Computer Science: Faculty Publications
Investigating Student Belonging, Engagement, and Self-Efficacy in Online and In-Person Learning Environments
Document Type
Article
Publication Date
2-17-2026
Publication Title
Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1
DOI
10.1145/3770762.3772626
Abstract
Computing education has increasingly integrated diverse instructional modalities, including in-person, hybrid, fully online, and synchronous online formats, making it important to understand how these environments impact student experience, which is crucial for promoting equity and retention. This experience report presents findings from a federally funded multi-institutional study of over 300 students enrolled in computing courses across various modalities. We examined (1) how learning environments affect students’ sense of inclusion and connection to their academic community; (2) whether academic self-confidence varies by modality preference or prior online learning exposure; (3) the role of learning assistants (LAs) in supporting collaborative learning and motivation; and (4) how modality choices align with perceived academic performance. This article presents initial findings from a student survey conducted across all participating institutions, focusing on the intersection of course modality, LA presence, and student demographics with key aspects of academic success: belonging, engagement, and self-efficacy. We designed the survey to examine modality preferences, identify patterns in student belonging and self-efficacy, analyze open-ended responses for common themes, explore relationships between course structure, support, and learning behaviors, and investigate factors influencing interest in follow-up participation. We used Likert-scale survey analysis, open-ended text clustering, and predictive modeling to identify patterns that correlate with positive learning experiences. We examine the implications of these findings to explore how learning contexts and support structures impact student outcomes in computing using various data analysis techniques. The insights gained from this research can help instructors and researchers better understand and support students across various learning modalities.
Recommended Citation
Ramasamy, Vijayalakshmi, Hagit Leshem, Maria Reid, Sharon Tuttle, Tiana Solis, Md Ali, Edward Jones, Peter J. Clarke.
2026.
"Investigating Student Belonging, Engagement, and Self-Efficacy in Online and In-Person Learning Environments."
Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1: 901-907.
doi: 10.1145/3770762.3772626 source: https://doi.org/10.1145/3770762.3772626
https://digitalcommons.georgiasouthern.edu/compsci-facpubs/322
Copyright
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