Investigating effects of perceived technology-enhanced environment on self-regulated learning

• Published in: Education and information technologies Vol. 29; no. 1; pp. 161 - 183
• Main Authors: Sui, Chi-Jung, Yen, Miao-Hsuan, Chang, Chun-Yen
• Format: Journal Article
• Language: English
• Published: New York Springer US 2024; Springer Nature B.V
• Subjects: Bayesian Statistics; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Education; Educational Technology; Influence of Technology; Information Systems Applications (incl.Internet); Science Instruction; Self Efficacy; Self evaluation; Structural equation modeling; Structural Equation Models; User Interfaces and Human Computer Interaction; Technology-enhanced environment; Bayesian structural equation modeling; Self-efficacy; Self-regulation
• ISSN: 1360-2357; 1573-7608
• DOI: 10.1007/s10639-023-12270-x

This study examined the effects of a technology-enhanced intervention on the self-regulation of 262 eighth-grade students, employing information and communication technology (ICT) and web-based self-assessment tools set against science learning. The data were analyzed using Bayesian structural equation modeling to unravel the intricate relationships between self-regulation, self-efficacy, perceptions of ICT, and self-assessment tools. Our research findings underscored the direct and indirect impacts of self-efficacy, perceived ease of use, and perceived use of technology on self-regulation. The results revealed the predictive power of self-assessment tools in determining self-regulation outcomes, underlining the potential of technology-enhanced self-regulated learning environments. The study posited the necessity to transcend mere technology incorporation and to emphasize the inclusion of monitoring strategies explicitly designed to augment self-regulation. Interestingly, self-efficacy appeared to indirectly influence self-regulation outcomes through perceived the use of technology rather than direct influence. Analytically, this research indicated that Bayesian estimation could offer a more comprehensive insight into structural equation modeling by assessing the estimates’ uncertainty. This research substantially contributes to comprehending the influence of technology-enhanced environments on students’ self-regulated learning, stressing the importance of constructing practical tools explicitly designed to cultivate self-regulation.