TY - JOUR
T1 - Investigating effects of perceived technology-enhanced environment on self-regulated learning
AU - Sui, Chi Jung
AU - Yen, Miao Hsuan
AU - Chang, Chun Yen
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - Bayesian structural equation modeling
KW - Self-efficacy
KW - Self-regulation
KW - Technology-enhanced environment
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U2 - 10.1007/s10639-023-12270-x
DO - 10.1007/s10639-023-12270-x
M3 - Article
AN - SCOPUS:85175659401
SN - 1360-2357
VL - 29
SP - 161
EP - 183
JO - Education and Information Technologies
JF - Education and Information Technologies
IS - 1
ER -