Exploring the Pattern and Influence Factors in the Correlation Between Learning Engagement and Academic Achievement in Online Learning

Abstract

This study investigates the complex patterns linking
learning engagement to academic achievement in online
learning environments. By analyzing data from 217
university students using regression, K-means clustering,
ANOVA, and Epistemic Network Analysis (ENA), the research
reveals that simple positive correlations obscure distinct
student profiles. Cluster analysis identified three
groups(high engagement & achievement, low engagement &
achievemenr, low engagement/high achievement), including a
notable "low-engagement/high-achievement" profile. Results
indicate that behavioral engagement serves as the primary
differentiator between high and low academic achievement.
Furthermore, ENA findings suggest that
low-engagement/high-achievement students compensate for
lower behavioral frequency with superior cognitive quality,
characterized by integrated knowledge generation, whereas
low-performing students rely on superficial referencing.
These findings challenge linear engagement–achievement
models, demonstrating that academic success depends less on
the magnitude of engagement than on the structural quality
of cognitive processing and behavioral execution.