, open search in the job market was put on hold, due to which ECRs were unable to progress in their careers. Additionally, postdocs who were near the end of their contract had difficulty getting employed and thus, many of them sought employment in non-academic sectors ( Termini & Traver, 2020 ). Most researchers argued that the pandemic had negatively impacted their career prospects ( Woolston, 2020a ). However, another study noted that while students made short-term academic changes that affected their graduation, there were no serious changes to their career plans ( Forakis et al ., 2020 ).

A study by Byrom (2020) found that three-fourths of the participants (doctoral students and ECRs from the UK) experienced a negative impact of the lockdown restrictions on their ability to collect data, discuss ideas and findings with colleagues, and disseminate their research findings. Other participants also mentioned that there was a negative impact on data analysis, writing, and working on grant or fellowship applications. Further, there was reduced or no access to the software required for their research work. This decreased ability to work led to stress and worry about researchers’ future plans which resulted in low levels of mental well-being, culminating in mental distress. Additionally, it was found that researchers who had lesser social support networks within and beyond academia tended to struggle with their mental well-being. Administrative burden undertaken by junior researchers due to remote work arrangements contributed to pressure for ECRs ( Matthews et al ., 2021 ).

Researchers faced high levels of stress ( Shin & Jung, 2014 , as cited in Camerlink et al ., 2021 ) and uncertainty with regards to job position ( Castellacci & Vinas-Bardolet, 2021 , as cited in Camerlink et al ., 2021 ) especially since the onset of the pandemic. It was noted that researchers were facing additional mental health challenges and a reduction in life satisfaction due to the pandemic ( Ammar et al ., 2020 , as cited in Camerlink et al ., 2021 ).

The Australian Academy of Science, Early and Mid-career Researchers (EMCR) Forum conducted a national survey (2020) to understand the impact of COVID-19 on EMCRs in STEM fields in Australia. They found that the pandemic had a significant impact on mental health and productivity of scientists. Researchers perceived a loss of their career prospects and increased anxiety due to uncertain employment situations.

Gender, race, and impact on research productivity during COVID-19

The stay-at-home orders, lockdowns, and school closures affected scientists, especially those who had to take care of children and elders ( Kowal et al ., 2020 ; Myers et al ., 2020 ). STEMM (science, technology, engineering, mathematics, and medicine) faculty had to manage their laboratory, transition to remote working, transfer courses to online platforms, continue to be academically productive and also, simultaneously take care of, and home-school their children ( Krukowski et al ., 2021 ).

The notion that the lockdown had a differential impact on men and women received considerable recognition ( Muric et al ., 2021 ; Yildirim & Eslen-Ziya, 2021 ). Women academic personnel faced unequal work-life balance challenges during the pandemic, which led to a reduction in the time spent on research hours as compared to men ( Deryugina et al ., 2021 ; Myers et al ., 2020 ). In a dual-academic relationship, women were more likely to get lesser support at home than men ( King & Frederickson, 2021 ). Research indicated that women were significantly underrepresented in tenured faculty positions ( Snyder et al ., 2019 , as cited in King & Frederickson, 2021 ), particularly in STEM fields ( Burrelli, 2008 , as cited in Fox, 2001 ; King & Frederickson, 2021 ).

In general, productivity in academia is characterised by submitting grants and articles, publication success, as well as other activities, such as peer review and serving on funding panels, which are essential for promotion and tenure ( Krukowski et al ., 2021 ). A study by Krukowski et al . (2021) found significant changes in productivity before and during the pandemic, with significantly fewer first/corresponding and co-authored articles submitted by women researchers. Further, there were significant decreases in productivity for individuals with children younger than the age of 6 years at home. However, on the other hand, individuals with children between the ages of 6 and 18 years at home, reported significant increase or stable productivity.

Additionally, women’s rate of productivity in last authorship positions declined significantly, suggesting that women were being underrepresented in prestigious, and all other authorship positions. This led to an increased inequality between both genders during the pandemic. Further, there was a significant reduction in women authorships in the first, middle, last, and sole author positions in articles deposited to the arXiv repository, which covers preprints in the fields of physics, maths, statistics, biology, to name a few ( King & Frederickson, 2021 ). It was also noted that the daily routine of women researchers due to having children was disproportionately affected by the lockdown as compared to men. Thus, on account of the increased domestic burden and child care responsibilities during COVID-19, their integrated impact on career productivity was a threat to tenure and promotion of early career women researchers ( Cardel et al ., 2020 ).

Among biodiversity researchers and conservationists in India, COVID-19 affected research, education, communication, networking, and on-field research activities ( Ramvilas et al ., 2021 ). In a national study, it was noted that female EMCRs with caring responsibilities, researchers who were early in their career, and researchers working on contract were the groups that were most impacted by the pandemic ( EMCR Forum, 2020 ).

Apart from gender, an ethnographic study in India had noted that Brahmins and other upper castes dominated in science, medicine, engineering, and academic professions and culturally shaped institutions based on their caste identities ( Thomas, 2020 ). In a survey conducted by National Institutes of Health (NIH) to understand the impact of the pandemic on scientists belonging to underrepresented racial and ethnic groups, participants reported a decrease in research productivity ( NIH, 2020 ). A study of scientists in the USA revealed that male researchers without children were the least affected group in terms of productivity during the pandemic as compared to Black mothers, which were the most affected. Racism against black women in academia was also highlighted ( Staniscuaski et al ., 2021 ).

Institutional and social support

In a study conducted by Ogilvie et al . (2020) to understand graduate students’ experiences during the pandemic, most of the respondents mentioned that they received more support from their advisors, professors, and peers rather than from college or university administrators. Additionally, they also reported more support in terms of physical and mental well-being as compared to economic well-being ( Ogilvie et al ., 2020 ).

In developing countries such as Bangladesh, it was argued that institutional support during the pandemic was important to fill the academic gap that emerged due to the transition to a virtual education system ( Ullah et al ., 2021 ). Institutional support links various stakeholders to resources, expertise, and emotional support allowing navigation through the institution effectively and successfully ( Ullah et al ., 2021 ). Ullah et al . (2021) assessed the amount of institutional support received in Bangladesh for online education during the pandemic. They found that even though a few universities provided average support for continuing online education, several problems such as lack of software to conduct classes online, lack of training, lack of smartphones, poor internet access, etc. were prevalent.

Impact of the pandemic on funders and suppliers

In an interview conducted by Nature Communications ( Matthews et al ., 2021 ), STEM researchers noted several changes that had occurred in research funding for STEM, and overall in the scientific community. Many funding agencies eased eligibility criteria in order to accommodate students who required funding. Researchers acknowledge that while budget cuts might last longer than the pandemic, philanthropic donations may aid the situation of public universities ( Matthews et al ., 2021 ).

The operations and supply chain management were influenced by the COVID-19 pandemic to a large extent ( Lin et al ., 2020 as cited in Queiroz et al ., 2020 ). Disruptions to any of the global supply chains (e.g., closed or partially closed manufacturing units, airports operating with harsh restrictions, shortage of medical equipment and supplies), could lead to the experience of ripple effects by many industries like, medical equipment, consumer good, to name a few ( Dolgui et al ., 2018 ; Ivanov, 2020a ; Ivanov, 2022 , as cited in Queiroz et al ., 2020 ). Further, there was an increase in demand for necessary items such as personal protective equipment (PPE), ventilators, and canned foods due to the pandemic. However, because of the various challenges faced by supply, transportation, and manufacturing units, there was a reduction in their capacities. The challenges faced by these units included border closures, lockdown in the markets, interruption in vehicle movement, suspension of international trade, labour shortage, and maintaining physical distancing in manufacturing facilities ( Amankwah-Amoah, 2020 ; Paul & Chowdhury, 2020 , as cited in Chowdhury et al ., 2021 ). This substantially affected the suppliers’ ability to deliver products on time ( Ivanov & Das, 2020 , as cited in Chowdhury et al ., 2021 ). Researchers across the world faced difficulties in securing supplies like gloves, micropipettes, pipette tips, centrifuge tubes, and other laboratory basics leading to an increased demand while the manufacturing and the distribution channels were disrupted ( Woolston, 2021 ).

The world’s major scientific funders modified their funding policies in response to COVID-19 ( Stoye, 2020 ). Horizon 2020, a European funding programme for research and innovation, provided researchers with extensions in their funding, and also allowed them to reallocate funds to working remotely and paying salaries of researchers who could not continue with their experiments because of the lockdown. Further, reorientation of the projects to research on COVID-19 was also supported. Other funding institutions such as Cancer Research UK, the Wellcome Trust, US National Institutes of Health (NIH), US National Science Foundation (NSF), and many more provided maximum flexibility and relief to researchers impacted by the pandemic ( Stoye, 2020 ). The NIH established the COVID-19 supplemental fund to assist affected researchers. They extended the early-stage investigator status and provided significant flexibility in terms of grant money utilisation ( NIH, 2020 ).

Funding agencies in China, Italy, UK, and USA provided no-cost grant extensions and extended grant deadlines ( Colbert et al ., 2020 ). The Canadian Institutes of Health Research (CIHR), a health research investment agency, also implemented gender policy interventions during the COVID-19 funding competition that included extending deadlines and factoring sex/gender into the grant requirements. It was noticed that the CIHR received more applications and awarded a greater proportion of grants to female scientists compared to male scientists. Along with that, many funded studies considered sex and gender in COVID-19 related research ( Witteman et al ., 2021 ).

Impact on STEM students (or those without a PhD degree)

A study by Gupta et al . (2021) reported that most US students' academic path was affected due to the pandemic, while also creating a challenge in completing coursework for degree requirements. Further, they faced difficulty with regards to remote learning, displacement, and loss of opportunities. It was also noted that STEM majors showed concerns with regards to finding internship opportunities, quality of learning, academic performance, and being unprepared for on-site lab and advanced courses.

Another research from the US reported that restrictions on access to resources and facilities along with academic coursework-related challenges led to a delay in graduation by doctoral, masters, and undergraduate students. It was further noted that Hispanic and Black undergraduates were more likely than Asians and Whites to delay graduation (Report 1; Saw et al ., 2020a ). It was also observed that STEM female faculty and students reported facing more problems adapting to remote learning and technological issues compared to their male colleagues and peers (Report 2; Saw et al. , 2020b ). Furthermore, it was noted that PhD students in Brazil belonging to a minority ethnic group were more likely to be financially disadvantaged compared to white students ( Woolston, 2020b ).

Positive outcomes of the pandemic

Ranganathan et al .'s (2021) study on cancer care during the pandemic also highlighted the increase in value-based health care which involved focusing on a patient’s outcome-based treatment wherein unnecessary tests were avoided and the provider was also monetarily compensated based on the patient's health outcome. This included initiatives such as ‘Choosing Wisely’ for cancer patients, in addition to telephonic consultations. COVID-19 research illustrated efficient ways of doing clinical cancer research that included reduced imaging. This was learnt from large scale practice-defining trials resulting in the modification of existing cancer trial protocols.

COVID-19 also had a significant impact on scientific communication, collaboration, and training. Video conferencing gained importance in terms of meetings, journal clubs, and communication with collaborators. In a study conducted among life science scientists, more than half of the participants suggested that their communication with mentors or supervisors had not changed and a few participants also noted an increase in communication. This indicated that video conferencing was effective in communication and mentoring during the pandemic ( Korbel & Stegle, 2020 ).

It was also noted that e-conferencing among life science scientists was becoming an important format for scientific meetings. During the lockdown, the adoption of e-learning software by life science trainees based in wet labs increased. The trainees wanted to expand their skill set like, learning new programming languages ( Korbel & Stegle, 2020 ). Further, scientists spent more time in data analysis, manuscript or thesis writing, and developing grant applications. Some scientists also indicated shifting their research activities to contribute to COVID-19 related research ( Korbel & Stegle, 2020 ). In sum, even though the pandemic had substantial effects associated with stress and work interruptions among scientists, new ways to cooperate, exchange ideas, and learn via electronic means were some of the positive outcomes of the pandemic ( Korbel & Stegle, 2020 ).

Vast literature emphasised the scope of the impact of COVID-19 pandemic on STEM researchers all over the world. In particular, the pandemic had a significant impact on ECRs, who faced a barrier in the progression of their career, as well as women scientists who were unable to work to their full potential due to household or childcare responsibilities. While most of these challenges were already faced by many researchers prior to the pandemic, these issues were heightened during the pandemic. However, not many of these studies focused on the pandemic’s influence on Indian scientists. Therefore, the current study aims to understand the effect of gender, caste, childcare responsibilities, primary research discipline, transition to online working/ teaching, contracting COVID-19, funding opportunities, and institutional and social support received on scientific productivity, mental health and future career prospects among researchers in India.

Research questions

In the context of emerging strands of literature on the impact of COVID-19 on STEM research, the current study posits the following research questions in the Indian context:

RQ1: What impacts the ability to continue one’s research during the COVID-19 pandemic?

RQ2: What impacts one’s ability to continue to teach during the COVID-19 pandemic?

RQ3: What impacts researcher’s scientific productivity during the COVID-19 pandemic?

RQ4: What impacts mental health among STEM scientists during the COVID-19 pandemic?

RQ5: What has an impact on a STEM scientist’s decision to return to academia, after leaving academia during the COVID-19 pandemic?

RQ6: What has an impact on a STEM scientist’s plan to continue a career in STEM even if they are thinking about leaving academia?

RQ7: What was the differential impact of the pandemic among ECRs, Heads of Institutes, suppliers and funders?

RQ8: What were some of the reasons behind planning to leave academia?

RQ9: What were the reasons and effects of leaving academia?

RQ10: Were there any actionable policy recommendations that arise from various challenges faced by scientists during the pandemic?

Ethical considerations

The study was approved by the Monk Prayogshala Institutional Review Board (FWA-recognized) on 5 th July 2021 (#065-021). Written informed consent from survey participants and audio-recorded consent from interview participants for publication of unidentifiable participant responses was obtained.

The current study employed a mixed method design using both quantitative (survey) and qualitative (interview) methods to collect data from researchers and stakeholders in STEM. To make the survey 1 more accessible to participants and to recruit a representative sample, the survey was made available in ten Indian languages (Hindi: 75, Marathi: 24, Tamil: 13, Kannada: 6, Telugu: 1, Bengali: 18, Gujarati: 7, Malayalam: 11, Oriya: 3, and Assamese: 4) along with English (n = 912).

Participants

Participants were recruited via targeted emails to Institute and Department heads, networks of India Alliance and Dr. Subramanyam, comprehensive database of Central Institutes in India, and snowball sampling through social media campaigns. The sample size for the study was stipulated by the funding agency (DBT/Wellcome Trust India Alliance). The study included participants from India who were 18 years and above, and those studying or working in a STEM-related field. Data from participants were excluded from the analysis if the participant did not consent to participate in the study, the progress for the survey was either 0 or 1, and those younger than the age of 18 years.

Heads of Institutes, suppliers of scientific material, and funders/donors for the interview were recruited using purposive sampling. Contact information for all potential respondents was collected from websites of research institutes, organisations that work in STEM disciplines, government research institutes, universities, companies that supply scientific equipment and funding agencies working in India. Another method of recruiting respondents included using the India Alliance's network of fellows who work in various institutes across the country. The fellows were contacted and asked if they could put the authors in touch with their respective heads of institutes to be interviewed. The study was conducted to obtain representation from all regions of India and from researchers working in government research laboratories, universities, private institutes, and colleges.

Survey . The survey form was designed and circulated online via Qualtrics. It was a self-developed tool that included questions related to participant’s socio-demographics, the effects of COVID-19 on research, funding, scientific productivity, teaching, institutional/social support, mental health, and details on COVID-19 information. Further, the survey also included questions for researchers who had left/were thinking of leaving academia. Double-barrelled questions were avoided in the survey. Furthermore, display and skip logic functions were used in the survey so that participants did not have to respond to questions that were not applicable to them thus reducing fatigue.

Interview . These were scheduled with the heads of institutes, suppliers of scientific materials, funders/donors, ECRs, people who were thinking about leaving academia, and those who had already left academia based on mutual convenience. The interview guides included questions based on COVID-19 effects on the institute, funding, scientific productivity, teaching, and social support. The semi-structured interviews were conducted by Vedika Inamdar, a female research author at the department of sociology at Monk Prayogshala, India. The researcher has a Master of Arts (M.A.) degree and has 3 years of training and experience as a qualitative researcher.

The semi-structured interview schedule was pilot tested. Each online interview typically lasted between 45 to 60 minutes and was recorded (audio and/or visual) on the Zoom Meeting Platform with prior consent of the interviewee for transcription at a later stage. No repeat interviews were conducted for any of the participants. Furthermore, leading questions were not asked in the interviews to avoid biased responses.

The interview schedule and questionnaire can be found as Extended data ( Mehta et al ., 2022 ).

The survey form included quantitative as well as a few qualitative questions for a detailed understanding on individuals experiences during the pandemic. At the end of the survey, participants were debriefed about the study and were provided with the option of entering their email ID to receive a compensation of INR 100 and a certificate of participation from India Alliance and Monk Prayogshala for taking part in the study. All semi-structured interviews were conducted online, using Zoom video-conferencing software and audio-recorded for transcription at a later stage. At the end of the interview, participants were debriefed about the study and were provided with a compensation of INR 1000 and a certificate of participation from India Alliance and Monk Prayogshala for taking part in the study.

Data analysis

Quantitative data were analysed using RStudio software version 1.4.1717 ( RStudio team, 2021 ). The factor structure and internal consistency reliability of the self-developed survey questions were assessed using confirmatory factor analysis (CFA) and Cronbach’s alpha. One-factor CFA models were computed to understand whether the tested variables represented the specified construct. Furthermore, Cronbach's alpha tested to understand the inter-relatedness of the items in a scale. Based on these metrics, indices for digital literacy, core research issues, university support, social support, and mental health were developed. Next, zero-order correlations were assessed based on which regression analysis was computed to assess the proposed research questions. To corroborate these findings, sentiment and content analysis was computed on the descriptive responses provided by the participants. Additionally, interview responses were analysed using thematic analysis. This analysis was coded by two qualitative researchers using the NVivo 20 software (released in March 2020) .

Quantitative results

The participants of this study were STEM ECRs (within 10 years of receiving PhD), senior postdoctoral fellows, researchers with their own labs/groups with less than 10 years of research experience, those having a graduate/postgraduate degree, heads of institutes, suppliers of scientific materials, and funders/donors. A total of 1074 participants took part in the online survey. Participants not meeting the inclusion criteria were excluded; thus, a total of 618 participants were included in the analysis ( Mehta et al ., 2022 ). Specifically, participants who completed the survey in less than 90 seconds (n = 351), those with a progress of 0/1 (n = 81), individuals who did not consent to participate (n = 2), and participants younger than 18 years, those with variables having extreme values, and participants not falling into the criteria for ECRs (especially for those who had their doctoral degree; n = 22) were excluded from analysis. Finally, the dataset was divided into two groups, one for those who had completed their doctoral or postdoctoral training (N = 300) and another for those who have only completed their post-graduation or graduation (N = 318). The sample size reduced further for certain variables owing to missing data (refer to the descriptive tables for more detail).

Participants having a doctoral or a postdoctoral degree

Descriptive statistics. The dataset included a total of 150 men, and 141 women (6 participants preferred not to disclose their gender) having a mean age of 39.43 years (SD = 7.46). Out of the total number of participants, 162 individuals had a doctorate (MD or PhD) degree and 138 individuals had completed their postdoctoral training. Additionally, 149 of the total participants belonged to a dominant caste group (Brahmin, Kshatriya, Vaishya, and other upper castes) whereas, 36 participants belonged to an underprivileged caste group (Scheduled Caste, Scheduled Tribe, Other Backward Class, and other lower castes), while the remaining participants did not disclose their caste details. For more details, refer to Table 1 and Table 2 in the Appendix .

Reliability and validity. Indices for variables such as digital literacy, core research issues, university support, social support, and mental health were developed. Cronbach’s alpha and confirmatory factor analysis using the MLR (robust maximum likelihood) method of estimation was computed in order to evaluate the psychometric properties of the indices. Additionally, since digital literacy, core research issues, and social support indices were found to be non-normal (see Table 3 ), a DWLS (diagonally weighted least squares) method of estimation was also computed to assess index validity. For the factor models, fit was measured by evaluating the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and standardised root mean square residual (SRMR), in order to determine optimal fit (see Table 4 ). According to the widely used criteria, a cut-off value of ≥0.95 for CFI and TLI, ≤0.06 for RMSEA, and ≤0.08 for SRMR indicate a good model fit 2 ( Groskurth et al. , 2021 ; Hu & Bentler, 1999 ).

Table 3. Shapiro-Wilk test of normality.

Note. W = Shapiro–Wilk test statistic

Table 4. One-factor confirmatory factor analysis using robust maximum likelihood (MLR) and diagonally weighted least squares (DWLS) methods.

Note. CFI = Comparative Fit Index, TLI = Tucker Lewis Index, RMSEA = Root Mean Square Error of Approximation, SRMR = Standardized Root Mean Square Residual.

For the dataset involving individuals who had completed their PhD or postdoctoral degree, it was noted that the digital literacy index ( α = 0.93), the core research issues index ( α = 0.80), university support index ( α = 0.84), social support index ( α = 0.72), and the mental health index ( α = 0.70,) had a good internal consistency reliability. 3

The core research issues index involved items related to difficulty in discussing research with colleagues, difficulty in data collection, difficulty in dissemination, methodological challenges, lab staff being asked to leave, decrease in lab staff, staff leaving affecting performance, and staff unable to continue research work on campus. The digital literacy index measured the participants’ ability to access email, virtually access bank accounts, use digital technologies, video conferencing, online file sharing, and learning new technology without the help of a third party.

University support index included the extent of physical, mental, material, and economic support received from university professors and administrators. Furthermore, support received from the university in terms of resources, flexibility in work hours, training, monetary assistance, and financial guidance were also measured. Support received from family, relatives, and peers in terms of physical, mental, material, and economic well-being were included in the social support measure. Mental health index included items related to overall mental health, work-life balance, amount of stress and happiness one experienced.

Correlations. A Pearson’s correlation coefficient was computed to understand the relationship between the variables (see Table 5 ). It was noted that if the number of people residing in a household along with those below the age of 18 years increased, one’s access to independent workspace reduced. Additionally, a negative impact on teaching was positively correlated to difficulty in migrating to online teaching.

Table 5. Correlation matrix (participants with a doctorate/post doctorate degree).

Note. * p < .05. ** p < .01.

To further summarise the findings, greater social support was correlated with lower core research issues, a decrease in impact on supervisory role, and a decrease of negative impact on teaching. On the other hand, decrease in university support is correlated to an increase in disruption of lab supplies, core research issues, delay in PhD degree, delay in postdoc completion, disruption in receiving a grant or fellowship, personal financial instability, and impact on supervisory role. In terms of scientific productivity, an adverse change in productivity was related to an increased reliance on a lab to conduct research, dependency on interaction with human participants, disruption in lab supplies, core research issues, and a lower university support.

Finally, better mental health was correlated with increase in access to an independent workspace, better stable internet connection, and greater social and university support. Additionally, better mental health was also related to decrease in disruption of lab supplies, reduced difficulty receiving a grant, greater personal financial security, no change in productivity, lower impact on supervisory role, decreased difficulty migrating to online teaching, and a reduction in students' PhD degrees delay and postdoctoral scholars’ training delay.

Regression analysis 4 . Based on significant correlations between variables, multiple regression models were computed using pairwise deletion (lavaan; Rosseel, 2012 ) to answer each above-mentioned research question (see Table 6 ). Additionally, regression analysis was also performed on disaggregated datasets based on gender (males and females) and caste (dominant and underprivileged caste). A post hoc power analysis using G*Power 3.1 ( Faul et al ., 2009 ; Faul et al ., 2007 , RRID:SCR_013726) was computed for all the models having at least one significant predictor. It was observed that the models had a high power ranging from 0.95- 1.00 ( α = 0.05) for the differing effect size, sample size, and number of predictors for each model. Regression results allow us to examine specific hypotheses related to certain variables, while controlling for other confounding variables. In this way, the results focus on the statistically significant (or otherwise) association or effect between the explanatory variable and the outcome(s) of interest.

Table 6. Multiple regression model estimates for each research question.

The results 5 ( Figure 1 ) showed that lower mental health significantly predicted a greater number of core research issues ( β = -0.546, z =-2.807, p = 0.005). Furthermore, greater difficulty in receiving a grant, significantly predicted a greater disruption in lab supplies ( β = 0.18, z = 2.345, p (p-value) = 0.019), and a higher digital literacy significantly predicted an increase in the number of working hours in terms of professional development ( β = 0.034, z = 1.959, p = 0.050). This suggests that mental health, difficulty receiving a grant, and digital literacy had a significant impact on one’s ability to continue one’s research during the COVID-19 pandemic (RQ1).

Figure 1. Regression analysis of mental health on core research issues.

Note. The figure shows a negative relationship between mental health and core research issues.

It was observed ( Figure 2a ) that greater disruption in procuring lab supplies had a significantly higher impact on an individual’s supervisory role ( β = 0.254, z = 2.051, p = 0.040). Thus, this might be one of the reasons that affected one’s ability to continue to teach during the COVID-19 pandemic (RQ2). Note that no statistically significant relationship was observed between disruption in lab supply and other aspects of online teaching (e.g., migration to online teaching). Further, greater core research issues predicted an adverse change in researcher’s scientific productivity during the pandemic ( β = 0.024, z = 2.136, p = 0.033; RQ3). Finally, it was noted that STEM scientists’ better mental health (RQ4) was significantly predicted by a lesser difficulty in receiving a grant ( β = -0.343, z = -2.302, p = 0.021, Figure 2b ), a smaller change in scientific productivity ( β = -0.707, z = -2.602, p = 0.009), higher university support ( β = 0.069, z = 2.070, p = 0.038, Figure 2c ), and higher social support ( β = 0.189, z = 3.963, p = 0.00).

Figure 2a. Regression analysis for men and women of lab supplies disruption on supervisory role.

Note. The figure shows a positive relation between disruption of supplies and impact on supervisory role which was stronger and significant for women as compared to men.

Figure 2b. Regression analysis of difficulty of receiving a grant and mental health.

Note. The figure shows a weak negative relation between difficulty receiving a grant and impact on mental health.

Figure 2c. Regression analysis for men and women of university support on mental health.

Note. The figure shows a stronger and significant positive relationship between university support and mental health among men as compared to women.

For men, it was found that greater core research issues were significantly predicted by lower mental health ( β = -0.58, z = -2.152, p = 0.031), and higher the difficulty in receiving a grant predicted a greater disruption in procuring lab supplies ( β = 0.252, z = 2.058, p = 0.040). This suggests that mental health and difficulty receiving a grant were major aspects affecting men’s inability to continue research during the pandemic (RQ1). Furthermore, higher the research dependency on interactions with human participants ( β = 0.175, z = 2.290, p = 0.022) and greater core research issues ( β = 0.039, z = 2.406, p = 0.016) significantly predict adverse changes in scientific productivity for men (RQ3). Higher university support ( β = 0.072, z = 2.151, p = 0.031) and social support ( β = 0.127, z = 2.015, p = 0.044) predicted a better mental health among men (RQ4).

For women, on the other hand, it was noted that lower mental health significantly predicted higher core research issues ( β = -0.547, z = -1.995, p = 0.046) thus, impacting their ability to continue research during the pandemic (RQ1). Additionally, a higher disruption in procuring lab supplies predicted a greater impact on their supervisory role for PhD students ( β = 0.402, z = 2.126, p = 0.033), and a lower mental health predicted a greater the difficulty to migrate to online teaching ( β = -0.091, z = -1.956, p = 0.050) consequently affecting female’s ability to continue to teach (RQ2). Adverse change in scientific productivity (RQ3) was predicted by greater personal financial instability ( β = 0.252, z = 2.850, p = 0.004) and lower mental health ( β = -0.081, z = -2.042, p = 0.041). Greater difficulty receiving a grant ( β = -0.531, z = -2.508, p = 0.012), adverse change in productivity ( β = -0.977, z = -2.929, p = 0.003), and lower social support ( β = 0.220, z = 3.378, p = 0.001) significantly predicted lower mental health for women (RQ4).

For dominant castes, who form a majority in our sample, it was observed that being able to manage switching to remote working ( β = -0.396, z = -2.876, p = 0.004), better stability in internet connection to work remotely ( β = -0.387, z = -2.198, p = 0.028), and lesser disruption in lab supplies ( β = 0.285, z = 2.057, p = 0.040) had a lower impact on one’s supervisory role (RQ2). A better stability in internet connection to work remotely ( β = -0.608, z = -3.888, p = 0.00) and better mental health ( β = -0.103, z = -2.069, p = 0.039) significantly predicted a lower difficulty to migrate to online teaching (RQ2). Further, a higher dependency of working in a physical lab predicted an adverse change in scientific productivity (RQ3; β = 0.242, z = 2.168, p = 0.030). It was also noted that greater social support predicted better mental health ( β = 0.179, z = 2.328, p = 0.020) among the dominant caste group (RQ4). Note that these are not relative to the underprivileged caste group as there was insufficient data on underprivileged caste group members in the survey.

The underprivileged caste group had a very small sample size (n = 36); hence, the correlations potentially show spurious relationships that might lead to inaccurate inferences, and as a result, are not reported here.

For those who had left academia (RQ5; N = 23) or were thinking about leaving academia (RQ6; N= 24), due to a small sample size, statistically robust and reliable results were not obtained. Hence, qualitative data was used to gauge a scientist’s reasons for leaving or considering leaving academia. This is discussed in the following section.

Participants having a graduate or a postgraduate degree (i.e., not a PhD)

Descriptive statistics. A total of 175 individuals identified as men, 134 individuals identified as women, and 2 individuals identified as non-binary/transgender (4 participants prefered not to respond). The sample had a mean age of 29.34 years (SD= 8.26) and 177 of the total participants belonged to a dominant caste group (Brahmin, Kshatriya, Vaishya, and other upper castes) whereas, 55 participants belonged to an underprivileged caste group (Scheduled Caste, Scheduled Tribe, Other Backward Class, and other lower castes). For more details, refer to Table 7 and Table 8 in the Appendix .

Reliability and validity. Internal consistency reliability and CFA using MLR method of estimation was computed to evaluate their psychometric properties of the indices. Since, the data for all the indices was not normal (see Table 9 ), DWLS estimation was also used to evaluate the validity of the indices (see Table 10 ). For the dataset involving individuals who had completed their graduate or postgraduate degree, it was noted that the digital literacy index ( α = 0.90, robust CFI= 0.980), the core research issues index ( α = 0.74, robust CFI= 0.986), university support index ( α = 0.89, robust CFI= 0.818), social support index ( α = 0.83, robust CFI= 0.787), and the mental health index ( α = 0.76, robust CFI= 1.00) had a good internal consistency reliability and an adequate model fit¹ ( Groskurth et al ., 2021 ).

Table 9. Shapiro-Wilk test of normality (participants with a graduate/postgraduate degree).

Note. W = Shapiro–Wilk test statistic.

Table 10. One-factor confirmatory factor analysis using robust maximum likelihood (MLR) and diagonally weighted least squares (DWLS) methods (participants with a graduate/postgraduate degree).

The core research issues index involved items related to difficulty in discussing research with colleagues, difficulty in data collection, difficulty in dissemination, and methodological challenges faced while conducting research. The digital literacy index measured the participants ability to access email, virtually access bank accounts, use digital technologies, video conferencing, online file sharing, and learning new technology without the help of a third party.

University support index included the extent of physical, mental, material, and economic support received from university professors and administrators. Furthermore, support received from the university in terms of resources, flexibility in work hours, training, monetary assistance, and financial guidance was also measured. Support received from family, relatives, and peers in terms of physical, mental, material, and economic well-being were included in the social support measure. Mental health index comprised items related to overall mental health, work-life balance, and the amount of happiness one experienced.

Regression analysis. Based on significant correlations between variables (see Table 11 ), multiple regression models were computed using pairwise deletion (lavaan; Rosseel, 2012 ) to answer each of the above-mentioned research questions (see Table 12 ). Additionally, regression analysis was also performed on disaggregated datasets based on gender (men and women) and caste (dominant and underprivileged caste). A post hoc power analysis using G*Power 3.1 ( Faul et al ., 2009 ) was computed for all the models having at least one significant predictor. It was observed that the models had a high power ranging from 0.99-1.00 ( α = 0.05) for the differing effect size, sample size, and number of predictors for each model.

Table 11. Correlation matrix (participants with a graduate/postgraduate degree).

Note . * p < .05. ** p < .01.

Table 12. Multiple Regression model estimates (participants with a graduate/postgraduate degree).

The results showed that a greater difficulty in receiving a grant ( β = 0.548, z = 2.082, p = 0.037) and a greater financial insecurity in the household ( β = 0.848, z = 2.284, p = 0.022) significantly predicted higher core research issues. Further, greater difficulty in receiving a grant also predicted a higher disruption in lab supplies ( β = 0.375, z = 3.569, p = 0.00). It was also observed that an adverse change in scientific productivity was predicted by higher core research issues ( β = 0.080, z = 2.835, p = 0.005) and greater support from the university predicted better mental health ( β = 0.084, z = 2.628, p = 0.009).

Among men, it was found that household financial instability significantly predicted core research issues ( β = 0.987, z = 2.014, p = 0.044) and core research issues predicted an adverse change in scientific productivity ( β = 0.115, z = 2.605, p = 0.009). Furthermore, it was noted that a stable internet connection to work remotely ( β = 0.677, z = 2.083, p = 0.037) and greater support from the university ( β = 0.097, z = 2.093, p = 0.036) predicted better mental health among men.

For women, difficulty in receiving a grant significantly predicted a greater disruption in lab supplies ( β = 0.444, z = 2.958, p = 0.003) and, a lower disruption in lab supplies predicted a greater change in one’s scientific productivity ( β = -0.282, z = -2.078, p = 0.038). Additionally, greater difficulty in receiving a grant predicted an adverse change in scientific productivity among women ( β = 0.374, z = 2.187, p = 0.029).

Greater household financial insecurity predicted more core research issues ( β = 0.998, z = 2.309, p = 0.021) among the dominant caste. Further, greater difficulty in receiving a grant also predicted a higher disruption in lab supplies ( β = 0.454, z = 2.688, p = 0.007). It was also observed that access to an independent workspace to work from home ( β = 0.941, z = 2.625, p = 0.009) and greater support received from the university ( β = 0.125, z = 3.126, p = 0.002) significantly predicted better mental health for the dominant caste groups. Due to a small sample size for the underprivileged caste groups (n =55), the correlations were spurious and unreliable to interpret hence, are not reported and included in the analysis.

For those who had left academia (N = 78) or were thinking about leaving academia (N= 25), due to a small sample size, deducible and reliable results cannot be obtained. Hence, qualitative data will be used as a way to gauge people’s reasons for leaving or considering leaving academia.

Qualitative results

Sentiment analysis was computed to identify the emotional tone for the qualitative questions included in the survey using RStudio. Furthermore, thematic analysis was conducted to analyse the interview responses using the NVivo 20 software (Released in March 2020) .

Sentiment analysis

Using the ‘bing’ dictionary within the ‘dplyr’ package in R Studio software version 1.4.1717 ( RStudio team, 2021 ), we explored whether certain qualitative descriptive responses were positively or negatively coded. Specifically, certain emotionally-loaded words were examined and classified at the document level. First, each response for each question was unnested into unigrams (i.e., single words); these words were then assigned positive/negative scores. Next, we further listed the phrases in context using the “keyword in context” function in the “quanteda” package. This function returns words in the immediate context of provided keywords. The main results are summarised in Figure 3 .

Figure 3. Sentiment analyses results.

Note: Graphs summarise positive and negative sentiment frequencies of number of words used in a random 6% sample of all descriptive responses provided by survey participants.

Methodological challenges. We found that the overall sentiment regarding methodological issues were negative, with 73 negatively coded words, and 30 positively coded words. Words such as “broke,” “burden,” and “challenging” were used when participants were asked about methodological challenges.

Words related to “method,” “work,” and “research” were “stopping” their own research work, “remote data collection,” having to change their methods, and not being able to work.

Professional development . A total of 16 positive (e.g., accessible, easy, efficient) and 13 negative words (e.g., delays, backward, and burden) were used to describe the changes in professional development. Using the keywords “profession,” “develop,” and “skill,” we found that participants discussed having more time for professional development, and participating in programmes and workshops online. As there were a small number of responses, the impact of the pandemic on professional development is inconclusive.

Impact on teaching. To describe the negative effects of the pandemic on teaching, participants used 36 negatively coded terms (e.g., abysmally, anxiety, cheating) and 26 positive ones (e.g., attentive, comfortable, confident). This included discussions about not being comfortable teaching online, lack of lab tutorials and practicals, and lack of feedback and engagement with students. The higher number of negative words indicate the difficulties academic personnel faced while teaching in the pandemic.

Scientific productivity. In total, 52 negative words (e.g., delays) and 32 positive words (e.g., engaging, productive) were used to describe changes in scientific productivity. Participants discussed how there were personal and health-based issues, as well as having spent time trying to keep the lab running, rather than on science. In other words, administrative duties and personal issues took away from being productive. On the other hand, once lockdown restrictions were lifted, participants reported being productive. Similarly, one participant discussed re-planning experiments such that a single person could run them. This suggests that researchers’ productivity was affected negatively during the lockdown.

Mental health. To describe reasons for stress, 113 negative words (e.g., anxiety, burden, chronic) and 35 positive words were used. Participants described a lack of social interaction, physical activities, being isolated, increase in workload, among other difficulties. The following keywords were used: “stress,” “because,” “anxious,” “anxiety,” “nerv,” “deal,” “mental,” “health.” These yielded responses describing helplessness, death anxiety, and stress related to financial and career trajectories.

Long-term plans. Five positive and three negative words were used to describe long-term plans after quitting. These include description of life as uncertain and requiring health and money; further, a few described wanting to switch to industry jobs, and general discontent with academia in India.

Reasons for leaving. Overall, 12 negative words and nine positive words were used to describe reasons for leaving academia. Participants described a lack of money, an abundance of bureaucratic and administrative issues and duties. Further, the reduced number of research positions and salary delays were mentioned.

Recommendations. Participants used more positive than negative words when asked about recommendations for improving academic experiences. These included transparency, growth opportunities, timely disbursements of funds, improving diversity, and other professional development opportunities.

Content analysis

Reasons for leaving academia. Participants who had completed their PhD/post doc reported that the major reasons for leaving academia (RQ5; see Table 13 ) were: reduced funding/money (e.g. “No pay for 6 months due to delays in grant release with no support from the institution to ensure the grant gets released.”), , increased work pressure and workload (e.g. “Too much work, too many research projects + online teaching, constantly on a computer with no time for personal work which started interfering with my health.”), child-care responsibility (e.g. “Need for partial work-from-home options to balance childcare needs.”), and lack of opportunities (e.g. “The pandemic also shut doors to various available research opportunities.”).

Table 13. Content analysis to understand a STEM scientist’s decision to leave academia.

Note. Includes responses from 21 participants; some participants noted multiple reasons.

Reasons for thinking about leaving academia. Those ECRs who were thinking about leaving academia (RQ6; see Table 14 ) mentioned lack of funding (e.g. “Reduced funding”), poor work culture (e.g. “Unfair professional assessment at workplace”), issues related to salary/money (e.g. “Not sure when salary for myself and the other research staff will be released”), lack of support (e.g. “Lack of support from upper management”), higher work pressure and workload (e.g. “A lot of pressure”), bureaucratic issues (e.g. “Unfair, hypocritical, opaque system.”), and lack of job stability/security (e.g. “Lack of job stability”) as reasons.

Table 14. Content analysis to understand a STEM scientist’s reason for thinking of leaving academia.

Note. Includes responses from 22 participants; some participants noted multiple reasons.

Thematic analysis

From 341 emails sent to the stakeholders to participate in the interview, the researchers did not receive any response from about 317 participants. Extensive and detailed interviews of 24 stakeholders were conducted to determine their views on the impact of the pandemic on research and the functioning of their organisation and employees. The interviews included a subsample of heads of institutes, representatives from funding agencies, suppliers of scientific equipment and materials, other stakeholders, and ECRs. Due to the unavailability and non-response from the funding agencies and suppliers of scientific equipment, 4 other stakeholders were interviewed (presented as individual case studies).

From the 258 emails sent to the HoIs, 22 funding agencies, and 40 suppliers approached, only 8 HoIs, 3 funders, and 4 suppliers agreed to participate in the interview. Additionally, interviews were conducted with 5 ECRs (from the 21 ECRs who were approached) who elaborated on their reasons for planning to leave academia. Finally, 4 additional stakeholders working in Indian STEM were also interviewed to understand their perspective of the impact on COVID-19 on researchers in India.

For conducting thematic analysis, two researchers coded the interview transcripts. The responses were coded according to the predetermined codes from the interview guide and the literature review conducted for the study while, a few were derived from the data. Following this, through discussion, the researchers came to a consensus on the themes and the codes that the interview responses revealed. The variation in qualitative research designs compounds the intricacies of the saturation question along with the multiple methods of data collection ( Sebele-Mpofu, 2020 ). Given that predetermined codes (based on the literature review and the questionnaire built on the literature review) were used to analyse the responses in our study, the concept of thematic saturation does not necessarily apply to the current analysis as the study is based on prior research.

Heads of Institutes (HoIs). In understanding the effects of COVID-19 on the institute, HoIs mentioned the impact of the pandemic on research within the institute, digital literacy training for researchers, enforcement of formal policies, challenges associated with virtual mode of communication, deadline-related challenges, and changes in their roles and responsibilities. Furthermore, effects of the pandemic on funding for projects and laboratories, procurement of scientific equipment due to funding, attrition within the institute, influence on hiring, and the impact on scientific productivity were discussed.

The HoI’s also mentioned the change in the proportion of time spent on research supervision, administrative duties, and teaching. In terms of teaching, they discussed the specific requests/challenges experienced by students and teachers along with the shift to online teaching and assessment. Finally, the support received from institutes in terms of flexibility in working hours, connecting to nearby hospitals, and concessions in paying tuition fees for students were highlighted. Additional specialised support for members with childcare responsibilities and specific grievance redressal mechanisms were also provided by the institutes. For a detailed summary of the interview responses with HoIs, refer to the Extended data .

Funding agencies. Between the three funders interviewed, they fund research in India in the range of USD 14 million, 108 million, and 344 million (only the last figure is for global grants funded). Thus, each operates at a different scale, thematic funding area, and in varying geographical contexts. The major themes that were discussed by the funders included the impact on research output of the institute, effect on future project and funding timelines, changes in funding policies, increase in COVID-19 related research funding, and support to research institutes during the pandemic. For a detailed summary of funding agency responses, refer to the Extended data .

Suppliers of scientific equipment. The four suppliers who agreed to be interviewed conduct business in products involving high-end imaging platforms, equipment for clinical diagnostics, nuclear research supplies, and telescopes. Each of these operate at a different scale, products, and in varying geographical contexts. The findings for ‘COVID-19 Effects on supply of scientific equipment’ noted the following themes: challenges associated with supply of scientific products, change in demands to COVID-19 testing, diagnostics and research from scientists, and the digital mode of marketing and interactions. Furthermore, the supply was impacted due to change in obtaining funding and payment terms. To understand the challenges faced by suppliers due to the pandemic in detail, refer to the Extended data .

ECRs who had left or were planning to leave academia. The ECRs were interviewed specifically on their motivations and reasons vis-a-vis leaving or planning to leave academia. The major themes of not being able to do their desired work, difficulty with online teaching, funding difficulties, appraisal and salary issues, overwork, lack of stability and opportunities were highlighted as reasons for leaving or thinking about leaving academia. For a detailed summary of ECR responses, refer to the Extended data .

Other important stakeholders in Indian STEM. The stakeholders interviewed ranged from research and innovation hubs to companies that bridge the gap between suppliers of scientific equipment and scientists. It also involved platforms that provide communication between life science researchers in India. All the organisations mentioned that research, funding, and supply was directed towards COVID-19 research and efforts during the pandemic. Lockdown restrictions paused research for scientists and supply of materials for research. The pandemic also provided a time for innovation that was geared toward public health and increased virtual communication between researchers and scientists across the country. Suggestions from interviews with these stakeholders focused on increased and equitable funding for research institutes across the country and on timely payments for scientists from funding agencies. Another suggestion was based on reduction of bureaucratic and additional administrative procedures that become an obstacle for scientists in applying for funding. Similarly, scientists and research laboratories face delays due to extensive bureaucratic procedures in taking their research to its final development stage. For a detailed summary of other stakeholder case studies, refer to the Extended data .

The purpose of this study was to obtain data to help us understand the comprehensive effect of the COVID-19 pandemic on STEM researchers and stakeholders (suppliers and funders) across India. It was noted from the findings that certain antecedents significantly predicted STEM scientists’ ability to continue research work, teaching, maintain productivity, and mental health during the pandemic. The study highlighted the various challenges faced by early career researchers, and STEM scientists at various positions in their careers during the COVID-19 restrictions in India.

Extensive research since the onset of the COVID-19 pandemic that focused on its impact on the scientific community, as well as their productivity was conducted. A large number of these studies focused on the disproportionate impact of the pandemic as well as associated lockdown restrictions on female and traditionally underrepresented scientists around the world. These studies have pointed squarely to a larger penalty imposed on female scientists as a result of gendered norms of caregiving and lack of equal opportunities, among others.

Distressingly, our study pointed towards a larger toll on the mental well-being of female early-career researchers (ECRs) in India. Our research focused on ECRs, as they were at a career stage often characterised by job uncertainty, lack of new job opportunities, and a lack of funding ( López-Vergès et al ., 2021 ). Thus, that the impact of the pandemic was magnified on this particular sample of researchers. This impact was evident across many fields and found in other large-scale survey work, both during the early stages of the pandemic ( Myers et al ., 2020 ), as well as later on ( Morin et al ., 2021 ).

First, while there were several studies that found adverse impacts of the pandemic on mental health of scientists ( Chan et al ., 2020 ), there were very few that were able to link them to other stressors. For example, Doyle et al . (2021) found that physician scientists in the US reported distress on account of increased clinical demands and research delays. Our work suggested that mental health was substantially improved when universities provided support, or scientists had strong social support systems (in the form of relatives, friends, or family), and was also associated with fewer disruptions in research work.

Our finding on the importance of social support, particularly for female ECRs was echoed in work by the National Academy of Sciences ( The impact of COVID-19 on the Careers of Women in Academic Science, Engineering, and Medicine, 2021 ), which indicated that any social isolation that women face in this regard could damage their well-being and productivity.

Kelly (2021) found a reduction in the time that female scientists were able to devote to research, which mirrored some of the qualitative research findings from our work. However, this meant that they were less ‘visible,’ and therefore less likely to be quoted as experts in the media ( Jones, 2020 ). Similarly, lack of access to campus facilities was also cited among a large share of scientists in Johnson et al . (2021) -- a finding that aligned with the views expressed by heads of institutes / universities as well as other ECRs through interviews.

Gao et al . (2021) found that a large number of scientists reported pivoting to COVID-19 research during the pandemic, and our stakeholder interviews confirmed that funders made changes to their strategies to focus on COVID-19. Although quantitative evidence from our study did not suggest that personal or household financial stability played a significant role in mental health concerns or scientific productivity in the sample, research from Australia ( McGaughey et al ., 2022 ) and Ireland ( Shankar et al ., 2021 ) found that increased career uncertainty and concomitant financial insecurity contributed to greater stress.

Following sections will describe the results in detail based on the proposed research questions.

Impact on one’s ability to continue research during COVID-19

Specifically, for the individuals who had received a doctorate or a postdoctoral degree, it was observed that those having poor mental health were faced with an increase in core research issues (like methodological challenges, difficulty in data collection and dissemination, staff leaving campus, and difficulty working on campus). Further, greater difficulty in receiving a grant/fellowship led to an increased disruption of procuring lab supplies (slow or compromised supply chains and associated higher costs), and higher digital literacy led to an increase in the number of working hours for professional development (skill development, online courses/webinars, workshops, etc.). Scientists were unable to procure basic lab supplies such as gloves, plastic tips for pipettes, and centrifuge tubes, slowing down or halting research projects ( Woolston, 2021 ). Among life science trainees based in wet labs it was found that they made use of e-learning software during the lockdown to expand their skills (like, learning a new programming language; Korbel & Stegle, 2020 ).

In terms of gender, it was observed that for both men and women, poor mental health led to an increase in core research issues. While both genders faced a greater difficulty in receiving a grant or fellowship, it led to a disruption in obtaining lab supplies among men whereas it affected mental health for women.

Taking into account the qualitative responses to the survey questions, it supported the quantitative results suggesting that issues related to money and funding along with health, lack of access to lab, no access to software/hardware, lack of technical support, and absence of research participants were the major methodological challenges faced by the researchers. Further, in terms of professional development individuals mentioned attending conferences and enrolling for courses.

For individuals who did not have a doctoral degree, the results showed that a greater difficulty in receiving a grant and a greater financial insecurity in the household led to an increase in core research issues. However, participants having a PhD were not affected by difficulties related to financial security. Along with that, a greater difficulty in receiving a grant also gave rise to a higher disruption in procuring lab supplies. A similar trend of difficulty receiving a grant leading to disruption in supplies was observed among participants having a PhD degree. Among men, it was found that household financial instability increased core research issues while for women, difficulty receiving a grant significantly predicted a greater disruption in lab supplies. For individuals belonging to the dominant caste, it was noted that greater household financial insecurity led to more core research issues and greater difficulty in receiving a grant resulted in a higher disruption in lab supplies. It was found that Hispanic and Black undergraduates were more likely than Asians and Whites to delay graduation due to restriction of access to resources and delay in projects (Report 1; Saw et al ., 2020a ). A study noted that PhD students in Brazil belonging to a minority ethnic group were more likely to be financially disadvantaged as compared to white students ( Woolston, 2020b ).

Impact on one’s ability to continue to teach during the COVID-19 pandemic

For those who supervised PhD students, a greater disruption in lab supplies led to a greater impact on their supervisory role. This in turn had an impact on one’s teaching ability. Women (not significant for men) faced a disruption in procuring lab supplies, which affected their supervisory role and faced more difficulty in migrating to online teaching due to lower mental health. This suggested a significant impact of the pandemic on teaching duties of women as compared to men. This is in line with findings from surveys of STEM researchers in Australia. They reported increased challenges in student supervision due to the lack of face-to-face communications, and those with teaching responsibilities had increased teaching workload due to online teaching thus, limiting their research capacity ( EMCR Forum, 2020 ).

In terms of dominant caste groups, it was observed that being able to manage switching to remote working, better stability in internet connection to work remotely, and lesser disruption in lab supplies had a lower impact on one’s supervisory role. A greater stability in internet connection to work remotely and a better mental health led to a lower difficulty in migrating to online teaching. Due to an unequal sample distribution, any comparison between dominant and underprivileged groups might be difficult to interpret. Additionally, the qualitative results reported a decrease in interaction, money, health, and methodological challenges as the issues having a negative impact on one’s teaching.

Impact on researcher’s scientific productivity

Susceptibility to greater core research issues (such as difficulty in data collection, dissemination, methodological challenges) led to an adverse change in one’s scientific productivity. An earlier study had shown that many doctoral students and ECRs from the UK were experiencing a negative impact of the lockdown restrictions on their ability to collect data, discuss ideas and findings with colleagues, and disseminate their research findings ( Byrom, 2020 ). Further, the pandemic had a significant impact on the productivity of early and mid-career researchers in STEM fields in Australia ( EMCR Forum, 2020 ).

While men’s scientific productivity was affected by external reasons such as, greater research dependency on interactions with human participants and more core research issues (difficulty in data collection, dissemination, methodological challenges), women’s productivity was affected due to personal financial instability and low mental health during the pandemic.

For dominant caste groups, a higher dependency of working in a physical lab for their research, was one of the reasons leading to an adverse change in scientific productivity. Due to an unequal sample distribution, any comparison between dominant and underprivileged groups was difficult to interpret.

Evidence from interviews with ECRs echoed some of these findings. Some of the issues that affected researchers' scientific productivity were uncertainty, loss of time due to COVID-19, decline in scientific output, lack of access to lab, money, mental stress, and change in research field.

Among the graduate and postgraduate students, adverse changes in scientific productivity were based on higher core research issues (like, difficulty in data collection, dissemination, methodological challenges). Similar trends were also reported among the post-PhD group of participants. While for men greater core research issues led to an adverse change in scientific productivity, for women a greater difficulty in receiving a grant led to an adverse change in productivity. Additionally, lower disruption in lab supplies resulted in a greater change in scientific productivity among women. A study noted that STEM female faculty and students reported facing more problems adapting to remote learning and technological issues as compared to their male colleagues and peers (Report 2; Saw et al ., 2020b ).

Impact on mental health among STEM scientists

Finally, less difficulty in receiving grants, lower change in scientific productivity, more university and social support led to better mental health among STEM researchers. Specifically, an adverse change in scientific productivity led to lower mental health among researchers which is in line with the findings of an Australian national survey that found the pandemic had a significant impact on mental health and productivity of STEM scientists ( EMCR Forum, 2020 ). In a study conducted by Ogilvie et al . (2020) graduate students mentioned that they received more support from their advisors, professors, and peers in terms of physical and mental well-being ( Ogilvie et al ., 2020 ). On the other hand, it was found that researchers having lesser social support networks within and beyond academia tended to struggle with their mental well-being ( Byrom, 2020 ).

For men, receiving greater university and social support predicted better mental health. For women, difficulty in receiving a grant or fellowship and adverse change in their scientific productivity predicted lower mental health while, receiving higher social support from family, relatives, and peers led to better mental health. These differences bring into light the differential needs and challenges between men and women.

It was also noted that dominant caste groups which received greater social support showed better mental health. Due to an unequal sample distribution, any comparison between dominant and underprivileged groups was difficult to interpret. In terms of the qualitative responses, researchers noted that family and household responsibilities, fear of losing their job, money, health of self and family, and fear of COVID-19 some of the reasons leading to increased stress during the pandemic.

The good mental health of a STEM researcher was a result of greater support received from the university. However, among researchers with a PhD/post-doctoral degree, apart from the importance of university support, difficulty in receiving grants, social support, and change in productivity also affected their mental health. Furthermore, it was noted that a stable internet connection to work remotely and greater support from the university predicted better mental health among men. It was also observed that access to an independent workspace to work from home and greater support received from the university significantly led to better mental health for the dominant caste groups. An ethnographic study had noted that Brahmins and other upper castes dominate in science, medicine, engineering, and academic professions and culturally shape institutions based on their caste identities in India ( Thomas, 2020 ).

Reasons for leaving academia and thinking about leaving academia

The section concerning researchers who had left academia and were thinking about leaving academia had a low sample size due to which quantitative inquiry did not lead to any reliable and conclusive results (RQs 5 and 6). Hence, content analysis was conducted on the descriptive responses provided by survey participants for these sections and supplemented by qualitative evidence from interviews with a subsample of ECRs.

Many participants reported issues with money and funding, increased work pressure and workload that were some of the major reasons for leaving academia. Further, a few participants also reported bad work culture, bias towards women, lack of opportunities, loss of job, and child care responsibilities as other reasons for not continuing to work in academia.

Researchers who were thinking about leaving academia mentioned lack of funding, poor work culture, delay in receiving salary, lack of support, high work pressure and workload, job insecurity, and bureaucratic issues as major reasons for the same.

In line with the survey responses, in-depth interviews conducted with ECRs planning to leave or had left academia highlighted similar reasons (RQs 8 and 9). They reported being unable to perform and complete desired work due to the pandemic along with funding difficulties and delays in receiving salary. Further, it was also noted that the issues of teaching online, increased workload, and lack of opportunities and stability were some additional motivators and reasons for leaving and thinking about leaving academia.

Differential impact of the pandemic among ECRs, Heads of Institutes, suppliers and funders

The survey respondents mentioned ECRs and doctoral students as the ones experiencing the most setbacks in terms of mental, scientific difficulties due to the pandemic. From interviews with HoIs, it was evident that the pandemic impacted scientists in different ways. Lack of access to their research material and laboratories delayed research for some; however, a few scientists were able to return to their labs with precautionary measures. For the HoIs, managing personnel remotely and also on campus once restrictions were lifted were the main challenges of the pandemic. Scenario planning due to the uncertainty of the pandemic was the main challenge and HoIs had to take on new roles to manage this. Managing administrative, supervisory, teaching, research and personnel management tasks were impacted due to the virtual mode of work and the time allotted for each also changed for the HoIs. Ensuring that extensions of grants, additional sources of funding, current funding timelines, and disbursement of salaries was managed during the pandemic was one of the key roles of the HoIs. Mental health of their staff and scientists within the institute and their own mental health was a challenge during the pandemic, even though a few institutes did have counselling support. Virtual coordination of software, hardware, and other research-based support for the scientists was one of the key roles taken up by the HoIs during the pandemic.

For the funding agencies interviewed, they mentioned that current research by the organisations they supported was paused and COVID-19 related research took priority. The organisations supported by the funders were unable to utilise the funds set aside for field work/lab-based work due to lockdown restrictions, but other forms of virtual research still took place. Funders mentioned that committees and boards had to be consulted on the new challenges for funding timelines as presented by the changing nature of the pandemic. The funders interviewed funded organisations, institutes, and individual scientists and the research goals linked to the funding were adapted according to the pandemic. In terms of deadline extensions, funders provided cost and no-cost extensions while also easing the timelines for deliverables required during the funding period. Funding agencies also supported virtual means of research dissemination including workshops, webinars, conferences, and research podcasts with their scientists. This also included virtual meetings with the organisations they supported and regular newsletters on research findings. A suggestion that was highlighted during the interview, was that organisations and institutes across the research spectrum must have a succession plan and a scenario plan in place to ensure minimum disruptions within the organisation's structure due to unforeseeable events in future.

The suppliers of scientific equipment reported a delay in supply of material and equipment owing to lockdown related restrictions on travel within the country and across national borders. Government mandates on manufacturing and supply of material that favour domestic production, especially during the pandemic, impacted suppliers negatively due to added levels of permissions and bureaucratic procedures. Payments for the transportation and delivery of scientific material and equipment were delayed since research institutes were shut due to the lockdown. There were no changes in the type of primary market or target group during the pandemic, and the suppliers moved to virtual means of business through their website and online portals for transactions. However, not everything could be smoothly managed via a virtual medium since equipment needs to be sampled by the scientists or a physical demonstration needs to be completed before an equipment is purchased.

Policy recommendations that arise from various challenges faced by scientists during the pandemic

We asked participants for their suggestions and base the following policy recommendations on these:

1. Grant management and other administrative duties should be minimised for scientists as it takes away from their research time.

2. Flexible working hours must be adopted by the institute for the researchers to work independently especially during a pandemic when remote working arrangements are the norm.

3. Funding opportunities must be made widely available for the smaller research institutes in the country, and that funding must be disbursed on time from funding agencies.

4. Institutions must have a better environment for growth opportunities, which takes into account researchers’ mental health, work-life balance, and provides holistic support to the researchers, which has gained importance during the pandemic.

5. Institutions must increase job opportunities and prioritise giving learning opportunities to graduates since online education has unfavourably impacted certain courses and skill learning.

6. For women researchers, there should be support in providing day-care, affordable childcare, transport, flexible working hours taking into account the gendered division of labour in the house. Women researchers with children or those who have older people at home have also expressed the need to have flexible working hours as it gets harder to have a work-life balance.

7. The administration should be acquainted with the process of scientific research and there is a need for upskilling in the tech domain to ensure smoother communication and efficient processing of paperwork digitally. An increase in efficiency, especially in the tech domain, of the administration is needed for quick decision-making and to figure out plans in case of changes in the mode of education.

8. In order to ensure networking and interaction between researchers, there should be more online workshops, conferences, mentorship opportunities and advancement of training to connect with peers.

9. Institutions should extend funding, submission, grant deadlines taking into account lack of access to labs, delay in procuring equipment and reduce the pressure for researchers to keep publishing.

10. Institutes should make efforts to maintain a contingency/reserve fund to deal with similar events in future.

Implications

Along with providing a detailed understanding on the various challenges faced by researchers in the STEM community, the current study also illuminates the needs of these researchers (such as importance of social and university support) in order to increase their scientific productivity and improve mental health during the pandemic. Noting the impact of the pandemic on mental health of researchers, an important inference from the study is normalising talking about mental health and providing necessary resources to academic personnel to improve their mental health and build coping resources.

The study has many policy implications, such as the need for training and development of STEM scientists in the area of technological skills and digital literacy to provide opportunities for upskilling researchers/professors and being able to transition to hybrid/online working. Furthermore, a necessity to develop standard operating procedures (SOPs) across domains of teaching and research to alleviate losses in the future. Noting the impact of the pandemic on mental health of researchers, an important inference from the study is normalising talking about mental health and providing necessary resources to academic personnel to improve mental hygiene. Finally, setting up reserve funds to provide funding opportunities to researchers in the case of any such future contingency.

Additionally, this research provides the groundwork for addressing the impact of the pandemic on more understudied groups in India such as women and other genders and individuals belonging to the underprivileged caste. Even though many studies have been conducted in countries such as the USA and UK to understand the impact of the pandemic on researchers, especially women and different racial groups, not many studies have highlighted this difference in an Indian context. Finally, this study also gives an idea of how the pandemic affected STEM researchers not only from the perspective of ECRs but also, from a frame of reference of other stakeholders like the funding agencies, suppliers of lab equipment, heads of institutes, and other stakeholders.

Some of the survey participants provided some recommendations to improve researchers' experience in academia and also increase scientific productivity. A reduction in grant management and administrative duties of researchers, availability of funding opportunities, flexibility in working hours, providing additional means of support, and growth opportunities were a few suggestions made by the participants. Additionally, increase in job opportunities and training along with extending submission deadlines and increasing networking among researchers was also reported. Lastly, providing support especially, for women in terms of childcare and transport were highlighted.

Limitations

Although the current research provides valuable insights into the needs and challenges faced by STEM researchers in India, there are a few limitations of the study. First, the total sample size was small, suggesting that the results cannot be generalised to all the STEM scientists in India.

Secondly, due to the pandemic only digital tools were used to disseminate the survey, making it available to only a select group of individuals having access to a device, internet connection, and possibly belonging to an urban area. Finally, the study lacked equal representation of different caste groups and research disciplines due to which it was difficult to make a comparison between each group regarding the impact of the pandemic. In particular, the study was unable to comment on scientists or ECRs from underprivileged caste groups, who may have faced differing challenges relative to dominant caste group scientists.

Future directions

Subsequent studies can include a larger sample so that generalizable results are obtained. Additionally, a more representative sample comprising equal participants from different genders, castes, religions, and discipline groups should be made so that comparisons between these can be made. Further, a more inclusive data collection method for the underprivileged groups can be employed in order to have a more representative sample take part in the study.

In an attempt to evaluate the challenges faced by STEM researchers in India during the pandemic, disruptions in terms of continuing research, impact on scientific productivity, and declining mental health were reported. Quantitative results indicated that ECRs who were susceptible to research issues like difficulties with data collection and dissemination, and methodological challenges had a large impact on their scientific productivity. Furthermore, difficulty in receiving funding led to an increased disruption of procuring lab supplies. It was also noted that better mental health among ECRs was based on less difficulty in receiving grants, lower change in scientific productivity, and more university and social support. Qualitative findings pointed towards issues with funding and increased work pressure as major reasons for leaving academia. Additionally, interviews with diverse stakeholders suggested a disparate effect of the pandemic on institute heads, suppliers, and funders.

Data availability

Underlying data.

Open Science Framework: Assessing the Impact of COVID-19 on STEM (Science, Technology, Engineering, Mathematics) Researchers in India. https://doi.org/10.17605/OSF.IO/MVXDB ( Mehta et al ., 2022 ).

This project contains the following underlying data:

- IA_abovephd-analysis.csv

- IA_belowphd-analysis.csv

- Interview transcripts.zip

Extended data

This project contains the following extended data:

- India_Alliance_-_Survey_-_English.docx

- India_Alliance_Questionnaires.docx (the semi-structured interview schedule)

- Qualitative analysis_interviews.docx (analysed qualitative responses from the participants)

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Acknowledgments

We thank Nicolette Jadhav for her invaluable contribution and feedback in terms of development of the survey questionnaire, methodology, analysis, and review of text. We thank K. VijayRaghavan, Vasan Sambandamurthy, Smita Jain, Sarah Hyder Iqbal and TheLifeofScience.com/Labhopping for their support, advice and encouragement throughout this study.

1 The survey was piloted with 10 STEM researchers who had signed up/expressed interest in participating.

2 It has been noted that the different goodness-of-fit (GOF) indices (like CFI, RMSEA, SRMR) are highly susceptible to extraneous data and the analysis characteristics like number of indicators, number of response options, and sample size, to name a few ( Groskurth et al. , 2021 ). Thus, the model indices should be interpreted with caution.

3 Internal consistency reliability was assessed using cronbach’s alpha ( α ). Scales with α values ranging from 0.70 - 0.95 are considered as having good reliability ( Nunnally, 1978 ).

4 A regression analysis was computed to understand whether scientists’ ability to continue teaching and research, their productivity, and mental health were predicted by variables like disruption in supplies, digital literacy, and grant disruptions, to name a few.

5 The output for the regression analysis contains the beta coefficient ( β ), z-value (z), and p-level (p, indicating the level of significance for the relationship) for each model.

Table 1. Descriptive statistics of participants with a PhD/post-doctoral degree.

Note. *12= Not applicable to me, **12= I’m not sure. SD = Standard deviation

Table 2. Frequency distribution of participants with a PhD/post-doctoral degree.

Table 7. descriptive statistics of participants with a graduate/postgraduate degree..

Note. *12= Not applicable to me, **12= I’m not sure. SD = Standard Deviation

Table 8. Frequency distribution of participants with a graduate/postgraduate degree.

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Comments on this article Comments (0)

Open peer review.

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Difficulties of early career researchers in STEMM in Australia

• Respond or Comment
• COMMENT ON THIS REPORT

Is the work clearly and accurately presented and does it cite the current literature?

Is the study design appropriate and is the work technically sound?

Are sufficient details of methods and analysis provided to allow replication by others?

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Are the conclusions drawn adequately supported by the results?

• The article by Mehta et al. aims to evaluate impact of Covid-19
• The article by Mehta et al. aims to evaluate impact of Covid-19 on not only STEM researchers, but also additional stake holders in India. Inclusion of stakeholders other than researchers adds value to this work. While researchers from early career stage to older ones, heads of institutions are the expected inclusions; funders, equipment suppliers are also included to provide a more rounded picture of the impact. In addition to equipment supply, researchers were also hampered by extensive delays in the supply of laboratory chemicals and reagents. It is not clear whether they were included or not.
• In the introduction, the authors have provided an extensive background for their research. There have been many manuscripts/papers published reviewing impact of Covid-19 on researchers at all stages of their career from early pandemic days onwards. Work from India is very limited and that in itself is good enough justification for a systematic effort to understand the situation, highlight difficulties and suggest possible solutions. Solutions of long-term nature to avoid repetition of the crisis are the most valuable ones for any country. However, such a clear set of recommendations for the future are not coming forth.
• Two points of criticism here. 'Suppressed class' may not be the best phrase to use for individuals from under privileged categories. Two, while 'social distancing' was a common term used during Covid-19 pandemic worldwide, in specific Indian context this phrase has a distinct contextual meaning - a behaviour which involves treating people as outcastes or 'untouchables'; and hence 'physical distancing' would have been a better way to express the practice followed during this period.
• Text on methodological details is repetitive and some editing would have made it more concise and better to read.
• There is a mention of compensation provided to each participant. It is assumed it was Rs. 100/- per person. But at one place it is mentioned as Rs. 1000/-.
• Questionnaire was meant for early career researchers, however, at least one researcher aged 64 years participated in the survey (Appendix, Table 1, data on age). This suggests there was possibly no clear, strict definition of 'early career'.
• There is no mention whether the questionnaire was pre-tested. While seasoned researchers do it as a matter of course, a statement to the effect was desirable.
• So called 'suppressed class' individuals are underrepresented. However, in non-PhD category of respondents their number is 56. It would have been worthwhile to provide qualitative information about their specific problems if they were there. The authors have given a lot of emphasis on doing quantitative analysis of the data collected from the questionnaire, by developing specific algorithms but this survey encompasses socio-culturally different participants as well and hence it feels that an opportunity to evaluate comparative qualitative experiences of underprivileged participants is missed in the effort.
• More specifically, in addition to the earlier comment on the underprivileged respondents, the results section includes minimum details of the personal interviews in the main text. Only passing statements are mentioned. Instead of checking the details in the supplementary information (extended information) it would have been better to get a sense of findings in the main text. Importance of personal interviews to the whole picture is diminished because of this near-absence of information in the main text.
• Analysis of data from questionnaires is presented as many figures and tables. While providing details is important some details occupy a lot more space than they deserve. For example Figure 3 describing 'sentiment analysis'. Firstly it is unclear what it conveys in each panel. Secondly, the axes are unreadable while the bars occupy huge space in each panel. Thirdly, how meaningful is this level of quantification?
• Based on quantitative data statistical analysis is done, however, clear trends, impressions and take home messages from the data are possibly getting lost. They are not clearly described in the text. Hence those who cannot clearly read the tables and interpret the data as presented are unlikely to get anything much out of the extensive work done by the authors.
• A ‘Conclusion’ section has been added to the manuscript highlighting some of the main findings of the study.
• Furthermore, edits have been made to include the reasons and use of conducting the statistical tests in the ‘Data analysis’ subsection.
• Additionally, the ‘Result’ section already included an explanation of the direction of the relationship between variables of interest.
• Finally, the ‘Discussion’ section of the manuscript is divided into subsections based on the research questions proposed by the study. Each subsection thus, reiterates all the findings along with a brief explanation.  
• Statistical analysis, for example, has thrown up some differences between men and women researchers. Is there a social significance of these findings? Is that going to help in policy related decisions? While authors are not expected to be the advisors on public health policy, if there were clear meaningfully different impact of Covid-19 on men versus women it should have been made apparent. Even after reading the whole text one is left searching for clear observations.
• In discussion, policy recommendations arising out of the comments of the respondents are mentioned. Apart from a significant impact on the researchers' mental health during Covid-19 due to extreme uncertainty and stress, no major new point emerges.
• In conclusion, the work done is sound in terms of planning and execution including data collection from early career researchers. Data analysis is mired with the use of complex statistical methods making it a manuscript for statisticians than other researchers. Personal interviews and comments from heads of the institutions and others would have been very useful to include in the main text, and shift many tables and re-analysis of primary data as extended data. Regardless of these limitations it is clear that early career researchers, especially those without a permanent job in hand, are affected much more than those with a permanent job in hand. Men and women both are affected badly, possibly somewhat on different fronts; but mental health issues are very significant and may have lasting impact on the researchers. Funding delays, delays in equipment procurement (and reagents and chemicals procurement) were critical in paralysing working conditions. Having data on Indian situation during Covid-19 pandemic should provide the basis for prevention of future disruptions of this kind.
• This paper has been prepared thoughtfully and is well written. The literature review is thorough and up to
• This paper has been prepared thoughtfully and is well written. The literature review is thorough and up to date and has brought several papers of which I was unaware to my attention. Given the funding body and the platform for publication I am surprised at the omission of the Wellcome Trust report "What researchers think about the culture they work in".
• The research appears to have been carried out in a suitable manner. I note the questionnaire is very long which will not have helped the response rate. I would like to see the base questions for the interview - or to know they exist.
• While I have no issues about the research funding, my main concern is that the authors do not point out, or perhaps even realise as it is not mentioned at all, that their areas of concern are always present in the STEM environment; they have been exacerbated by the COVID pandemic, not caused by the pandemic. Stress, lack of funding, intention to leave and lack of work life balance are endemic for researchers in STEM, and particularly for early career researchers.
• Following this, it is not realistic for most academic researchers to expect they will continue in a research career (although they do expect to). There are not enough jobs - or enough funding. The fact they were forced to seek alternate career opportunities during COVID was probably a benefit for them.
• It would be interesting to see the views of PhD students and early career researchers compared with the more senior researchers.
• It would also be interesting to know whether there is empathy for the difficulties of the researchers from the HoIs or funding bodies.

Reviewer Status

Alongside their report, reviewers assign a status to the article:

Reviewer Reports

• Katherine Christian , Queensland University of Technology, Brisbane, Australia
• Vineeta Bal , IISER Pune: Indian Institute of Science Education Research Pune, Pune, India

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STEM undergraduates' perspectives of instructor and university responses to the COVID-19 pandemic in Spring 2020

Affiliations.

• 1 Department of Allied Health Sciences, University of Connecticut, Storrs, Connecticut, United States of America.
• 2 Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
• 3 Department of Women's, Gender, and Sexuality Studies, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
• 4 Department of Mathematics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
• PMID: 34449780
• PMCID: PMC8396789
• DOI: 10.1371/journal.pone.0256213

Objectives: We examined undergraduate STEM students' experiences during Spring 2020 when universities switched to remote instruction due to the COVID-19 pandemic. Specifically, we sought to understand actions by universities and instructors that students found effective or ineffective, as well as instructor behaviors that conveyed a sense of caring or not caring about their students' success.

Methods: In July 2020 we conducted 16 focus groups with STEM undergraduate students enrolled in US colleges and universities (N = 59). Focus groups were stratified by gender, race/ethnicity, and socioeconomic status. Content analyses were performed using a data-driven inductive approach.

Results: Participants (N = 59; 51% female) were racially/ethnically diverse (76% race/ethnicity other than non-Hispanic white) and from 32 colleges and universities. The most common effective instructor strategies mentioned included hybrid instruction (35%) and use of multiple tools for learning and student engagement (27%). The most common ineffective strategies mentioned were increasing the course workload or difficulty level (18%) and use of pre-recorded lectures (15%). The most common behaviors cited as making students feel the instructor cared about their success were exhibiting leniency and/or flexibility regarding course policies or assessments (29%) and being responsive and accessible to students (25%). The most common behaviors cited as conveying the instructors did not care included poor communication skills (28%) and increasing the difficulty of the course (15%). University actions students found helpful included flexible policies (41%) and moving key services online (e.g., tutoring, counseling; 24%). Students felt universities should have created policies for faculty and departments to increase consistency (26%) and ensured communication strategies were honest, prompt, and transparent (23%).

Conclusions: To be prepared for future emergencies, universities should devise evidence-based policies for remote operations and all instructors should be trained in best practices for remote instruction. Research is needed to identify and ameliorate negative impacts of the pandemic on STEM education.

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VIEW LARGER COVER

Undergraduate Research Experiences for STEM Students

Successes, challenges, and opportunities.

Undergraduate research has a rich history, and many practicing researchers point to undergraduate research experiences (UREs) as crucial to their own career success. There are many ongoing efforts to improve undergraduate science, technology, engineering, and mathematics (STEM) education that focus on increasing the active engagement of students and decreasing traditional lecture-based teaching, and UREs have been proposed as a solution to these efforts and may be a key strategy for broadening participation in STEM. In light of the proposals questions have been asked about what is known about student participation in UREs, best practices in UREs design, and evidence of beneficial outcomes from UREs.

Undergraduate Research Experiences for STEM Students provides a comprehensive overview of and insights about the current and rapidly evolving types of UREs, in an effort to improve understanding of the complexity of UREs in terms of their content, their surrounding context, the diversity of the student participants, and the opportunities for learning provided by a research experience. This study analyzes UREs by considering them as part of a learning system that is shaped by forces related to national policy, institutional leadership, and departmental culture, as well as by the interactions among faculty, other mentors, and students. The report provides a set of questions to be considered by those implementing UREs as well as an agenda for future research that can help answer questions about how UREs work and which aspects of the experiences are most powerful.

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Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2017. Undergraduate Research Experiences for STEM Students: Successes, Challenges, and Opportunities . Washington, DC: The National Academies Press. https://doi.org/10.17226/24622. Import this citation to: Bibtex EndNote Reference Manager

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How the Pandemic Is Changing STEM Education

How in-person does science have to be.

By Madeleine Gregory

September 28, 2020

Photo by  zubada /iStock

This year’s back-to-school is unlike any other. Parents, teachers, and students are weighing safety against the desire to be in the classroom . Campuses that are usually buzzing with students are nearly empty. Dorms are sites of isolation rather than community, places where students are stuck before the glare of a laptop. Even colleges that have opted to have in-person classes need to prepare to pivot online in case of a COVID-19 outbreak.

But one type of class is particularly difficult to move online: lab classes. 

Many courses in the STEM fields—science, technology, engineering, and mathematics—include lab or field classes as practical components to an otherwise theoretical course. Professors are now tasked with converting this experiential learning—which relies on the student’s ability to touch and see and feel the lesson—to a flat, remote interface. 

Students need to leave university with a specific set of skills and expertise that matches the degree they hold, and COVID-19 threatens to change the meaning of a STEM degree. Can a student graduate in biology having never learned to perform fundamental procedures like the polymerase chain reaction? Can they graduate in forestry if they’ve never done fieldwork in an actual forest? 

We’re about to find out. According to The Chronicle of Higher Education , 10 percent of colleges planned to begin the semester fully online at the start of the school year, about 4 percent were holding classes fully in person, and 78 percent were doing a hybrid of online and in-person education (the remaining 8 percent were still deciding). Here are a few ways these different strategies are affecting STEM in higher education. 

Any in-person instruction is controversial.

Even if students are allowed to go into labs, not all students want to risk being there in person. At some colleges, faculty, graduate students, and kitchen and custodial staff don’t have the option of working online—if they want to keep their jobs, they have to return to campus. Many faculty, students, and staff are also struggling with childcare. 

At Arizona State University, labs that can’t easily be moved online are happening in person. ASU required a negative test result before students were allowed to return to dorms, and developed an FDA-approved rapid saliva-based COVID-19 test, provided free to students. 

The school says that it is regularly testing a “statistically significant” percentage of the students, hoping to keep tabs on the presence of the virus. Still, the reopening has already received pushback from some faculty and staff, who published an open letter to school administration on Medium , saying that ASU’s policies were endangering school staff and that outbreaks on campus could easily spread to the larger community and vice versa, since many students live off-campus with family and commute into school. 

Several students have been suspended for violating  the school’s COVID guidelines : "Everyone—including faculty, staff, students, and visitors—is required to wear face coverings in classrooms, labs, offices, and all ASU outdoor spaces (except while eating). Students and employees are required to do a daily health check through the ASU mobile app or healthcheck.asu.edu, which involves monitoring their temperature and answering questions about any symptoms." Students can’t bring visitors into the dorms or go to parties off-campus that don’t follow public health guidelines. Since August 1, however, 1,330 cases have been recorded at ASU.  

What does “equal opportunity” mean when everything’s online? 

Now that computer labs are closed and many students are attending remotely, schools now also need to make sure that all students have access to a computer and the internet. 

“The pandemic has brought out a lot of inequities,” says Lynn Huntsinger, the associate dean of instruction and student affairs at UC Berkeley’s Rausser College of Natural Resources. “Among them, do you have a good place to work at home, and do you have good internet?”

Many colleges are expanding laptop loaning programs and adding wi-fi hotspots if internet connectivity is a problem. Some lab classes require specialized (and expensive) software, like ArcGIS or AdobeSuite or R. These can require higher computing power than most entry-level laptops have, so some schools are working to allow students to log in to on-campus computers remotely, allowing them to use the greater processing power to complete their assignments. 

All that puts an added financial strain on already-strapped college budgets and requires new levels of technical troubleshooting for students and faculty.

Your lab’s in the mail.

Certain lab classes—like chemistry—require a lot of expensive technical and safety equipment. Those are the ones that, if possible, are taking place on campus. When the classes are moved online, students have to watch their teachers perform chemistry reactions on video, rather than performing them themselves. 

For labs in which the materials are less hazardous, professors work with students to create their own labs at home. At UC Berkeley, Lynn Huntsinger—who teaches ecology in addition to her role as a dean—is sending her students a lab kit with specimens, seeds, jars, and all the equipment they need for a soil lab. Instead of students planting in the campus greenhouse, she’s having them replicate the experiment at home. 

At UMass Amherst, ecology professor Kristina Stinson usually spends the lab sessions for her plant-identification class wandering the tree-filled campus, with students stopping to see, touch, smell, and discuss the trademarks of each species that they’re studying. 

Now, her four-hour lab classes feature a one-hour lecture, then a two-hour break during which students leave and then return for the final hour with videos of local specimens to share. Even if people are in different locations, Stinson said, they should be able to identify similar species. Her students—whether in California or another country—are still expected to be able to successfully identify New England plant life. 

She’s relying a lot more heavily on visual aids than she normally does in this course, showing pictures of species in different seasons and sizes. “It’s important to recognize the faculty who are putting in all these extra hours and care to make sure students get what they need,” Stinson said. “We’re talking around the country about how we’re doing this.”

A good lab job is hard to find.

For many STEM students, working as assistants in research labs is critical for learning what it’s like to work in a particular field. Undergraduate research experience can also be critical to getting into a graduate program or medical school. 

Some labs are still in operation on campus, with new safety protocols. But getting your foot in the door at a research lab is trickier when you’re at home on your laptop, instead of chatting with your professor or a grad student after class. 

Some labs have shifted their research toward more online-friendly topics like data analysis. That might not be such a bad thing, says Elizabeth Crook, a professor of Earth System Science at UC Irvine. Crook has already seen more interest in her GIS classes and research, which translates better to an online format than traditional lab or field classes do, and presents more job opportunities to students. As long as the university is providing the same amount of mentorship opportunities through internships or research programs, she says, students can learn as much studying remotely as they would have in person.

Some schools are creating their own opportunities. Jennifer Vanos, a professor of sustainability who researches urban climate at Arizona State University, said that in the School of Sustainability, upperclassmen need to complete an internship to graduate. Many companies aren’t hiring, so her lab created a research internship in an attempt to fill that gap. Other labs are minimizing crowding by refraining from taking on new students. At UMass Lowell, students can only work in a lab as an undergraduate if they already did before the pandemic and have expertise that’s relevant to the project. 

The pandemic has made research a lot harder, says Vanos. Many projects slowed or stalled last spring, and professors have spent the summer scrambling to move their classes online. Vanos’s field research studying extreme heat has continued, but her research involving human subjects is cancelled. Equipment isn’t as easy to come by—the sensors that she ordered didn’t arrive for four months because of supply chain disruptions in China. 

Also, says Vanos, because many researchers spent the spring and summer concentrating on working through data and writing up research papers instead of doing labwork, that’s led to a glut of papers ready for review. As a reviewer herself, Vanos said she’s getting way more requests than normal, and she has to say no a lot. Female reviewers are especially hard to find, she says. She and her colleagues suspect it's because many women are taking the lead on childcare, and she’s worried about the long-term implications. “We need the female perspective on these reviews.” 

Online education has some upsides. Huntsinger is excited to have guest lectures from anywhere. At UMass Lowell, Juliette Rooney-Varga leads the World Climate simulation, having students play the part of countries, businesses, and other key players in climate policy. 

Since the pandemic forced her to adapt her climate simulations for web presentation, Rooney-Varga has made World Climate available for anyone to use . 

“A lot of people are viewing this as a temporary thing,” Rooney-Varga said. For her, the key has been to design programs that she’ll continue to use even after the pandemic is over. “With this online format, geography is less important than it ever has been,” Rooney-Varga said. “You can reach people anywhere at any time.”

Madeleine Gregory is a former editorial fellow at Sierra. 

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Students academic and social concerns during COVID-19 pandemic

Azzah al-maskari.

1 University of Technology and Applied Colleges- Ibra, Ibra, Oman

Thurayya Al-Riyami

Siraj k. kunjumuhammed.

2 Modern College of Business and Sciences, Muscat, Oman

Due to the COVID-19 pandemic, Higher Education Institutions (HEI) replaced regular face-to-face teaching with online teaching and learning. However, the shift caused several academic and social concerns for students, such as lack of academic support, lack of adequate resources to support online teaching, lack of socialization, stress, anxiety, and lack of motivation in attending classes. This research evaluates the impact of HEIs support, faculty support, and resources available on the academic and social concerns of students in HEIs during the pandemic. 11,114 students across the HEIs in Sultanate of Oman participated in an online national survey. Regression and factor analysis were used to verify the research model developed based on the literature review. Results showed that HEI support and faculty support significantly affect university students' academic and social concerns. Furthermore, resource availability was found to affect the academic concerns of students but not their social concerns. This research recommends strategies for HEIs and faculty to promote faculty-student interaction using both synchronous and asynchronous modes to reduce student concerns and motivate them to engage in online classes.

Introduction

COVID-19 pandemic influenced all walks of life; the higher education sector is not an exception. Since WHO declared COVID-19 as a pandemic in March 2020, lockdown, social distancing, work from home, and online classes became part of life. Distance education replaced regular face-to-face classes; higher education institutions (HEI) rely heavily on a distance learning model to continue offering their programs. HEI invested heavily in IT infrastructure, trained staff and students, and moved their different activities online, including teaching and assessment. The shift, however, caused several concerns for students and staff. A few recent research have explored the challenges encountered by students during the pandemic (e.g., Mailizar et al., 2020 ; Aristovnik et al., 2020 ; Al-Salman & Haider, 2021 ). However, all these studies suggested the need for further studies on students' responses towards online learning and their concerns (Basilaia & Kvavadze, 2020 ; Mailizar et al., 2020 ; Basilaia & Kvavadze, 2020 ).

Distance Education (DE) includes all study methods and all levels of education that do not enjoy direct and continuous supervision by teachers attending with their students in traditional classrooms. Still, the education process is subject to planning, organization, and directed by an educational institution and teachers" (Holmberg, 1977 , p.9). DL experiments with synchronous or asynchronous environments using different devices such as mobile phones, tablets, or laptops. Participants interact with their teachers and share their ideas with colleagues remotely. It offers many benefits, for instance, flexibility. Besides, the course contents are accessible to students anytime. DE is not costly as it saves the costs of establishing new classrooms and saves electricity, water, and others (Ferriman, 2013 ). However, a low level of motivation, feelings of isolation, and loneliness are some of the challenges affecting DE's effectiveness (Hetsevich, 2017 ).

In the Sultanate of Oman, the Supreme Committee decided to suspend face-to-face classes and shift to online education on March 15, 2020. Accordingly, HEIs shifted teaching and learning online, modified their assessment scheme, and initiated measures to enhance their investments in IT. It allowed HEIs to continue their academic programs and maintain the health of their stakeholders. However, the shift posed significant challenges as it was not well planned. The challenges include lack of infrastructure and resources, teacher's inexperience in the virtual teaching mode, resources available for students, network connectivity issues. Indeed, the student's academic concerns and social concerns due to pandemic created a unique situation that was never a subject matter in the empirical research.

Against this background, this paper investigates students' academic and social concerns in the HEIs in the Sultanate of Oman. Specifically, this paper examines the role of HEI support, faculty support, and resources on the academic and social concerns of the students.

Literature review

Academic concerns refer to learning difficulties, lack of attention from teachers, and increasing workload that have restricted students' ability to concentrate during online classes. Several authors around the world have researched students' academic concerns caused by COVID-19. For instance, Realyvásquez-Vargas et al. ( 2020 ) found that shifting to online learning affected students' academic performance and caused a lot of intellectual fatigue due to the increased workload. Also, the challenge includes a high risk of students dropping out of their courses (Cohen, 2017 ). The only way to overcome such a phenomenon is individualized monitoring, which is probably hard to be accomplished by all teachers (UNESCO, 2020 ). Besides, many students have not benefited from online learning since they have not received proper guidance from their teachers (Ali, 2020 ; Sullivan et al., 2018 ) and lose interest in attending classes online. Also, Al-Salman and Haider ( 2021 ) stated that the volume of assignments has negatively affected students' academic performance. In another study, Aristovnik et al. ( 2020 ) analyzed how students perceive the impact of the COVID-19 pandemic with a sample of 30,383 university students from 62 countries; their study revealed that students complained about the intensive workload that affected students' academic performance.

This paper defines social concerns as the outcome of student experiences, feelings of loneliness, fear of a pandemic, worries about health and the health of loved ones, and lack of communication with classmates and relatives. According to the UNESCO report ( 2020 ), the shift to a virtual mode of teaching–learning limited social contact and socialization routines, a central part of students' daily experience in HEIs. The report indicated that 75% of students in HEIs worldwide had experienced anxiety and unease due to the study suspension. In the same vein, Duraku and Hoxha ( 2020 ) found that a majority of students in HEIs reported moderate levels of stress (65.4%), while more than one-quarter of students reported high levels of stress (26.9%). Similarly, Almuraqab ( 2020 ), in his study in the UAE, found that more than half of respondents (58%) agreed that distance learning made group collaboration among students less and very limited, which affected the ability to learn and interact with their classmates. Gillis and Krull ( 2020 ) observed that students experienced barriers to learning due to the pandemic, including distractions, increased anxiety, and feeling less motivated. Further, Aristovnik et al. ( 2020 ) found that students experienced boredom, anxiety, and frustration due to the adoption of particular hygienic behaviors that prevented them from performing simple daily practices such as shaking hands and getting in touch with their family members and friends.

Factors that impact students' academic and social Concerns during online education

The success of online classes depends on many factors. Empirical research univocally highlighted the critical role of faculty in shaping students' experience in online classes. For instance, Adnan and Anwar ( 2020 ), based on a study among 126 undergraduates and postgraduate college students in different HEIs in Pakistan, found that students' academic performance is affected due to lack of face-to-face interaction with the instructors and delays in responding to students' inquiries. Bates and Khasawneh ( 2007 ) stated that frequent feedback from teachers improved students' academic performance and increased their motivation and engagement during online learning. Students learned more when their lecturers provided training on using the online learning system at the beginning of the course. In addition, Zhou et al. ( 2020 ) have found that most teachers in China are unfamiliar with synchronous and asynchronous online teaching tools and could not guide their students on using online platforms/or learning management systems. Hence, it is imperative that faculty knowledge, experience, and interaction during online classes significantly influence students' experiences in online classes.

Considering the challenges posed by the pandemic, Daniel ( 2020 ) observed that faculty should take advantage of asynchronous teaching to engage students and ease their concerns to juggle home and study demands. However, this is contrary to the expectation that faculty should continuously utilize synchronous platforms to engage in discussions and interactions with students. Drane et al. ( 2020 ) observed that students from more vulnerable backgrounds are likely to experience persistent disadvantage through a range of barriers, for instance, long-term educational disengagement, digital exclusion, poor technology management, and increased psychosocial challenge. These barriers can be significantly managed by the faculty while designing the online classes and mode of engagement.

Although teachers' moved to online classes based on HEIs directive, teachers at HEIs have not had enough time to adapt their course contents to online mode, both synchronous and asynchronous. Chaaban and Ellili-Cherif ( 2017 ) considered lack of time to look for appropriate online materials that cater to students' level and needs as one of the obstacles teachers encounter. It needs adequate time to find materials that meet the standardized curriculum and assessment implemented in most HEIs (Biancarosa & Griffiths, 2012 ; Vrasidas, 2015 ). Thus, due to the pandemic, teachers shared as many materials as possible and expected students to choose the best materials for themselves, which caused many challenges for students. Amita ( 2020 ) stated that learners encountered difficulties in choosing the best source amongst many sent by their teachers, which affected their academic performance and increased their anxiety and frustration.

It suggests that, given the urgency of continuing education online during the pandemic, faculty support is critical in addressing students' academic and social concerns. For instance, a faculty need to maintain effective interaction with their students, give them necessary feedback, and provide them with sufficient learning materials that have a meaningful impact on student's academic and social concerns during the pandemic. Therefore, the empirical discussion furthers the following hypothesis (H1):

• H1: Faculty support significantly affects students' academic and social concerns during online education.

HEI support also critically influences student experiences in online learning. Recent research established the role of HEI support in student's academic success and wellbeing in general (e.g., technical training and support, counseling support, financial support, communication support, etc.). In their study, Fernandez and Shaw ( 2020 ) emphasized the role of effective communication to gain the trust and commitment of faculty, staff, and students. Altamirano and Collazo ( 2020 ) cited an example wherein the leaders at Urban Diverse College communicated with staff by weekly emails that contain heartfelt motivational messages and information on developments concerning the community at large. In a national survey, Active Minds ( 2020 ) reported that many students expressed that a lack of regular and caring communication from their institutions was a primary stressor during COVID-19. Students expect communications from their HEIs, and checking if have accessibility issue or staying focused during online classes. Besides, HEIs should share meaningful and heartful messages with students. HEIs should also provide support services to facilitate student's success and wellbeing during online learning. Some students may lack the skills or have trouble using online platforms. Zeeshan et al. ( 2020 ) emphasized the importance of technical support from their university administration to motivate students to manage technological stresses and develop full readiness for online learning.

Sarker et al. ( 2019 ), in their study in a private university in Bangladesh, stated that to obtain optimum benefit from e-learning technologies, HEIs must ensure quality content distribution through user-friendly systems and enhanced asynchronous interaction between the lecturers and students. For instance, HEIs should provide training for both lecturers and students to cope with the new learning environment during the pandemic. HEIs were rated differently in their approach to academic support to faculty and students in the previous empirical literature. Abu Shekhadim et al. ( 2020 ) based on a study in Palestine, concluded that HEIs provided moderate support; they did not train students to use e-learning, neither no guidelines disseminated to students on how to use the virtual platforms. Similarly, Draissi and Yong ( 2020 ) found that the support provided to students in Moroccan HEIs was insufficient due to the lack of infrastructure needed to implement online education successfully. These empirical findings support WorldBank's ( 2020 ) observation that most students had difficulties accessing online learning due to the lack of support from the HEIs. Furthermore, lack of support aggravates student concerns, and simultaneously students lose their interest in attending classes online. Yilmaz et al. ( 2020 ) emphasized that many students do not know what to do in the online learning process and need external support; otherwise, their motivation decreases and affects their academic performance.

From the empirical literature on HEI's relevance to students' learning experience, academic and social concerns, the second hypothesis, H2, is proposed.

• H2: HEI support significantly affects students' academic and social concerns during online education.

Availability of resources is another factor that facilitates the success of online education. Previous research has shown that one of the main challenges for implementing a virtual mode of learning is an internet connection which has proven to be a significant issue for students, especially those located in remote areas. Poor internet connection is considered the main challenge for online education during the pandemic in many studies worldwide (e.g., Baticulon et al., 2020 ; Kamarianos et al., 2020 ; Means & Neisler, 2020 ; Sahu, 2020 ). A study conducted in China found that network coverage in remote areas is insufficient. Learners in mountainous areas had to walk for hours to find places with stable network signals (Huang et al., 2020 ).

Similarly, in Egypt, Mahdy ( 2020 ) found that learners suffered from poor internet connectivity during the lockdown, which affected the quality of their learning. In Morocco, students encountered several issues during online education due to network capacity and lack of internet access in remote and rural areas. The government addressed it by utilizing television channels to broadcast lectures for HEI students. In Saudi Arabia, limited bandwidth has been a significant issue reported by both teachers and students during the pandemic (Khalil et al., 2020 ; Alnajjar et al., 2020 ). Lassoued et al. ( 2020 ) investigated the obstacles encountered by 300 students experiencing distance education in four Arab countries during the COVID-19 pandemic (Algerian, Egyptian, Palestinian, and Iraqi). The students stated that the lack of resources needed during online education, namely internet connection, was a significant challenge. In contrast, a study conducted in the UAE (Almuraqab, 2020 ) found that 74.5% of respondents had good internet access and appropriate devices for online learning.

Although we focus on infrastructure at HEI, resources available with students, teachers and HEI are also significant determinants of the effectiveness of distance online learning. In Oman, the government has initiated a strategy to provide laptops to all students in HEIs, which is an excellent gesture to ensure the availability of adequate infrastructure during online classes. For instance, in the Mckinsey & Company report in the USA, Kim et al. ( 2020 ) reported that only 11% of the participants reported having all the necessary equipment for remote learning. Having necessary devices like laptops is an essential requirement for successful online learning. However, many studies indicate that students rely more on their smartphones during online education, which might not be compatible with many online platforms and programs. For example, Mahdy ( 2020 ) found that the most used devices by students in 86 countries were smartphones. Also, lack of devices or limited access due to gadget sharing were encountered by medical students in the Philippines (Baticulon et al., 2020 ) and Pakistan (Abbasi et al., 2020 ). In addition, during the pandemic, many students have difficulties accessing online education due to the lack of basic digital skills (Lassoued et al., 2020 ; World Bank, 2020 ). It caused students to lose interest in attending classes online, affecting their academic achievement (Arënliu & Bërxulli, 2020 ; Quacquarelli Symonds, 2020 ). Shetty et al. ( 2020 ) reported many concerns facing students like lack of face-to-face interactions, lack of socialization, distraction by social media, and technology-related issues. They rated their concern about health, hygiene measures, and the feeling of loneliness as the significant reasons for their social concerns. Among the social concerns, students worried about their health and lack of social interaction leading to a lonely life. These observations support Guangul et al. ( 2020 ), Fernandez and Shaw ( 2020 ), Khalil et al. ( 2020 ), and Alnajjar et al. ( 2020 ). Reassuring students and parents with targeted communication should be vital in the institutional response (Daniel, 2020 ) to address the student concerns. Daniel ( 2020 ) further explained that teachers and counselors might be better than parents at assuaging students' anxieties in deprived situations. HEI should maintain continuous interaction with the students, using synchronous and asynchronous teaching and learning modes. Almuraqab ( 2020 ) considered the resources to support teaching and learning an essential requirement to ease students' concerns. (See Fig. ​ Fig.1 1 )

Conceptual framework

Son et al. ( 2020 ) conducted interview surveys with 195 students at a large public university in the United States to understand the effects of the pandemic on their mental health and wellbeing. The majority of the participants indicated increased stress and anxiety due to the COVID-19 outbreak. They fear and worry about their health and loved ones, difficulty concentrating, disruptions to sleeping patterns, decreased social interactions due to social distancing and increased concerns on academic performance. Therefore, the third hypothesis is proposed:

• H3: Resource availability significantly affects students' academic and social concerns during online education.

Research methodology

Data collection method.

A quantitative survey method using a structured questionnaire is adopted for data collection. It is considered as an efficient way of collecting data from many respondents in geographically spread areas within a short time (Campbell et al., 2004 ). The researchers designed the questionnaire; some items of the questionnaire were developed from the literature review and previous studies (e.g., Quacquarelli Symonds, 2020 ; Almuraqab, 2020 ; Abu Shekhadim et al., 2020 ), while others were based on the researchers' experience and intuitiveness during the COVID-19 pandemic. The questionnaire included different parts. Part one consisted of demographic information of the participants such as gender, specialization, year of study, institution type (private or government), location of the HEI, type of internet connection they use (wi-fi or data mobile), and laptop ownership., and tools used for online learning (e.g., laptop, smartphone, or others). Part two consisted of student perceptions of the support provided by HEIs (5 items) and the support provided by faculty (4 items) during Spring 2020. They expressed their perceptions on a five-point Likert scale: "very effective = 5", "effective = 4", "neutral = 3", "ineffective = 2", and "very ineffective = 1". Part three consisted of student concerns during online education. They have expressed their concern in 7 items. Part four consisted of resources availability needed for online education (6 items). In parts three and four, students have expressed their opinions on a five-point Likert scale: "strongly agree = 5", "agree = 4", "neutral = 3", "disagree = 2", "strongly disagree = 1". The questionnaire also had open-ended questions that asked students what they appreciated about their lecturers and institutions and the kind of challenges they encountered during online education in the spring semester.

The internal consistency reliability of the questionnaire items was checked through the application of Cronbach's alpha tests of inter-reliability correlations. Table ​ Table1 1 shows Cronbach's Alpha which shows that our questionnaire is reliable given that all the items are above the minimum threshold of 0.7.

Cronbach's Alpha of the Questionnaire's Sections

To verify the validity and practicality of the questionnaire (Oppenheim, 2000 ), it was piloted with a group of students. In addition, to check the content validity, which referred to reviewing the questionnaire items by experts in the field to examine its readability, clarity, and comprehensiveness (Sangoseni et al., 2013 ), the questionnaire was reviewed by experts in the field, and their suggestions incorporated. The ethical considerations were adhered to by obtaining permission from institutions. Also, a research ethics form was completed and approved. The researchers obtained participants' informed consent before they participated in the online questionnaire, and they were assured that they could withdraw from the study at any time.

The questionnaire was plotted online from June 20 to July 26, 2020. The questionnaire was prepared in Arabic and English so students could adequately express themselves. The questionnaire link using 'Google forms' shared with the Ministry of Higher Education, and they provided full support for this study and communicated with all HEIs in Oman. They shared the link with their students through email and WhatsApp. The responses covered all regions in the Sultanate of Oman.

As per the most recent data received from the Education Council in the Sultanate of Oman, there are 127,962 students cumulatively enrolled in HEIs in Oman. In this study, we had 11,141 respondents, a response rate of 9%. This rate is sufficient as it aligns with the generalized scientific guideline for sample size decisions proposed by Krejcie and Morgan ( 1970 ). Krejcie and Morgan ( 1970 ) noted that as the population increases, the proportion of the population required in the sample size is reduced or even becomes static after reaching a specific limit. However, if the population size is small, then the whole population may be required as the sample (e.g., less than 30) (p. 610). For this study, the suitability of data checked using Kaiser–Meyer–Olkin (KMO) and the Bartlett test. Here the KMO measure is greater than 0.6 (0.938), and the Bartlett test is statistically significant (0.000), so the data is deemed valid for use in this research (Bartlett, 1954 ; Kaiser, 1974 ).

Data are coded using Microsoft Excel and performed statistical analysis using Microsoft Excel and SPSS version 22. While reporting descriptive data, the study utilized percentage, mean (M) and standard deviation (SD). Hypothesis testing used the p -value, as recommended by Tabachnick and Fidell ( 2007 ). The study employed regression analysis and factor loading to explore the underlying relationships and the associations between the dependent and independent variables. Cronbach's alpha score confirmed the internal consistency of the questionnaire.

This section consists of results related to the main findings: demographic information of the participants, student perceptions of the support provided by HEIs, the support provided by faculty, resources' availability during online education, and student concerns during online education.

Demographic information of the participants

The demographic profile of participants is described in terms of gender, specialization, year of study, and location of the HEIs they attend. Female participants are more than double that of male. Out of the 11,114 students who participated in this study, 7,590 are female (67.9%), and 3,591 are male (32.1%). Concerning student’s specialization, 3,235 of them belongs to Engineering (28.9%), 2,769 in Business (24.8%), 1,918 in Computer Science/ IT (17.2%), and 1,413 in Nursing (12.6%). We have fewer respondents from other specializations: Applied Sciences (594), Education (244), Pharmacy (152), Language (101), Islamic Study (97), and Medicine (34). We also have 624 students from other specializations. All our participants are undergraduate students: 2,132 (19.1%) are still in the foundation program, 2,302 (20%) are in the first year of study, 2,743 (20.6%) respondents are in the second year of study (24.5%), 2,074 (18.5%) in the third year of study, 1,776 (15.9%) in the fourth year of study, and 87 students in other years of their studies. Their age ranged between 18 to 23 years old. Most of our respondents belong to government HEIs ( N  = 9108, 81%). Furthermore, our participants are studying in HEIs located in different regions in Oman. 35.7% of participants belong to Muscat ( N  = 3997), as most HEIs locates there. 60.4% HEIs moved online towards the end of the semester, while 28.7% and 10.9% moved online in the middle and at the beginning of the semester, respectively.

At the time of the data collection, less than half of our participants have their laptop ( N  = 5,140, 46%), while 4,046 share the same laptop with other people in the same house (36.2%), and 1,995 do not have a laptop at all (17.8%). Many of our participants have used their mobile data ( N  = 4,751, 42.5%) for internet connection, while only 2,717 (24.3%) have used wi-fi at home, and 3,713 (33.2%) have used both wi-fi and mobile data.

Descriptive analysis of the data

Table ​ Table2 2 presents the descriptive data. Students rated their perceptions with the support provided by the HEIs (3.45) more than the faculty support (3.02). Resource availability such as internet connection, having a suitable place for online studying, and having the required equipment to study online are rated moderate (3.13).

Mean and Standard Deviation

Students' social concerns due to anxiety, worries, and loneliness averaged (4.08). The pandemic and the subsequent lockdown forced students to change their academic routines completely, move online and socially distant. Interestingly, students' academic concerns averaged 4.25. Among the students' academic concerns, whether they will complete the academic semester, the workload during online education, and whether they will graduate on time were major academic concerns. Their average score significantly reflected both academic concerns and social concerns.

An interesting observation based on the correlation, shown in Table ​ Table3, 3 , there is a significant relationship between academic concerns and social concerns ( r  = 0.479, p  < 0.001).

Correlation Between Variables Selected

*Significant at 0.05 level; **significant at 0.01 level

Regression analysis

The results ( f -statistic = 1047.376, p  < 0.001) explains that 23.3% of the variability in student's academic concerns (adjusted R 2  = 27.5) can be explained by HEI support, faculty support and resource availability. The R 2 value is deemed accepted if greater than 0.1 and was deemed adequate for our study (Falk & Miller, 1992 ; Van Tonder & Petzer, 2018 ). Table ​ Table4 4 gives information about the regression coefficients for the predictor variables entered into the model. HEI support, faculty support, resource availability, and social concerns were significant predictors. Specifically, for the dependent variable (student social concern) an R 2 value equal to 0.234 was obtained, which declares that the independent variables (HEI support, faculty support, resources, and academic concerns) explained this dependent variable at 27.5%. (See Fig. ​ Fig.2 2 ).

Regression Results of (Academic Concern as Dependent Variable)

H 1 : Our data support the hypothesis that the HEI support (e.g., sharing timely information, technical support, and showing care for students) while taking online classes from home during the COVID-19 pandemic has a significant impact on the students' academic concern

H 2: Our data support the hypothesis that the faculty support (e.g., showing care for students, engaging and interacting with them) while taking online classes from home during the COVID-19 pandemic has a significant impact on the students' academic concern

H 3 : Our data support the hypothesis that the availability of the resources (e.g., internet connection, equipment needed for online education, suitable places to study) while taking online classes from home during the COVID-19 pandemic has a significant impact on the students' academic concern

Similarly, variables that were found significantly correlated with the dependent variable, student social concerns, were entered as predictors into a multiple regression using the standard method. A significant model emerged : F (4, 11,176) = 851.781, p  < 0.001. The model explains that 23.4% of the variance in student's social concerns (adjusted R 2= 23.3). Table ​ Table5 5 gives information about the regression coefficients for the predictor variables entered into the model. HEI support, faculty support, resource availability, and social concerns were significant predictors. Specifically, for the dependent variable (student academic concern) an R 2 value equal to 0.275 was obtained, which declares that the independent variables (HEI support, faculty support, resources, and social concerns) explained this dependent variable at 23.4%. (See Fig. ​ Fig.3 3 ).

Regression Results of (Social Concern as Dependent Variable)

H 1 : Our data support the hypothesis that the HEI support (e.g., sharing timely information, technical support, and showing care for students) while taking online classes from home during the COVID-19 pandemic has a significant impact on the students' social concern

H 2: Our data support the hypothesis that the faculty support (e.g., showing care for students, engaging, and interacting with them) while taking online classes from home during the COVID-19 pandemic has a significant impact the students' social concern

H 3 : Our data do not support the hypothesis that the availability of the resources (e.g., internet connection, equipment needed for online education, suitable places to study) while taking online classes from home during the COVID-19 pandemic has a significant impact on the students' social concern

Factor analysis

In order to verify whether the selected variables are significant predictors of the dependent variables, the study utilized factor analysis. The composite reliability, Cronbach's alpha, average variance extracted (AVE), and Variance Inflation Factor index (VIF) were calculated to test the internal consistency and validity of the model. It is generally known that if the reliability coefficient is above 0.7, then it is acceptable (Carrasco & Jover,  2003 ), which shows that the measures are reliable and internally consistent.

Table ​ Table6 6 shows composite reliability is above 0.70 for all the variables in this study. The model's reliability is considered good if the composite reliability is more than 0.6 and the average variance extracted (AVE) is greater than 0.5 (Srinivasan et al., 2002 ). This level of AVE or higher indicates that, on average, the construct explains 50 percent or more of the variance of its indicators. Moreover, the AVE in this study is above 0.50, which indicates that the latent variables have a convergence ability that is quite ideal. The Variance Inflation Factor (VIF) is used to measure the degree of multi-collinearity of the independent variable with the other independent variables in a regression model. A value of ≤ 10 for VIF and 0.10 for the minimum level of tolerance is considered acceptable levels (Rovai et al., 2013 ).

Factor Loading

The changes happening in the DV variable can be explained collectively by the three factors 74.1% of the time. This means that about 26% can be explained by other variables not explored in this study. The model's validity is explained here, using the AVE, VIF, Cronbach alpha, Composite Reliability and R 2. Based on the factor analysis, HEI support, faculty support and resources are combined as factor I, while social concerns and academic concerns are combined as Factor II. Together they explain 74.4% of the variance out of total. This means that other factors will explain a 22% variance. The analysis is done using the rotation method.

While examining the impact of the Covid-19 pandemic on students at HEIs, it is observed that all the empirical literature has univocally concluded that both social and academic concerns significantly influenced student experience in online learning at HEIs. The literature also highlighted the role of HEI support, faculty support, and resources in addressing the social and academic concerns of the students. Three major inferences were drawn based on the analysis. At first, this research supports the previous empirical findings that social concerns and academic concerns significantly affect student learning in online classes during the pandemic. Secondly, this research found that HEI support, faculty support, and resources available are significant predictors of academic concerns. The third important observation is that HEI support and faculty support significantly influence the student's social concerns. All the inferences point out that though the pandemic created social and academic concerns, strategic interventions from the HEI can play a significant role in addressing the concerns. Students feel lonely and are tensed due to the pandemic. However, HEI support, faculty support, and resources can play a major role in reducing social and academic concerns.

As outlined, this research furthers the empirical findings that students' academic and social concerns were significant during the current pandemic. For example, Shetty et al. ( 2020 ) considered it due to a lack of face-to-face communication, lack of social interaction, and technology-related issues. They rated their concern about health, hygiene measures, and the feeling of loneliness as the significant reasons for their social concerns. Among the social concerns, students worried about their health and lack of social interaction leading to a lonely life. These observations support Guangul et al. ( 2020 ); Fernandez and Shaw ( 2020 ); Khalil et al. ( 2020 ); Alnajjar et al. ( 2020 ); Son et al. ( 2020 ). Socialization is a significant part of student experiences before the pandemic. However, the emergency remote teaching, lockdown, and social distancing measures created anxiety and stress among students due to the suspension of face-to-face classes. Empirical research highlighted that students experienced stress, increased anxiety, and feeling less motivated (Almuraqab, 2020 ; Aristovnik et al., 2020 ; Duraku & Hoxha, 2020 ; Gillis & Krull, 2020 ). This research furthers the empirical findings and reports that social concerns significantly influenced their behavior during the pandemic. Four statements were mainly focused on the student's social concerns, and the overall score of the statement was 4.08, indicating a firm agreement with these statements. This inference is also significant and requires the attention of HEI and faculty.

As the coronavirus (COVID-19) is still around, this is a time of momentous change, and communication with students is more crucial than ever. Therefore, HEIs should use all possible means to communicate necessary information to their students. Tyrovolas et al. ( 2020 ) in Saudi Arabia reported that students perceived social media (e.g., Facebook and WhatsApp) as a more appropriate tool for communication due to its ease of use and simplicity. Therefore, HEIs should activate their accounts on social media and communicate information to their students. Additionally, the HEIs should communicate with students personally through personalized messaging and orientations as it is known that personal touch is an effective technique for involving students and supporting them. HEIs can also produce videos about health and safety measures or rationale for decisions made and send them to students and their families. In addition, the HEIs should support students to diminish students' concerns by providing them with counseling services. Daniel ( 2020 ) explained that counselors might be better than parents at assuaging students' anxieties in deprived situations.

Specifically addressing the academic concerns, this research established that HEI support, faculty support, and resources significantly influence student's academic concerns. Unlike face-to-face teaching, wherein the students and faculty interact daily, online learning created a physical distance. Add to this the social pressures and tensions posed by the pandemic. In order to mitigate students' academic concerns, HEIs strategic interventions are required. For instance, the HEIs have to design appropriate and compelling content and establish an adequate infrastructure for their current faculty to achieve better learning outcomes.

Furthermore, HEIs should provide their faculty with the necessary training to successfully carry out online learning, increase student interaction, and achieve quality in online education. HEIs must encourage synchronous online sessions since they give lecturers more opportunities to interact with their students, respond to their inquiries, and establish peer collaboration, leading to a better understanding of the topics studied (Papadima-Sophocleous & Loizides, 2016 ). Teachers should utilize professional development activities to improve their technological and pedagogical competencies. Communities of Practice (COP) are recommended to share common interests or passion in a certain area and regularly meet to exchange ideas and assist each other to develop professionally (Wenger et al.,  2002 ).

The reasons for academic concerns are increased workload (Realyvásquez-Vargas et al., 2020 ; Aristovnik et al., 2020 ; Mishra et al., 2020 ), the volume of assignments (Al-Salman & Haider, 2021 ) lack of proper guidance (Ali, 2020 ; Sullivan et al., 2018 ). All these factors were significant based on the analysis. For instance, the statement "my university/college workload has significantly increased during online education' is rated as strongly agree, with a mean score of 4.08 by students. This observation supports the empirical research findings and requires the attention of HEI administrators. As students, similar to any other group of people, are also undergoing tremendous pressure due to the pandemic in terms of health and safety concerns and feelings of loneliness, adding more assignments and activities will only negatively impact their studies. This also requires HEIs and faculty to continuously interact with students and address their concerns to feel supported during this pandemic. Blackmon and Major ( 2012 ) emphasized that teachers had a substantial impact on students' online education experience, largely through their being accessible during the course and providing needed support to their students. They also highlighted that if the students had negative experiences with their teachers due to lack of contact or support, students would be uncomfortable during the online experience, affecting their performance. Therefore, the HEIs need to develop policies and procedures to ensure that teachers provide adequate support for their students during the online teaching mode. This can be done via conducting one-to-one meetings with individuals or groups of students to address their needs or via their efforts to provide opportunities for their students to connect with peers.

The findings revealed that resources such as internet connectivity have also impacted student's academic concerns. Internet connectivity issues hinder student's ability to attend and participate in their course online. Internet connection has been an issue for many years, and the research findings complement numerous previous studies in different parts of the world, not exclusively limited to Oman (Ali, 2020 ; Amita, 2020 ; Duraku & Hoxha, 2020 ; Huang et al., 2020 ; Lassoued et al., 2020 ; Means & Neisler, 2020 ). Therefore, Oman needs to enhance its online infrastructure, especially internet connection, speed, and internet prices to benefit from online learning in the future.

Given that the pandemic is ongoing worldwide and strict measures are still continuously applied, such as lockdown and distance education, the COVID-19 pandemic negatively impacts higher education. The research findings demand interventions and preventive strategies to address the academic and social concerns of students. They need psychosocial and robust counseling services to provide the necessary support to help them overcome this stage. Even though COVID has changed the way universities operate, most importantly, HEIs should exert more effort to care for their students and make sure that their concerns are well managed. This can be achieved by constant communication with them and considering sustainable mental health support as a priority for the university. Purcell and Lumbreras ( 2021 ) stated that the pandemic is a period of punctuated equilibrium. The learnings from this period could lead to transformation in the HEI sector towards more significant equity and impact across teaching/learning, research/innovation, community service/engagement, and the staff/students' experience.

Future work should concentrate on students' equal access to DE where student needs and technical profiles are investigated, so necessary policies and interventions can be suggested to provide equal opportunities to all students. In addition, future research should examine the types of interactions among students and teachers during DE and their effectiveness. This is in addition to identifying the best practices to ensure students' wellbeing during DE and maintaining their active engagement with their HEIs, teachers, and peers. In addition, a similar study can be conducted to examine teachers' academic and social concerns,

Acknowledgements

The authors would like to sincerely appreciate the support provided by the Education Council, the Ministry of Higher Education, and the different higher education institutions in Oman. Appreciation is also extended for students for their valuable time and answering the surveys for this research.

No fund was received for this research.

Declaration

The authors declare that they have no competing interests.

Publisher's Note

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Contributor Information

Azzah Al-Maskari, Email: [email protected] .

Thurayya Al-Riyami, Email: mo.ude.tci@r_ayaruht .

Siraj K. Kunjumuhammed, Email: mo.ude.sbcm@jaris .

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Teaching STEM Topics that Spark Student Interest

| By Gale Staff |

Since the start of the twenty-first century, new initiatives in American education have stressed the importance of teaching science, technology, engineering, and mathematics (STEM) to help prepare students for jobs when they enter the workforce. Although readying students for future careers is an important goal of STEM, teachers may want to carve out some STEM education to include students’ interests and natural curiosity. Gale In Context: Middle School has numerous resources that will engage and excite students with a wide range of STEM-related subjects.

Students and teachers can explore an array of scientific topics and choose those which interest them most. The updated database for Gale In Context: Middle School includes resources on anatomy, such as in the portal about the brain, as well as resources covering earth science which can be found in the geology portal. For students who prefer stories about people who have made important contributions to STEM, they’ll also find resources that suit their interests. For instance, the database includes the Elizabeth Blackwell portal, which provides information about the first American woman to receive a medical degree. Still others may be interested in topics about major events in Earth’s history. These students may be interested in the new patterns of extinction portal, whose resources will help students better understand how and why extinction happens. Teachers can guide students’ research by helping them explore the different types of resources available that will spark their interest.

Understanding Extinction

Teachers with students who are already interested in extinction can guide them to the topic overview, where they’ll learn about what patterns extinctions have followed during Earth’s history. Students who understand the basics may not realize that extinction can occur because of natural pressures on a species—such as competition with other organisms—or because of human actions, such as overhunting and environmental damage. Furthermore, numerous extinctions can happen in a short period of time in an event called mass extinction. Students can also deepen their understanding by reading the reference articles “Mass Extinction” and “ Background Extinction ,” which give further insight into specific patterns.

Students who may not be as familiar with extinction can be guided to the video “Species Extinction and Exotic Species,” which provides them with an overview and explains why extinction can happen (for example, an increase in exotic species can take away resources from species already living in a particular ecosystem). This video will engage students by identifying the real-world effects of extinction and help them understand the topic’s importance.

Identifying Examples of Extinction

Students will also find resources that can help them understand more about specific examples of extinction. For instance, one of the most famous extinctions in Earth’s history is the mass extinction of dinosaurs. Students who already know about this may want to deepen their understanding by reading the article “ Were the Dinosaurs Thriving before that Asteroid Obliterated Them? ” which explains that dinosaurs were most likely facing threats to their existence before an asteroid hit. The article theorizes that the dinosaurs faced a “perfect storm” of threatening factors, including the asteroid impact, and that those combined factors caused their extinction.

Students can also learn about specific species and subspecies that have become extinct or nearly extinct during students’ own lifetimes. For example, the video “ Sudan World’s Last Male Northern White Rhino Dies ” covers the death of the rhinoceros subspecies. The video explains that the die-off happened mainly because of poaching and other human-caused factors. This example helps students understand that extinction is an ongoing threat and not just something that happened in the past.

They can also learn about species that have faced threats of extinction at various times for different reasons. For instance, the article “Antarctic Fur Seals, Once Hunted to Near Extinction, Now Face Climate Threat” explains that the seals were hunted for their fur in the 1800s, and that they nearly went extinct because of human overhunting. In the 1900s, however, new laws protected the seals, allowing the population to rebound. By the 2000s, the seals faced a new threat, as scientists believe that climate change is putting pressure on the population, observing that the seals have lower birth weights and other factors that indicate they’re facing food shortages. Scientists believe these food shortages are caused by climate change, as warmer waters have decreased the number of krill—a staple food for seals—in Antarctic waters.

Discovering Possible Effects of Extinction

The Patterns of Extinction portal also provides students with resources that discuss effects or possible effects of extinction. These types of resources are impactful because they discuss why the topic of extinction is important in the real world. In the video “ A Tale of Two Urchins ,” two different species of urchins, although related, have very different behaviors, which means they have different impacts on the ecosystems around them. The video helps students understand that the extinction of one species—even one whose relatives survive and thrive—may have major impacts on certain ecosystems.

The article “Mass Extinction Also Changed Ocean Ecology” explains that scientific research supports the idea that a mass extinction which happened about 250 million years ago had extreme effects on life in our oceans. Scientists believe that the effects are still apparent today because this extinction caused animals that hunted their own food to survive in larger numbers than organisms that filtered nutrients from the water. From this article, students will better understand the impact of extinction and how it can permanently affect life on Earth.

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Two Johns Hopkins students named Goldwater Scholars

The goldwater scholarship provides financial support to undergraduates pursuing research careers in stem fields.

By Hub staff report

Johns Hopkins juniors Kyra Bowden and Grace Luettgen were recently awarded the prestigious Barry Goldwater Scholarship .

Image caption: Kyra Bowden (left) and Grace Luettgen

The scholarship, named in honor of late Senator and Major General Barry Goldwater, supports college sophomores and juniors pursuing research careers in engineering, mathematics, and the natural sciences. Bowden and Luettgen are being recognized for their respective work in the fields of biomedical engineering and biophysics.

This year, the Goldwater Scholarship Foundation is supporting 438 new scholars selected from an applicant pool of about 5,000. Each scholar will receive up to $7,500 per academic year until either two years have passed or the student graduates. Schools can nominate up to four applicants each year.

Kyra Bowden

Biomedical engineering

Bowden aspires to use machine learning and image analysis to study disease and injury and optimize outcomes for orthopedics patients. Working with Seth Blackshaw and Jonathan Ling since spring 2022, Bowden has analyzed differential exon inclusion in proteins using ASCOT, a database of alternative splicing events drawn from hundreds of thousands of mouse and human RNA sequencing datasets, and developed Python scripts to use the AlphaFold v2.0 AI platform to model how ASCOT-identified splicing events impact protein structure and function. Bowden has received author credits in the top journals  Nature Communications  and  Nature Medicine  and is the first author of a poster presented at the Society for Neuroscience. She also received a grant from the Leong Summer Research Fund and will be spending this summer in Switzerland as part of the École Polytechnique Fédérale de Lausanne Excellence Research Internship Program. Outside of the lab, Bowden has served as a resident advisor since her sophomore year and is an officer of the Johns Hopkins chapters of the Biomedical Engineering Society and SHARE (Supporting Hospitals Abroad with Resources and Equipment). She volunteers with Thread, JHU Tutorial Project, and at a local health care center.

Grace Luettgen

Physics, Biophysics

Luettgen wants to design signaling proteins that modulate interactions between the immune system and diseased cells. Luettgen has been working in Brian Camley's lab since the spring of her first year, where her first project focused on developing a computational model to elucidate potential mechanisms of cell cluster migration, a process crucial to tissue development, wound healing, and cancer metastasis. She is now concentrating on chronic lymphocytic leukemia, using computational modeling to understand how malignant lymphocytes invade the lymph nodes by sensing changes in chemical cues. She is the first author of a recent presentation on this leukemia research at the American Physical Society and won an ASPIRE grant to help fund it. Luettgen has also assisted Aleksandrina Goeva and Miri Adler at the Broad Institute of MIT and Harvard on gene regulation of cerebellar neurons and communication between molecular layer interneurons (MLIs) and Purkinje layer interneurons (PLIs). Outside the lab and academic work for her two majors, Luettgen is an organizer for JHU Tutorial Project and volunteers with SHARE and Baltimore First, providing tech support to elderly members of the Baltimore community.    

To learn more about applying for the Goldwater Scholarship and other scholarships, visit the university's National Fellowship Program website .

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Tagged fellowships , undergraduate research

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Cannon Cline ’25, center, of the Nanticoke tribe and co-president of the American Indian Science and Engineering Society, accompanies prospective Indigenous high school students on a lab tour on March 22.

Through community, Indigenous students thrive in STEM

By caitlin hayes, cornell chronicle.

Growing up in coastal Delaware and Maryland as part of the Nanticoke tribal community, Cannon Cline ’25 became fascinated with the way storms transformed the coastline. As he grew older, he wanted to understand how weather and climate change impacted the land and the communities that live off of it, communities often marginalized like his own.

“I feel very passionate about being able to use what I do and the things I’m interested in to serve my Indigenous community and any underserved community,” said Cline, an Earth and atmospheric sciences major in the College of Agriculture and Life Sciences (CALS) and co-president of the university’s chapter of the American Indian Science and Engineering Society (AISES), a student organization focused on strengthening and growing the Indigenous STEM community at Cornell.

Over the last three years, Indigenous students have worked to resurrect AISES-Cornell after it fell dormant during the COVID-19 pandemic – and in rebuilding have made it stronger and more active. With a membership of around 30 students, AISES-Cornell has collaborated with admissions teams in the colleges to ramp up outreach efforts, held fundraisers, sent large contingents to the AISES national and leadership conferences, and provided community and professional development for Indigenous students on campus. The group has become a model chapter and a leader in the region, winning the 2023 AISES Pursuit of Excellence Award and hosting the regional conference twice in the last three years, most recently March 22-23.

Peter Thais ’25, of the St. Regis Mohawk tribe and a biological engineering major in the College of Agriculture and Life Sciences, has worked to revitalize the Cornell chapter of the American Indian Science and Engineering Society, an organization dedicated to creating community among Indigenous students studying STEM at Cornell.

“The primary goal for our AISES chapter is to create a space for Indigenous STEM students to share their thoughts and ideas and what they have in common,” said Peter Thais ‘25, of the St. Regis Mohawk tribe, AISES senior U.S. national student representative and co-president, with Cline, of AISES-Cornell. “I’ve learned there’s so much room for Indigenous peoples in STEM and incorporating community work in STEM, and there’s a lot of traditional knowledge that has a lot of value.”

Increasing visibility, giving back

AISES-Cornell is working to address a challenge many Indigenous students in STEM face: a lack of representation and visibility.

Michael Charles ’16, Diné, citizen of the Navajo Nation, and assistant professor of biological and environmental engineering in CALS, said he’s often been the sole Indigenous person in academic settings.

“There’s an invisibility around just existing that’s hard for students,” said Charles, who serves as informal adviser to AISES and was a part of AISES-Cornell as a student. “Especially students who were raised close to their cultures, a lot of times those cultures are so built on family and connection within their community, that coming to campus can make them feel very isolated.”

Indigenous students can also feel that there isn’t room for their cultural identity within STEM fields, Charles said. “It can be difficult to translate all of the things they do know, to understand that their knowledge and they themselves are a very valuable part of this community.”

But Taylor Heaton ’24, of the Tlingit people of Southeast Alaska and an Earth and atmospheric sciences major in CALS, said she’s seen firsthand how Indigenous students bring unique approaches and frameworks for thinking about problems in STEM fields, especially those related to the environment.

“Sustainability is at the core of a lot of Indigenous communities and always has been,” said Heaton, former president of AISES-Cornell and now the events chair.

Heaton gave as an example the Tlingit value “Wooch Yáx,” which means balance, reciprocity and respect. Thais referenced the Haudenosaunee’s “one dish, one spoon” principle of taking only what is needed from the land. And Charles has framed concepts in chemical engineering through the Navajo worldview embodied in “hózhó,” meaning beauty and balance.

“Within our culture, we’re very much taught within a reciprocity framework, within a community framework, rather than any individual goal or focus,” Charles said. “When we start thinking about how to balance what we give back to landscapes, to nature and what we’re taking and receiving, that fits within these pretty basic sustainability concepts.”

Many students’ work reflects this community focus: Cline hopes his research on saltwater intrusion modeling will help policymakers protect vulnerable agricultural coastal communities as extreme weather events increase. Thais studies the impact of land dispossession on Indigenous food systems in Charles’ lab; he hopes the story his data tells can shape policy to protect and restore the land and provide justice to those whose lands were dispossessed.

“I’ve learned over time that not only is there room for both traditional knowledge and academic or institutional knowledge in the same conversation, but they can go hand in hand to promote one another and be able to push each system forward,” said Thais, a biological engineering major in CALS.

“A big thing that was instilled in me was a sense of responsibility and kinship with the environment and the community at-large, to treat our lands and waters and surroundings with the same respect and love and care you would treat your own family,” Cline said. “That’s a big part of what’s led me down the path I’ve taken and into this career – is this feeling of responsibility and connection to the earth and a responsibility to contribute to my community.”

Building community

In 2022, AISES-Cornell began collaborating with Cornell Engineering’s admissions team, providing them with guidance on how to respectfully reach out to Indigenous communities that may be wary of outside institutions or that may not see Cornell as a place for them.

Students have since connected directly with prospective and admitted students and represented Cornell at numerous outreach events. And they’ve worked with Cornell Engineering to increase visibility for the robust Indigenous community at Cornell, including the American Indian and Indigenous Studies Program (AIISP), the Akwe:kon Program House , and Native American and Indigenous Students at Cornell .

Taylor Heaton '24, of the Tlingit people of Southeast Alaska and events chair for the American Indian Science and Engineering Society, attends an outreach event for prospective Indigenous high school students on March 22.

“Student involvement in outreach for admissions is not just powerful, it’s essential,” said Ginger Jung, assistant director for Cornell Engineering Admissions. “They are having the college experience in real time – they can talk about student and academic life in a way we cannot. And when they share their stories, it creates a lens through which prospective students can see the possibilities for themselves.”

AISES-Cornell works with other partners as well; most recently, on March 22, they teamed with AIISP to connect with and host prospective students at Promising Futures , an annual event to introduce high school students, teachers and counselors to Cornell.

Beyond Cornell, AISES-Cornell has helped establish chapters at other universities and is actively working to strengthen connections in the region. The regional conference held at Cornell in March, overlapping with Promising Futures, brought 125 college and high school students and academic and corporate representatives to campus to discuss the theme of “Sovereignty in Science,” and how research and data can contribute to – and belong to – Indigenous communities. Attending the national AISES conferences each year, with more than 3,000 Indigenous students and professionals, provides an even larger network, and many opportunities for internships, jobs and funding.

“Through AISES, I have this network of Natives in STEM all over the country, at all these different schools, and that’s so valuable,” Heaton said. “And then on campus, I have this closeness and understanding with my peers. It’s pretty awesome.” 

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An hereditary liver disease cured with the help of gene scissors

Researchers at the University of Helsinki and HUS Helsinki University Hospital have succeeded in correcting a gene defect that causes a hereditary liver disease and its adverse effects on cells.

Argininosuccinate lyase deficiency (ASLD), also known as argininosuccinic aciduria, is a disease that has been enriched in the Finnish genetic heritage. In this severe metabolic disease, the body does not process proteins normally, instead resulting in a very dangerous accumulation of argininosuccinic acid and ammonia. Excess ammonia causes disturbances of consciousness, coma and even death.

In Finland, infants are screened for ASLD to determine the disease risk before symptoms develop. The treatment is an extremely strict lifelong diet and, in severe cases, a liver transplant.

Researchers from the University of Helsinki and HUS Helsinki University Hospital have succeeded in correcting the gene defect associated with argininosuccinic aciduria and demonstrated that the harmful metabolism caused by the disease can be cured.

In their recently completed study, they initially modified the skin cells of patients with ASLD into stem cells. Subsequently, the researchers reprogrammed the disease-causing gene defects in the stem cells using the CRISPR-Cas9 technique, known as gene scissors. Finally, the researchers guided the corrected stem cells to differentiate into liver cells to see whether the disease that impairs hepatic function was actually cured and that the fixed cells no longer produced the harmful argininosuccinic acid.

"In our study, we demonstrated for the first time that the gene defect causing ASLD can be corrected with gene scissors without any adverse effects visible in the cells. The gene-corrected cells were also metabolically improved," says Docent of Stem Cell Biology Kirmo Wartiovaara, specialist in medical genetics, from the University of Helsinki and HUS.

The study was published in the American Journal of Human Genetics .

Researchers discover a suitable "gene mixture" in a drug already in use

In the study, the researchers used mRNA encapsulated inside lipid nanoparticles to get the gene scissors inside the cultured cells.

"This 'gene mixture' we produced is based on the formula of a pharmaceutical product already in use, which may facilitate its clinical use in the future. Our next goal is to cure ASLD in mice," says Doctoral Researcher Timo Keskinen from the University of Helsinki.

"The same gene editing technique works on living animals and humans, but we don't yet know how safe it is. This is why the matter has to be investigated first in laboratory animals," Keskinen adds.

Therapeutic potential at last for hereditary diseases

There are already more than 7,000 hereditary diseases in the world. Finns, as well as other populations originating in small groups of people, have their own genetic disease variants that are more common in the population than elsewhere in the world. Many of these gene variants of our distant ancestors are such that if a child inherits the same variant from both parents, they may develop a severe disease.

Treatments are available for only a handful of hereditary diseases, and curative therapies are even more rare.

"However, a cure could be possible if the gene defect causing the disease is eliminated entirely. Thanks to basic research carried out with the help of gene scissors and other precise gene-editing techniques, permanent fixes are gradually starting to emerge," Wartiovaara says.

The study is part of the doctoral theses of Sami Jalil and Timo Keskinen, supervised at the Biomedicum Stem Cell Center of the Biomedicum Helsinki research institute by Docent Kirmo Wartiovaara and Mervi Hyvönen, DMedSc.

• Gene Therapy
• Diseases and Conditions
• Personalized Medicine
• Birth Defects
• Human Biology
• Sickle Cell Anemia
• Gene therapy
• Hepatitis C
• Liver transplantation
• Huntington's disease
• Hip dysplasia

Story Source:

Materials provided by University of Helsinki . Note: Content may be edited for style and length.

Journal Reference :

• Sami Jalil, Timo Keskinen, Juhana Juutila, Rocio Sartori Maldonado, Liliya Euro, Anu Suomalainen, Risto Lapatto, Emilia Kuuluvainen, Ville Hietakangas, Timo Otonkoski, Mervi E. Hyvönen, Kirmo Wartiovaara. Genetic and functional correction of argininosuccinate lyase deficiency using CRISPR adenine base editors . The American Journal of Human Genetics , 2024; 111 (4): 714 DOI: 10.1016/j.ajhg.2024.03.004

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