skip to main content

Explore Research Products in the NSF-PAR

  • NSF Public Access
  • Search Results
  • Effect of the COVID-19 Pandemic on the Sense of Belonging in Higher Education for STEM Students in the United States and Mexico
Title: Effect of the COVID-19 Pandemic on the Sense of Belonging in Higher Education for STEM Students in the United States and Mexico

The COVID-19 pandemic generated worldwide negative effects on college students’ stress levels and motivation to learn. This research focuses on the lack of development of a sense of belonging in engineering students due to online classes during the pandemic and possible differences experiencing online classes between students from different contexts and cultures. Data were collected from 88 Mexican and 139 U.S. engineering students during the Spring 2021 semester using ten survey items asking students’ perceptions of the effects of taking online courses during the COVID-19 pandemic on their sense of belonging in their major. Quantitative and qualitative analyses were conducted, aiming to determine the effects of taking online classes on students’ sense of belonging in engineering. Findings stressed the poor sense of belonging that engineering students may have after taking online classes during the COVID-19 pandemic when they missed opportunities to develop meaningful relationships with their peers and professors due to the lack of good communication. Consequently, students had uncertainties about successful learning during the pandemic in both Mexico and the U.S. Thus, activities such as accessible office hours, study groups, and meetings with mentors and tutors should be promoted to help students recover from the lack of a sense of belonging in the engineering major generated during online classes due to the COVID-19 pandemic.

  more » « less
Award ID(s):
1730576
NSF-PAR ID:
10487541
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
MDPI
Date Published:
Journal Name:
Sustainability
Volume:
14
Issue:
24
ISSN:
2071-1050
Page Range / eLocation ID:
16627
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ( , Journal of Engineering Education)
    Abstract Background

    A predictor of student success, sense of belonging (SB) is often inhibited for minoritized students in engineering environments and difficult to foster in online courses. A shift to remote learning formats necessitated by COVID‐19, therefore, posed an additive threat to SB for engineering first‐year students, especially those with minoritized identities. Research is needed to understand impacts of online learning to SB for engineering students.

     Purpose Hypothesis(es)

    The study examined factors that promoted or detracted from SB in engineering in remote courses and ways in which identity related to SB.

     Design Method

    Part of a larger mixed‐methods study, this article examines focus group data from 31 first‐year engineering students in 2020 to characterize student experiences in engineering courses moved online during COVID‐19.

     Results

    In addition to the mutually reinforcing nature of SB and learning, findings reveal that the major factors of (a) peer interactions, (b) instructor behavior and course design, (c) environmental identity cues, and (d) personal and psychological factors influenced SB. Examples of factors that positively contributed to SB in remote‐delivery courses included platforms for open communication with peers, “live” ability to ask complex questions, and a critical mass of peers of similar identity; example factors hindering SB included limited use of cameras in synchronous classes, elitist peer interactions, instructor focus on academic performance (vs. growth), and feelings of self‐doubt.

     Conclusions

    Both identity and COVID‐19 impacted SB for students, with results showing four pathways to support SB and learning for diverse students in engineering across course formats.

     
    more » « less
  2. ; ; ; ; ( , Education Sciences)
    The COVID-19 outbreak spurred unplanned closures and transitions to online classes. Physical environments that once fostered social interaction and community were rendered inactive. We conducted interviews and administered surveys to examine undergraduate STEM students’ feelings of belonging and engagement while in physical isolation, and identified online teaching modes associated with these feelings. Surveys from a racially diverse group of 43 undergraduate students at a Hispanic Serving Institution (HSI) revealed that interactive synchronous instruction was positively associated with feelings of interest and belonging, particularly for students of color, while noninteractive instruction reduced social belonging, but was related to more cognitive engagement. Small group and one-on-one interviews with 23 of these students suggest that students derived feelings of connectedness from their instructors, peers, and prior experiences and relied on their sense of competency to motivate themselves in the course and feel a sense of belonging. Two embedded cases of students in physics classrooms are compared to highlight the range of student feelings of connectedness and competency during the lockdown. Findings reaffirm that social interaction tends to support belonging and engagement, particularly for under-represented (Black or African American and Hispanic) racial groups in STEM. STEM instructors who aim to support feelings of belonging and engagement in virtual learning environments should consider increasing opportunities for student–student and student–teacher interactions, as well as taking a flexible approach that validates and integrates student voice into instruction. Future research is needed to further explore the themes of relatedness and competency that emerged as aspects of course belonging. 
    more » « less
  3. ; ; ( , Frontiers in Built Environment)
    null (Ed.)
    The outbreak and emergence of the novel coronavirus (COVID-19) pandemic affected every aspect of human activity, especially the transportation sector. Many cities adopted unprecedented lockdown strategies that resulted in significant nonessential mobility restrictions; hence, transportation network companies (TNCs) have experienced major shifts in their operation. Millions of people alone in the USA have filed for unemployment in the early stage of the COVID-19 outbreak, many belonging to self-employed groups such as Uber/Lyft drivers. Due to unprecedented scenarios, both drivers and passengers experienced overwhelming challenges that might elongate the recovery process. The goal of this study is to understand the risk, response, and challenges associated with ridesharing (TNCs, drivers, and passengers) during the COVID-19 pandemic situation. As such, large-scale crowdsourced data were collected from online ridesharing forums (i.e., Uber Drivers) since the emergence of COVID-19 (January 25–May 10, 2020). Word bigrams, word frequency heatmaps, and topic models are among the different natural language processing and text-mining techniques used to preprocess the data and classify risk perception, risk-taking, or risk-averting behaviors associated with ridesharing during a major disease outbreak. Results indicate higher levels of concern about economic disruption, availability of stimulus checks, new employment opportunities, hospitalization, pandemic, personal hygiene, and staying at home. In addition, unprecedented challenges due to unemployment and the risk and uncertainties in the required personal protective actions against spreading the disease due to sharing are among the major interactions. The proposed text-based data analytics of the ridesharing risk communication dynamics during this pandemic will help to identify unobserved factors inadvertently affecting the TNCs as well as the users (drivers and passengers) and identify more efficient strategies and alternatives for the forthcoming “new normal” of the current pandemic and the ones in the future. The study will also guide us toward understanding how efficiently online social interaction outlets can be designed and implemented more effectively during a major crisis and how to leverage such platforms for providing guidelines during emergencies to minimize transmission of disease due to shared travel. 
    more » « less
  4. ; ; ; ; ( , American Society for Engineering Education 2022 Annual Conference and Exposition)
    During the Spring 2020 semester, universities shifted into emergency remote teaching due to the COVID-19 pandemic. Globally, the pandemic disrupted students learning, their support structures, and interactions with other individuals both socially and academically. In addition, it created lasting impacts on professionals in determining strategies and altering objectives to help undergraduate engineering students achieve their learning objectives. Previous research on social support during the pandemic has focused primarily on singular cultural context, this study was conducted to understand the impact of the pandemic on students support in different cultural contexts. The purpose of this research was to explore how students experienced social capital structures at two institutions: one in the United Kingdom (U.K.) and one in the United States (U.S.) during the period of emergency remote teaching. The survey was designed around social capital theory, it provided demographic information, students agreement with their educational and social interactions, and names of individuals as well as resources they utilized during the pandemic.Results revealed similarities and differences between the two groups. Both case studies had the same top three alters: friends/roommate, professor, and family members, and reported almost the same frequency in communication with their alters. Participants in both case studies also hadhigh rates of support in both expressive and instrumental categories from their top two alters. Examiningthe differences, the UK case had a lower mean response for both sense of belonging and satisfaction at the university. Finally, there was a difference in the types of alters identified in each case due to different cultural contexts. 
    more » « less
  5. ; ; ; ( , Proceedings of the ACM on Human-Computer Interaction)
    As computing courses become larger, students of minoritized groups continue to disproportionately face challenges that hinder their academic and professional success (e.g. implicit bias, microaggressions, lack of resources, assumptions of preparatory privilege). This can impact career aspirations and sense of belonging in computing communities. Instructors have the power to make immediate changes to support more equitable learning, but they are often unaware of students' challenges. To help both instructors and students understand the inequities in their classes, we developed StudentAmp, an interactive system that uses student feedback and self-reported demographic information (e.g. gender, ethnicity, disability, educational background) to show challenges and how they affect students differently. To help instructors make sense of feedback, StudentAmp ranks challenges by student-perceived disruptiveness. We conducted formative evaluations with five large college computing courses (150 - 750 students) being taught remotely during the COVID-19 pandemic. We found that students shared challenges beyond the scope of the course, perceived sharing information about who they were as useful but potentially dangerous, and that teaching teams were able to use this information to consider the positionality of students sharing challenges. Our findings relate to a central design tension of supporting equity by sharing contextualized information about students while also ensuring their privacy and well-being. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email