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      Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study

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          Abstract

          This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record analysis suggest that academics view ChatGPT positively as an educational tool, seeing it as a solution to challenges in teaching and learning processes. The study highlights ChatGPT's potential to enhance MSRL and holds implications for teacher education and AI integration in educational settings.

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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                09 April 2024
                30 April 2024
                09 April 2024
                : 10
                : 8
                : e29317
                Affiliations
                [a ]Faculty of Social Sciences and Humanities, School of Education, University Teknologi Malaysia, UTM Sukadi, Johor, 81310, Malaysia
                [b ]Educational Technology Department, College of Education, King Saud University, P.O. Box 21501, Riyadh, 11485, Saudi Arabia
                [c ]Ural Federal University Named After the First President of Russia B. N. Yeltsin, 620002, Ekaterinburg, Russia
                [d ]Institute of Business Administration, Shah Abdul Latif University, Khairpur, Pakistan
                Author notes
                [* ]Corresponding author. dahrinsiar@ 123456gmail.com
                [** ]Corresponding author. p-afandy@ 123456utm.my
                Article
                S2405-8440(24)05348-9 e29317
                10.1016/j.heliyon.2024.e29317
                11016976
                38628736
                cba7efa4-7cde-4122-8cf2-edf1e76e62d6
                © 2024 The Authors. Published by Elsevier Ltd.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 8 November 2023
                : 2 April 2024
                : 4 April 2024
                Categories
                Research Article

                artificial intelligence,ai in education,metacognition,self-regulated learning,chatgpt,technology acceptance model

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