How to Enhance Adult Self-regulated Learning Behavior in a Blended Learning Environment-Based on a Dual Analysis of SEM and fsQCA
JIANI ZHANG

Sichuan Open University

Abstract

Enhancing adult self-regulated learning behavior in a blended learning environment is a key issue for promoting high-quality development in adult education and building a learning society. By integrating Zimmerman^s triadic model of self-regulated learning, social ecological systems theory, and the technology acceptance model, this study constructs a model of the influence mechanisms of environmental and individual factors on self-regulated learning behavior. Using a combined approach of structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA), this paper conducted an empirical analysis of 441 questionnaire responses from adult learners. SEM results indicate that perceived usefulness serves as the key link between the learning environment and self-regulated behavior- learning motivation has a direct and significant impact on self-regulated behavior, and this effect is independent of environmental factors- platform usability is not a key factor influencing adult self-regulated behavior. The fsQCA further revealed two configurations that trigger high levels of self-regulated learning behavior: the motivation-driven configuration and the external collaboration-driven configuration. Based on these findings, this paper propose the following strategies: a teaching optimization strategy grounded in a value perspective, a classification guidance strategy grounded in a motivation perspective, a community-building strategy grounded in an interaction perspective, and a system support strategy grounded in a collaboration perspective.

Keywords: blended learning-adult self-regulated learning-influence mechanism-SEM- fsQCA

Topic: Distance dan Blended Learning