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29-01-2024 | Original Paper

Understanding College Students’ Behavioral Patterns in a Blended Learning Class

Authors: Hengtao Tang, Yeye Tang, Miao Dai, Xu Du, Jui-Long Hung, Hao Li

Published in: TechTrends | Issue 2/2024

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Abstract

Blended learning, integrating online and in-person components, has been increasingly adopted in higher education to enhance students’ learning experience and outcomes. While the advantages of blended learning are well-evidenced, research has primarily focused on the online pre-learning component, neglecting the significance of in-class activities. In-class activities play a crucial role in affording active learning opportunities (e.g., discussion, elaboration), necessitating a systemic understanding of their dynamics. The purpose of this study was thus to systemically investigate college students’ learning behaviors during in-class activities in a blended course. In-class activities were video-recorded and labelled manually following a coding scheme. By establishing a linear regression model, the study identified listening to the instructor’s lecture and taking notes as two predictors of students’ learning gains. Additionally, sequential patterns of learning behaviors during in-class activities were examined. The reciprocal interactions between students’ behavior of listening to the lecture and their note-taking actions were noted. The findings of this study contributed to a systemic view of blended learning by shedding light on students’ learning behaviors and their implications for instructional practice.
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Metadata
Title
Understanding College Students’ Behavioral Patterns in a Blended Learning Class
Authors
Hengtao Tang
Yeye Tang
Miao Dai
Xu Du
Jui-Long Hung
Hao Li
Publication date
29-01-2024
Publisher
Springer US
Published in
TechTrends / Issue 2/2024
Print ISSN: 8756-3894
Electronic ISSN: 1559-7075
DOI
https://doi.org/10.1007/s11528-024-00937-2

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