Using learning analytics with temporal modeling to uncover the interplay of before-class video viewing engagement, motivation, and performance in an active learning context

Jiun Yu Wu*, Chen Hsuan Liao, Chin Chung Tsai, Oi Man Kwok

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Video learning is a crucial component in flipped learning related to learners' readiness to attend more complex face-to-face activities. However, instructors may not know students' preparedness and motivation for each class. This study intended to examine the underlying mechanism between students' before-class video-viewing engagement and performance. We investigated learners' motivation (i.e., autonomous and controlled motivation) based on self-determination theory and controlled for their gender, age, and prior performance. An integrated temporal model was built under the dynamic structural equation modeling framework. Participants were 118 Taiwanese graduate students (78 females and 40 males) with a mean age of 26.14 years old. Study findings showed that students engage with the video content in a consistent viewing pattern, which has a significant relationship with their motivation and academic performance from week to week. The frequency of skipping backward was negatively associated with controlled motivation, while the frequency of pauses was positively associated with autonomous and controlled motivation. A high frequency of skipping forward predicted lower learning performance. Besides, a higher ratio of skipping backward predicted higher controlled motivation. Male students, older students, and students with higher prior performance exhibited higher autonomous motivation, which was related to better learning performance. Understanding these relationships can help educators and instructional designers develop more effective strategies for fostering students’ preparedness, engagement and success in active learning contexts. The study findings were discussed considering theoretical advancement and practical implications for enhancing personalized and active learning in higher education to achieve educational equity.

Original languageEnglish
Article number104975
JournalComputers and Education
Volume212
DOIs
Publication statusPublished - 2024 Apr

Keywords

  • Active learning
  • Data science applications in education
  • Educational equity
  • Gender difference
  • Learning analytics
  • Learning environment
  • Video-viewing engagement

ASJC Scopus subject areas

  • General Computer Science
  • Education

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