Understanding College Students’ Behavioral Patterns in a Blended Learning Class

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

Research output: Contribution to journalArticlepeer-review

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.

Original languageAmerican English
JournalTechTrends
StatePublished - 1 Mar 2024

Keywords

  • blended learning
  • in-class activities
  • lag sequential analysis
  • multimodal
  • systemic

EGS Disciplines

  • Educational Technology
  • Instructional Media Design

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