University Students’ Motivational Profiles Concerning Computer-Supported Learning With Learning Gains, Engagement, and EEG-Based Attention (Poster 6)

• In Event: Thursday Poster Session 2:30 pm
  In Poster Session: Cognitive and Emotional Processes in Learning Environments

Abstract

This research explores how students' need satisfaction, mindsets, goals, and domain-specific self-efficacy cluster and shift in computer-supported learning contexts for gauging learning needs from an instructor’s perspective. Using a two-step cluster analysis, motivational profiles of 71 university students were examined concerning collaborative learning gains, engagement levels, and EEG-based attention waves. Four cluster profiles emerged: growth mover, fixed mover, growth non-mover, and fixed non-mover. The stability of these profiles was confirmed by incorporating domain-specific self-efficacy. Significant differences were found among the profiles in learning engagement, suggesting that higher motivation, regardless of mindset, is linked to increased engagement. Furthermore, a growth mindset acts as a protective factor against decreased engagement. These findings contribute to understanding motivational factors in computer-supported learning.

Authors

• Chiung-Fang Chang, Tamkang University

• Jerry Chih-Yuan Sun, National Yang Ming Chiao Tung University