Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

12-2023

Abstract

This study employs Social Network Analysis (SNA) to explore peer learning behaviors among undergraduate Linear Algebra students. By examining the relational dynamics within the classroom, SNA unveils patterns of interaction, information flow, and collaboration among students. Our analysis identifies the prevalence and evolution of peer learning, and how it influences the students' academic performance. It also unveils the attributes of the students who engage in peer helping and the formation of small communities through such interactions. The findings of the study can provide valuable insights for educators aiming to enhance peer learning and improve educational practices in Linear Algebra and other fundamental subjects, thereby contributing to curriculum development and educational reforms.

Keywords

affective skill, computer science, linear algebra, peer learning, social network analysis

Discipline

Curriculum and Instruction | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE): Auckland, November 27 - December 1: Proceedings

First Page

1

Last Page

8

ISBN

9781665453318

Identifier

10.1109/TALE56641.2023.10398401

Publisher

IEEE

City or Country

Piscataway, NJ

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Additional URL

https://doi.org/10.1109/TALE56641.2023.10398401

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