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

Dahri, Nisar Ahmed; Yahaya, Noraffandy; Al-Rahmi, Waleed Mugahed; Aldraiweesh, Ahmed; Alturki, Uthman; Almutairy, Sultan; Shutaleva, Anna; Soomro, Rahim Bux

doi:10.1016/j.heliyon.2024.e29317

Cited by 239Artificial Intelligence in EducationTechnology Adoption and User BehaviourEducation and Learning Interventions

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

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Dahri, Nisar Ahmed, Yahaya, Noraffandy, Al-Rahmi, Waleed Mugahed, Aldraiweesh, Ahmed, Alturki, Uthman, Almutairy, Sultan, Shutaleva, Anna, Soomro, Rahim Bux·2024·Heliyon

DOI 10.1016/j.heliyon.2024.e29317PMC PMC11016976

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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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The positive effects of SI are consistent with prior research indicating that social expectations, peer endorsement, and collective support can shape users' acceptance of new technologies.
“Similarly, the positive effects of SI are consistent with prior research indicating that social expectations, peer endorsement, and collective support can shape users’ acceptance of new technologies [61,103,104,105,106].”
From Advancing Undergraduate Student Mental Healthcare of Social Anxiety Disorder: Evaluating the Acceptance of AR-Assisted Cognitive Behavioral Therapy Through TAM-Based Constructs. (2026) · cites this paper as [103]

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“Some interventions, such as self-regulated strategy development, have demonstrated the potential to improve academic skills in students with learning difficulties [22].”
Background
The relationship between technology acceptance and self-regulated learning: the mediation roles of intrinsic motivation and learning engagement
Fu-hai, A., Xi, L., & Yu, J. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11959-3 · Cited by 132 · cited 3× · see citing works
“People actively employ self-regulation processes and metacognitive strategies to enhance their learning experiences [73].”
Background
Negative emotions, cognitive load, acceptance, and self-perceived learning outcome in emergency remote education during COVID-19
Tzafilkou, K., Perifanou, M. A., & Economides, A. A. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10604-1 · Cited by 121 · cited 2× · see citing works
“…of technology acceptance in various regions including Germany [50], US [51], Saudi Arabia [52], Pakistan [53], Malaysia [54], Turkey [55], Greece [56], Indonesia [57], South Korea [58], and China [56,57], and across different technology-related domains such as e-learning, remote education,…”
Background
Integrating Communication and Task–Technology Fit Theories: The Adoption of Digital Media in Learning
Al-Rahmi, W. M., Al‐Adwan, A. S., Al-Maatouk, Q., Othman, M. S., Alsaud, A. R., Almogren, A. S., & Al-Rahmi, A. M. (2023) · Sustainability · doi:10.3390/su15108144 · Cited by 116 · cited 1× · see citing works
“The construct reliability, AVE, and CR are presented in Table 3, and factor loading values, as presented in Table 2, indicate the rigorous evaluation of the measurement model ’ s reliability and validity in our study [61,77,124].”
Method
Exploring College Students' Attitudes and Self-Efficacy of Mobile Learning
Yang, S.-H. (2012) · The Turkish Online Journal of Educational Technology · Cited by 115 · see citing works
Can ChatGPT Pass High School Exams on English Language Comprehension?
de Winter, J. C. F. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00372-z · Cited by 115 · cited 2× · see citing works
“It ’ s gained attention in creative writing, coding, teaching innovation, sentiment analysis, and annotation tasks [31].”
Background
Understanding Consumers’ Acceptance Intention to Use Mobile Food Delivery Applications through an Extended Technology Acceptance Model
An, S., Eck, T., & Yim, H. (2023) · Sustainability · doi:10.3390/su15010832 · Cited by 114 · see citing works
Internet banking adoption under Technology Acceptance Model—Evidence from Cambodian users
Ly, B., & Ly, R. (2022) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2022.100224 · Cited by 101 · cited 2× · see citing works
“[84], and [90].”
Background
An Overview: Metacognition in Education
Mahdavi, M. (2014) · International Journal of Multidisciplinary and Current Research · Cited by 93 · see citing works
Factors affecting undergraduates’ selection of online library resources in academic tasks
Joo, S., & Choi, N. (2015) · Library Hi Tech · doi:10.1108/lht-01-2015-0008 · Cited by 87 · see citing works
Acceptance of Mobile Learning Technology by Teachers: Influencing Mobile Self-Efficacy and 21st-Century Skills-Based Training
Dahri, N. A., Al-Rahmi, W. M., Almogren, A. S., Yahaya, N., Vighio, M. S., Al-Maatouk, Q., Al-Rahmi, A. M., & Al‐Adwan, A. S. (2023) · Sustainability · doi:10.3390/su15118514 · Cited by 87 · cited 3× · see citing works
“This study provides a significant gap in the literature by analyzing the factors influencing pre-service teachers ’ decision to use ChatGPT and examining their adoption of the AI tool for metacognitive self-regulated learning [10,28].”
Background
Artificial Intelligence (AI)-Based Technology Adoption in the Construction Industry: A Cross National Perspective Using the Technology Acceptance Model
Na, S., Heo, S., Choi, W., Kim, C., & Whang, S.-W. (2023) · Buildings · doi:10.3390/buildings13102518 · Cited by 86 · see citing works
Factors Influencing the Acceptance of Mobile Collaborative Learning for the Continuous Professional Development of Teachers
Dahri, N. A., Vighio, M. S., Bather, J. D., & Arain, A. A. (2021) · Sustainability · doi:10.3390/su132313222 · Cited by 81 · cited 1× · see citing works
“Learners benefit from actively posing and addressing questions pertinent to their studies to reach their desired learning outcomes [37,38].”
Background
Massive Open Online Course (MOOCs) Acceptance: The Role of Task-Technology Fit (TTF) for Higher Education Sustainability
Alyoussef, I. Y. (2021) · Sustainability · doi:10.3390/su13137374 · Cited by 79 · cited 4× · see citing works
“Reliability and continuing technology usage are strongly correlated with enjoyment [89].”
BackgroundResultInfluential
Exploring student satisfaction and acceptance of e-learning technologies in Saudi higher education
Alqahtani, M. A., Alamri, M. M., Sayaf, A. M., & Al-Rahmi, W. M. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.939336 · Cited by 78 · see citing works
Considerations for Adapting Higher Education Technology Courses for AI Large Language Models: A Critical Review of the Impact of ChatGPT
Tayan, O., Hassan, A., Khankan, K., & Askool, S. (2023) · Machine Learning with Applications · doi:10.1016/j.mlwa.2023.100513 · Cited by 75 · cited 1× · see citing works
“Tayan et al. [39] critically examine the integration of AI chatbots like ChatGPT into higher education technology courses.”
Background
Learning with Generative Artificial Intelligence Within a Network of Co-Regulation
Lodge, J. M., De Barba, P., & Broadbent, J. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.7.02 · Cited by 73 · cited 5× · see citing works
“Further, Lodge et al. [44] explore the transformative potential of generative AI, such as ChatGPT, in education, proposing a "co-regulation" model challenging traditional student-teacher dynamics; AI ’ s role includes providing personalized feedback, suggesting resources, and fostering…”
BackgroundMethodInfluential
Intention and barriers to use MOOCs: An investigation among the post graduate students in India
Mohan, M. M., Upadhyaya, P., & Rajasekharan Pillai, K. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10215-2 · Cited by 68 · cited 2× · see citing works
“[110,111].”
Result
AI-TAM: A model to investigate user acceptance and collaborative intention in human-in-the-loop AI applications
Baroni, I., Re Calegari, G., Scandolari, D., & Celino, I. (2022) · Human Computation · doi:10.15346/hc.v9i1.134 · Cited by 65 · cited 2× · see citing works
“Trust is crucial to technology adoption, as shown in the literature and aligned with studies [80,81].”
BackgroundResult
Impacts of Interview as Research Instrument of Data Collection in Social Sciences
Monday, T. U. (2020) · Journal of Digital Art & Humanities · doi:10.33847/2712-8148.1.1_2 · Cited by 64 · cited 3× · see citing works
“The semi-structured format ensured flexibility, adaptability, and participant comfort [103 – 105].”
Background
Relationship between technology acceptance model, self-regulation strategies, and academic self-efficacy with academic performance and perceived learning among college students during remote education
Navarro, R., Vega, V., Bayona, H., Bernal, V. M. G., & García, A. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1227956 · Cited by 63 · see citing works
Technology acceptance of a machine learning algorithm predicting delirium in a clinical setting: a mixed-methods study
Jauk, S., Kramer, D., Avian, A., Berghold, A., Leodolter, W., & Schulz, S. (2021) · Journal of Medical Systems · doi:10.1007/s10916-021-01727-6 · Cited by 59 · cited 1× · see citing works
“The post-task reflection sessions were an integral component of data collection, allowing participants to provide qualitative insights and share their experiences regarding using ChatGPT for metacognitive self-regulated learning [86].”
Background
Utilizing artificial intelligence to support analyzing self-regulated learning: A preliminary mixed-methods evaluation from a human-centered perspective
Wang, C.-Y., & Lin, J. J. H. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107721 · Cited by 55 · cited 5× · see citing works
“Wang and Lin [8] investigate the potential of AI as a tool for analyzing and supporting self-regulated learning (SRL).”
BackgroundInfluential
Technology Acceptance and Performance in Online Learning Environments: Impact of Self-Regulation
Tabak, F., & Nguyen, N. T. H. (2013) · Cited by 53 · see citing works
Towards Adaptive E-Learning among University Students: by Applying Technology Acceptance Model (TAM)
Alamri, M. M., Al-Rahmi, W. M., Yahaya, N., Al-Rahmi, A. M., Abualrejal, H. M., Zeki, A. M., & Al-Maatouk, Q. (2019) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.f1043.0986s319 · Cited by 53 · cited 8× · see citing works
“This construct reflects the application of metacognitive knowledge and skills to maximize and manage one ’ s learning [63,66].”
BackgroundMethodResultInfluential
The integrated social cognitive theory with the TAM model: The impact of M-learning in King Saud University art education
Almogren, A. S., & Aljammaz, N. A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1050532 · Cited by 52 · see citing works
A study on psychological determinants of users' autonomous vehicles adoption from anthropomorphism and UTAUT perspectives
Tian, Y., & Wang, X. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.986800 · Cited by 47 · see citing works
Mobile-Based Training and Certification Framework for Teachers’ Professional Development
Dahri, N. A., Al-Rahmi, W. M., Almogren, A. S., Yahaya, N., Vighio, M. S., & Al-Maatouk, Q. (2023) · Sustainability · doi:10.3390/su15075839 · Cited by 42 · see citing works
Investigating factors affecting teachers' training through mobile learning: Task technology fit perspective
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Almogren, A. S., & Vighio, M. S. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12434-9 · Cited by 42 · cited 1× · see citing works
“Learners benefit from actively posing and addressing questions pertinent to their studies to reach their desired learning outcomes [37,38].”
Background
Firm Size and Artificial Intelligence (AI)-Based Technology Adoption: The Role of Corporate Size in South Korean Construction Companies
Na, S., Heo, S., Choi, W., Han, S., & Kim, C. (2023) · Buildings · doi:10.3390/buildings13041066 · Cited by 38 · cited 2× · see citing works
“[62,101].”
Background
Usability Evaluation of Mobile App for the Sustainable Professional Development of Teachers
Dahri, N. A., Vighio, M. S., Al-Rahmi, W. M., & Alismaiel, O. A. (2022) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v16i16.32015 · Cited by 30 · cited 1× · see citing works
“Notably, the perception of enjoyment has been consistently linked to the intention to use computers [24,89,90,93].”
Background
SOCIAL INFLUENCE IN TECHNOLOGY ADOPTION RESEARCH: A LITERATURE REVIEW AND RESEARCH AGENDAPreprint
Graf‐Vlachy, L., & Buhtz, K. (2017) · SSRN Electronic Journal · Cited by 27 · see citing works
Assessing the Impact of Mobile-Based Training on Teachers’ Achievement and Usage Attitude
Dahri, N. A., Vighio, M. S., Alismaiel, O. A., & Al-Rahmi, W. M. (2022) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v16i09.30519 · Cited by 25 · cited 3× · see citing works
“Social influence on technology uptake is supported by previous research [41,77,78].”
BackgroundMethodResult
Children's metamemory: A review of the literature and implications for the classroom
Karably, K., & Zabrucky, K. M. (2009) · lnternational Electronic Journal of Elementary Education · Cited by 24 · see citing works
Comparing digital libraries in the web and mobile contexts from the perspective of the digital divide
Zha, X., Zhang, J., & Yan, Y. (2014) · Journal of Librarianship and Information Science · doi:10.1177/0961000614532677 · Cited by 23 · cited 1× · see citing works
“The behavioral psychology research of Fishbein and Ajzen [97] offers a theoretical framework for comprehending how attitude affects behavioral intentions.”
Background
Encouraging engagement: video-conference augmentation of online distance learning environments
Starr‐Glass, D. (2020) · On the Horizon The International Journal of Learning Futures · doi:10.1108/oth-06-2020-0020 · Cited by 23 · cited 1× · see citing works
“In the Chinese context, an et al. [73,74] discovered that technology acceptance significantly impacted middle school students ’ self-regulated learning (SRL), with information management.”
Background
Students’ Intention toward Self-Regulated Learning under Blended Learning Setting: PLS-SEM Approach
Jiang, Y., Wang, P., Li, Q., & Li, Y. (2022) · Sustainability · doi:10.3390/su141610140 · Cited by 23 · cited 1× · see citing works
“[51,58,113].”
University students’ acceptance of mobile learning: A comparative study in Turkey and Kyrgyzstan
Adanır, G. A., & Muhametjanova, G. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10620-1 · Cited by 21 · cited 1× · see citing works
“…determinants of technology acceptance in various regions including Germany [50], US [51], Saudi Arabia [52], Pakistan [53], Malaysia [54], Turkey [55], Greece [56], Indonesia [57], South Korea [58], and China [56,57], and across different technology-related domains such as e-learning, remote…”
Background
A survey on technology supported collaborative learning tools and techniques in teacher education
Dahri, N. A., Vighio, M. S., & Dahri, M. H. (2019) · International Conference on Information Science and Communication Technology (ICISCT) · doi:10.1109/cisct.2019.8777421 · Cited by 20 · cited 2× · see citing works
“Integrating Artificial Intelligence (AI) holds great promise for enhancing metacognitive self-regulated learning [2,28,29].”
Background
Comparing computer-assisted learning activities for learning clinical neuroscience: a randomized control trial
Rajan, K. K., & Pandit, A. S. (2022) · BMC Medical Education · doi:10.1186/s12909-022-03578-2 · Cited by 14 · cited 1× · see citing works
“Moreover, the flexibility and convenience offered by computer-assisted and mobile-assisted learning can enhance students ’ enjoyment and self-efficacy or personal competency, meta-cognition and self-learning skills ultimately resulting in increased participation in the learning process [71].”
Background
A Glimpse in ChatGPT Capabilities and its impact for AI researchPreprint
Joublin, F., Ceravola, A., Deigmoeller, J., Gienger, M., Franzius, M., & Eggert, J. P. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.06087 · Cited by 13 · see citing works
An AI-enhanced pattern recognition approach to temporal and spatial analysis of children's embodied interactions
Ocak, C., Kopcha, T. J., & Dey, R. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100146 · Cited by 13 · cited 1× · see citing works
“Furthermore, LLMs have evolved beyond text and can now interpret and generate content across multiple formats. their impact is already being felt in the fields of education and research [8,25].”
Background
Preservice Science Teachers’ Perspectives on and Practices Related to Self-Regulated Learning after a Brief Learning Opportunity
Tran, H. H., Capps, D. K., & Hodges, G. W. (2022) · Sustainability · doi:10.3390/su14105923 · Cited by 11 · see citing works
Exploring the Impact of Chat-GPT on Teacher Professional Development: Opportunities, Challenges, and Implications
Ming, G. K., & Mansor, M. B. (2023) · Asian Journal of Research in Education and Social Sciences · doi:10.55057/ajress.2023.5.4.6 · Cited by 8 · cited 3× · see citing works
“A limited amount of research has focused on pre-service teachers, a distinct population with particular expectations and characteristics, despite numerous studies examining educators ’ and students ’ acceptance of technology [42,43].”
Background
Teachers' Perceptions of Netiquette Practices by undergraduate Dental Students During Online Classes in Covid-19 Pandemic
Iqbal, S., Hanif, R., Ali, F., Tahir, M., Minhas, R., Yasmeen, R., Khokhar, A., & Laique, T. (2021) · Pakistan Journal of Medical and Health Sciences · doi:10.53350/pjmhs2115123498 · Cited by 7 · cited 2× · see citing works
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Theorizing Mental Models in Disciplinary Writing Ecologies through Scholarship, Talk-Aloud Protocols, and Semi-Structured Interviews
Adams, L. L. (2014) · OhioLink ETD Center (Ohio Library and Information Network) · Cited by 1 · see citing works

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Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective
Almogren, A. S., Al-Rahmi, W. M., & Dahri, N. A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e31887 · Cited by 194 · see citing works
Perceptions and Use of AI Chatbots among Students in Higher Education: A Scoping Review of Empirical Studies
Schei, O. M., Møgelvang, A., & Ludvigsen, K. (2024) · Education Sciences · doi:10.3390/educsci14080922 · Cited by 166 · see citing works
“Dahri et al. [30] used an extended TAM model, finding a high acceptance of ChatGPT among university students.”
How AI ‐Enhanced Social–Emotional Learning Framework Transforms EFL Students' Engagement and Emotional Well‐Being
Zong, Y., & Yang, L. (2025) · European Journal of Education · doi:10.1111/ejed.12925 · Cited by 163 · see citing works
Investigating influencing factors of learning satisfaction in AI ChatGPT for research: University students perspective
Almulla, M. A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e32220 · Cited by 161 · see citing works
“Satisfied students exhibit higher levels of persistence and achieve better learning outcomes, adopting a positive learning environment [34,35].”
BackgroundMethodResultInfluential
The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT
Alshammarı, S. H., & Babu, E. (2025) · Scientific Reports · doi:10.1038/s41598-025-91634-4 · Cited by 109 · see citing works
“Technology solutions that students perceive as easy to use, such as ChatGPT, are more likely to be used and to interact with 30 .”
How Generative AI Influences Students’ Self-Regulated Learning and Critical Thinking Skills? A Systematic Review
Sardi, J., Darmansyah, Candra, O., Yuliana, D. F., Habibullah, Yanto, D. T. P., & Eliza, F. (2025) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v15i1.53379 · Cited by 105 · see citing works
A SEM–ANN analysis to examine impact of artificial intelligence technologies on sustainable performance of SMEs
Soomro, R., Al-rahmi, W., Dahri, N. A., Almuqren, L., Almogren, A. S., & Aldaijy, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-86464-3 · Cited by 112 · see citing works
Factors Impacting the Adoption and Acceptance of ChatGPT in Educational Settings: A Narrative Review of Empirical Studies
Al-kfairy, M. (2024) · Applied System Innovation · doi:10.3390/asi7060110 · Cited by 97 · see citing works
“This method involves coding the data and organizing them into meaningful categories that reflect the key factors influencing the adoption of ChatGPT [15,21].”
Influential
The Effect of AI Gamification on Students’ Engagement and Academic Achievement in Malaysia: SEM Analysis Perspectives
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Almuqren, L., Almgren, A. S., Alshimai, A., & Al‐Adwan, A. S. (2025) · IEEE Access · doi:10.1109/access.2025.3560567 · Cited by 106 · see citing works
“Teachers often struggle to incorporate 21st-century teaching approaches due to a lack of knowledge and training, further compounding these issues [12], [13].”
Unpacking perceived risks and AI trust influences pre-service teachers’ AI acceptance: A structural equation modeling-based multi-group analysis
Zhang, C., Hu, M., Wu, W., Kamran, F., & Wang, X. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12905-7 · Cited by 95 · see citing works
“Likewise, Dahri et al. (2024) investigated the acceptance of ChatGPT as a metacognitive self-regulated learning (MSRL) tool among 300 pre-service teachers.”
Generative AI tool use enhances academic achievement in sustainable education through shared metacognition and cognitive offloading among preservice teachers
Iqbal, J., Hashmi, Z. F., Asghar, M. Z., & Abid, M. N. (2025) · Scientific Reports · doi:10.1038/s41598-025-01676-x · Cited by 82 · see citing works
A systematic mapping review at the intersection of artificial intelligence and self-regulated learning
Banihashem, S. K., Bond, M., Bergdahl, N., Khosravi, H., & Noroozi, O. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00548-8 · Cited by 82 · see citing works
“Additionally, AI aids metacognition by providing feedback, helping with study planning, and assessing progress, thereby fostering self-awareness and strategic learning (Afzaal et al., 2024; Dahri et al., 2024).”
The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach
Soomro, R. B., Memon, S. G., Dahri, N. A., Al-Rahmi, W. M., Aldriwish, K., Salameh, A. A. M., Al‐Adwan, A. S., & Saleem, A. (2024) · Sustainability · doi:10.3390/su16177351 · Cited by 80 · see citing works
Determinants of ChatGPT Adoption Intention in Higher Education: Expanding on TAM with the Mediating Roles of Trust and Risk
Balaskas, S., Tsiantos, V., Chatzifotiou, S., & Rigou, M. (2025) · Information · doi:10.3390/info16020082 · Cited by 81 · see citing works
“These findings contribute to theoretical discussions on the evolving dynamics in the adoption of AI, where utility alone may not be sufficient without addressing users’ basic concerns [21,26,32].”
Artificial intelligence in higher education institutions: review of innovations, opportunities and challenges
Ocen, S., Elasu, J., Aarakit, S. M., & Olupot, C. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1530247 · Cited by 137 · see citing works
Perceived institutional support and its effects on student perceptions of AI learning in higher education: the role of mediating perceived learning outcomes and moderating technology self-efficacy
Jeilani, A., & Abubakar, S. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1548900 · Cited by 64 · see citing works
Rethinking the importance of social norms in generative AI adoption: investigating the acceptance and use of generative AI among higher education students
Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00535-z · Cited by 69 · see citing works
“This finding indicates that fostering positive attitudes toward GenAI tools is critical for driving their adoption and use among university students, consistent with previous research (Dahri et al., 2024; Nazaretsky et al., 2022; Zou & Huang, 2023).”
Influential
The impact of AI literacy on work–life balance and job satisfaction among university faculty: a self-determination theory perspective
Huang, L., & Zhao, Y. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1669247 · Cited by 55 · see citing works
Large language models: Expectations for semantics-driven systems engineering
Buchmann, R. A., Eder, J., Fill, H.-G., Frank, U., Karagiannis, D., Laurenzi, E., Mylopoulos, J., Plexousakis, D., & Santos, M. Y. (2024) · Data & Knowledge Engineering · doi:10.1016/j.datak.2024.102324 · Cited by 59 · see citing works
The Influence of Social Support Theory on AI Acceptance: Examining Educational Support and Perceived Usefulness Using SEM Analysis
Aldraiweesh, A., & Alturki, U. (2025) · IEEE Access · doi:10.1109/access.2025.3534099 · Cited by 70 · see citing works
“These tools, powered by large language models (LLMs), enable students to access real-time, contextually relevant explanations, generate creative content, and receive writing assistance [59], [60].”
Exploring user acceptance of online virtual reality exhibition technologies: A case study of Liangzhu Museum
Li, J., & Lv, C. (2024) · PLoS ONE · doi:10.1371/journal.pone.0308267 · Cited by 55 · see citing works
Exploring the influence of ChatGPT on student academic success and career readiness
Dahri, N. A., Yahaya, N., & Al-Rahmi, W. M. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13148-2 · Cited by 63 · see citing works
“Furthermore, research has shown that ChatGPT usage can have a significant impact on user outcomes, such as improved academic performance (Dahri et al., 2024a; Lund et al., 2023), enhanced customer satisfaction (Rathore, 2023), and increased user engagement (Choudhury & Shamszare, 2023).”
Influential
Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI
Şimşek, A. S., Cengiz, G. Ş. T., & Bal, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13591-9 · Cited by 44 · see citing works
“Additionally, Dahri et al. (2024) emphasized that addressing teachers’ cognitive and practical needs enhances their willingness to adopt technology.”
Influential
A systematic literature review on designing self-regulated learning using generative artificial intelligence and its future research directions
Xia, Q., Liu, Q., Tlili, A., & Chiu, T. K. F. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105465 · Cited by 67 · see citing works
Training and technology acceptance of ChatGPT in university students of social sciences: a netcoincidental analysis
García-Alonso, E. M., León-Mejía, A. C., Sánchez-Cabrero, R., & Guzmán-Ordaz, R. (2024) · Behavioral Sciences · doi:10.3390/bs14070612 · Cited by 53 · see citing works
AI for Academic Success: Investigating the Role of Usability, Enjoyment, and Responsiveness in ChatGPT Adoption
Kim, M., Kim, J., Knotts, T. L., & Albers, N. D. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13398-8 · Cited by 38 · see citing works
“For example, Dahri et al. ( 2024 ) explored the acceptance of ChatGPT in supporting metacognitive self-regulated learning (MSRL) using an extended Technology Acceptance Model (TAM).”
Assessing clinical medicine students’ acceptance of large language model: based on technology acceptance model
Liu, F., Chang, X., Zhu, Q., Huang, Y., Li, Y., & Wang, H. (2024) · BMC Medical Education · doi:10.1186/s12909-024-06232-1 · Cited by 35 · see citing works
“As peer-to-peer communication is an important way for people to obtain new technology, the adoption of LLMs could be influenced by social impact with network externalities [21, 22].”
Background
Embedding Digital Technologies (AI and ICT) into Physical Education: A Systematic Review of Innovations, Pedagogical Impact, and Challenges
Tohănean, D. I., Vulpe, A.-M., Mijaică, R., & Alexe, D. I. (2025) · Applied Sciences · doi:10.3390/app15179826 · Cited by 35 · see citing works
Analysis of influencing factors on teachers' AI literacy under the SOR framework: An empirical study based on PLS-SEM and fsQCA
Ning, Y., Zheng, H., Wu, H., Jin, Z. M., Chang, H., & Wijaya, T. T. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13477-w · Cited by 39 · see citing works
Understanding Teachers’ Adoption of AI Technologies: An Empirical Study from Chinese Middle Schools
Zhao, J., Li, S., & Zhang, J. (2025) · Systems · doi:10.3390/systems13040302 · Cited by 41 · see citing works
“Furthermore, under the theme of acceptance of AI teaching technologies, novel latent variables—such as Teacher’s Trust [24,27], Subjective Norms [28,29], Anxiety [27,30], and Perceived Risk [13,31]—have emerged, alongside conventional variables like Performance Expectancy, Facilitating Conditions,…”
Embracing generative artificial intelligence tools in higher education: a survey study at the Hong Kong University of Science and Technology
He, A. J., Zhang, Z., Anand, P., & McMinn, S. (2024) · Journal of Asian Public Policy · doi:10.1080/17516234.2024.2447195 · Cited by 42 · see citing works
“In the context of academic learning, learners who have positive attitudes towards the usefulness of ChatGPT tend to demonstrate a higher level of behavioural intention that positively predicts their actual use of it (Abdaljaleel et al., 2024; Almogren et al., 2024; Dahri et al., 2024).”
Artificial intelligence, social influence, and AI anxiety: analyzing the intentions of science doctoral students to use ChatGPT with PLS-SEM
Uludağ, F., Kılıç, E., & Çelik, H. E. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-05641-x · Cited by 38 · see citing works
“Various studies (Algera ﬁ et al. 2023; Zhang et al. 2023; Boubker, 2024; Dahri et al. 2024; Albayati, 2024; Abdalla, 2024) emphasized that SI has an effect on PU.”
Exploring the Role of AI and Teacher Competencies on Instructional Planning and Student Performance in an Outcome-Based Education System
Alwakid, W. N., Dahri, N. A., Humayun, M., & Alwakid, G. N. (2025) · Systems · doi:10.3390/systems13070517 · Cited by 52 · see citing works
Exploring the role of agentic AI in fostering self-efficacy, autonomy support, and self-learning motivation in higher education
Alqurni, J. S. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1738774 · Cited by 41 · see citing works
A Systematic Review of User Attitudes Toward GenAI: Influencing Factors and Industry Perspectives
Chen, J., Wei, X., Xie, Q., Hu, A., Qiao, Y., Wan, R., & Liu, Y. (2025) · Journal of Intelligence · doi:10.3390/jintelligence13070078 · Cited by 36 · see citing works
The effect of artificial intelligence literacy on self-directed learning skills: The mediating role of attitude towards artificial intelligence: A study on nursing and midwifery students
Şengül, T., Sarıköse, S., Uncu, B., & Kaya, N. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104516 · Cited by 26 · see citing works
The psychology of AI adoption in education: University students' intentions to use Large Language Models for learning from a TAM and TPB perspective
Ngo, T. T. A., Vo, T. T. A., & Phan, M. T. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105789 · Cited by 32 · see citing works
AI support in self‐regulated learning: A decade of technological evolution and meta‐analysis
Xu, J. H., Luo, Y., Wang, C., Wang, M., & Wu, Y. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70058 · Cited by 26 · see citing works
AI Adoption for Collaboration: Factors Influencing Inclusive Learning Adoption in Higher Education
Alyoussef, I. Y., Drwish, A. M., Albakheet, F. A., Alqahtani, R. H. A., & Technology, A. A. A. E. (2025) · IEEE Access · doi:10.1109/access.2025.3567656 · Cited by 35 · see citing works
“AI enables personalized instruction, real-time feedback, and information-driven understandings, empowering educators to deliver tailored educational experiences that optimize student learning outcomes [10], [11], [12].”
Influential
The predictors of behavioral intention to use ChatGPT for academic purposes: evidence from higher education in Somalia
Abdi, A.-N. M., Omar, A. M., Ahmed, M. H., & Ahmed, A. A. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2460250 · Cited by 28 · see citing works
“Moreover, consistent with the recent literature, the study found that PEU is positively and significantly associated with the students ’ behavioral intention to use ChatGPT (BIU) for academic reasons (Almogren et al., 2024; Dahri et al., 2024; Yu et al., 2024).”
Influential
Students’ Reliance on AI in Higher Education: Identifying Contributing Factors
Pitts, G., Rani, N., Mildort, W., & Cook, E.-M. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-12773-0_9 · Cited by 52 · see citing works
Facilitating Online Self-Regulated Learning and Social Presence Using Chatbots: Evidence-Based Design Principles
Huang, W., & Hew, K. F. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3523199 · Cited by 21 · see citing works
Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis
Koteczki, R., & Balassa, B. E. (2025) · Education Sciences · doi:10.3390/educsci15081044 · Cited by 34 · see citing works
The Integration of ChatGPT in English for Foreign Language Course: Elevating AI Writing Assistant Acceptance
Salam, U. (2024) · Computers in the Schools · doi:10.1080/07380569.2024.2446239 · Cited by 30 · see citing works
“Dahri et al. (2024) explored the TAM of the acceptance of ChatGPT for Metacognitive Self-Regulated Learning (MSRL).”
Investigating the Impact of ChatGPT as an AI Tool on ESL Writing: Prospects and Challenges in Saudi Arabian Higher Education
Abduljawad, S. A. (2025) · International Journal of Computer-Assisted Language Learning and Teaching · doi:10.4018/ijcallt.367276 · Cited by 19 · see citing works
Exploring the impact of ChatGPT on teaching performance: findings from SOR theory, SEM and IPMA analysis approach
Dahri, N. A., Yahaya, N., Vighio, M. S., & Jumaat, N. F. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13539-z · Cited by 23 · see citing works
“In this way, teachers can integrate AI-driven applications to create an inclusive classroom envi - ronment that helps cater to diverse student needs and enables higher-order thinking skills for all students (Dahri et al., 2024a, b, c , d ).”
Influential
An empirical examination of the adoption of artificial intelligence in banking services: the case of Mongolia
Oyundari, B., Yondon, C., Enkhbat, R., Darkhijav, B., & Rahman, M. (2025) · Future Business Journal · doi:10.1186/s43093-025-00504-y · Cited by 25 · see citing works
Modeling teacher education students’ adoption of large language models through an extended technology acceptance framework
Gong, Y., Xu, C., Luo, S., & Lin, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-03298-9 · Cited by 26 · see citing works
“Teachers’ acceptance of ChatGPT is closely tied to their teaching roles: novice educators are more likely to rely on AI for teaching design, whereas experienced educators tend to view it as a supplementary tool 46 .”
Uncovering the Mediating Effects of AI Trust and Self‐Efficacy on Engagement in Human‐ GenAI Communication for EFL Learning
Zhang, Q., Pan, X., & Fan, J. (2025) · European Journal of Education · doi:10.1111/ejed.70336 · Cited by 17 · see citing works
Examining the Impact of Entrepreneurial Orientation, Self-Efficacy, and Perceived Business Performance on Managers’ Attitudes Towards AI and Its Adoption in Hospitality SMEs
Kukanja, M. (2024) · Systems · doi:10.3390/systems12120526 · Cited by 28 · see citing works
“Empirical research has validated these modified models across a variety of applications, demonstrating their effectiveness in predicting user acceptance [58,59].”
The socio-emotional dangers of using Artificial Intelligence (AI) technologies in second language (L2) education: Unveiling Chinese EFL teachers' perceptions and experiences
Sun, X., Dou, W., & Yang, Y. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105956 · Cited by 16 · see citing works
Prioritizing Ethical Conundrums in the Utilization of ChatGPT in Education through an Analytical Hierarchical Approach
Bukar, U., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., & Sneesl, R. (2024) · Education sciences · doi:10.3390/educsci14090959 · Cited by 18 · see citing works
Research on influencing factors and mechanisms of college students’ use of artificial intelligence tools based on sor and rational behavior models
Bai, L. (2025) · Current Psychology · doi:10.1007/s12144-024-07167-y · Cited by 17 · see citing works
“The integration of these frameworks captures both the environmental influences and rational decision pro - cesses that shape user behavior in educational technology adoption (Dahri et al., 2024).”
Dataset on technology acceptance in E-learning: A PLS-SEM analysis using extended TAM among undergraduate students in Indonesia
Sasongko, A. T., Ekhsan, M., & Fatchan, M. (2025) · Telematics and Informatics Reports · doi:10.1016/j.teler.2025.100192 · Cited by 28 · see citing works
Integrating technology acceptance, self-determination, and self-regulation: A structural model of generative AI-supported learning and competence
Yang, S. C. (2026) · Computers in Human Behavior · doi:10.1016/j.chb.2026.108933 · Cited by 17 · see citing works
Integrating AI chatbots for enhancing academic support in business education: A SEM-Based study toward sustainable learning
Alwakid, W. N., Dahri, N. A., Humayun, M., & Alwakid, G. N. (2025) · The International Journal of Management Education · doi:10.1016/j.ijme.2025.101252 · Cited by 18 · see citing works
Adopting blockchain gamification in education: exploring security, transparency, and trust using SEM analysis
Alwakid, W., & Dahri, N. A. (2025) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-025-13777-1 · Cited by 10 · see citing works
“SEM is well known for its capacity to test sophisticated theoretical models and measure latent constructs through multiple observed indica - tors (Dahri et al., 2024a, b , 2025c; Soormo et al., 2024).”
Chinese EFL learners’ GenAI literacy in digital multimodal composing and self-regulated writing: chain mediation effects of needs satisfaction and creative self-concept
Liu, M., Zhang, L. J., & Neufeld, T. J. E. (2025) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2025.2549754 · Cited by 15 · see citing works
Assessing ChatGPT Adoption in Higher Education: An Empirical Analysis
Dorobăț, I., & Corbea, A. M. I. (2025) · Electronics · doi:10.3390/electronics14234739 · Cited by 16 · see citing works
Primary teachers’ acceptance and sustained adoption of AI powered learner corpora for writing instruction through TAM and ECM perspectives
Zhang, N., Wong, W. L., & Barrot, J. S. (2025) · Scientific Reports · doi:10.1038/s41598-025-21205-0 · Cited by 19 · see citing works
“The two attitudinal drivers that predict behavioural intention in extended TAM research on ChatGPT adoption 13 .”
Changes in Public Perception of ChatGPT: A Text Mining Perspective Based on Social Media
Liu, Y.-T., & Lyu, Z. (2024) · International journal of human computer interactions · doi:10.1080/10447318.2024.2406966 · Cited by 14 · see citing works
“Partial scholars based on unstructured questionnaires employed qualitative analysis methods to investigate perceptions of ChatGPT, compensating for the drawbacks of structured questionnaires (Dahri et al., 2024; Wei et al., 2024).”
Generative AI and Its Potential Impact on Humanity
Nasr, R. S., & El‐Deeb, S. (2025) · International Journal of Consumer Studies · doi:10.1111/ijcs.70024 · Cited by 13 · see citing works
What Shapes Learners’ Trust in AI? A Meta-Analytic Review of Its Antecedents and Consequences
Cui, Y., Zeng, M. L., Du, X. K., & He, W. M. (2025) · IEEE Access · doi:10.1109/access.2025.3611367 · Cited by 17 · see citing works
“Prior research has consistently emphasized that trust in technology is a key determinant of users’ willingness to accept and use new systems [83], [109], as it helps alleviate learners’ concerns about potential risks and uncertainties associated with novel technologies [110].”
Personalised learning in project management education: Insights from an artificial intelligence-driven chatbot
Ingason, H. Þ., Aaltonen, K., Asmundarson, A. S., Friðgeirsson, Þ. V., Huemann, D., Huemann, M., Kujala, J., Lampela, H., Mancini, M., Mariani, C., et al. (2025) · Project Leadership and Society · doi:10.1016/j.plas.2025.100193 · Cited by 17 · see citing works
Decoding ChatGPT’s impact on student satisfaction and performance: a multimodal machine learning and explainable AI approach
Dahri, N. A., Dahri, F. H., Laghari, A. A., & Javed, M. (2025) · Complex Engineering Systems · doi:10.20517/ces.2025.07 · Cited by 10 · see citing works
Foresight for Sustainable Last-Mile Delivery: A Delphi-Based Scenario Study for Smart Cities in 2030
Mutambik, I. (2025) · Sustainability · doi:10.3390/su17156660 · Cited by 9 · see citing works
Exploring students’ perceptions of generative AI-generated feedback in learning programming
Khor, E. T., Chan, L., Koh, E., & SEOW, P. S. K. (2025) · Educational Psychology · doi:10.1080/01443410.2025.2564894 · Cited by 9 · see citing works
“…2024), other studies in different educational and cultural contexts find that subjective norms instead indirectly influence students’ behavioural intentions through its positive effect on students’ acceptance attitudes towards using GenAI (Albayati, 2024; dahri et al., 2024; Tiwari et al., 2024).”
AI literacy and psychosocial factors shaping Chinese university students’ attitudes and behavioral intentions toward generative AI use
Sun, Y., Li, L., Zhang, X., Chen, X., Deng, S., & Hu, X. (2026) · BMC Psychology · doi:10.1186/s40359-026-03989-6 · Cited by 9 · see citing works
A systematic mapping review on how generative artificial intelligence impacts social and emotional learning: A case of large language model chatbots
Liu, H., Fang, X., Cui, Q., & Chiu, T. K. F. (2026) · Review of Education · doi:10.1002/rev3.70141 · Cited by 10 · see citing works
Transforming teacher education through collaborative digital innovations: An empirical study of teachers'perceptions and experiences
Dahri, N. A., Yahaya, N., & Vighio, M. S. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13583-9 · Cited by 11 · see citing works
“This hypothesis aligns with research showing that SRL enhances students’engagement and performance in collaborative settings, driving group learning success (Dahri et al., 2024b; Zimmerman, 1989).”
Investigating factors influencing Chinese teachers’ intelligent technology application: extending TAM with NET and IDT
Zhao, J., Yao, H., & Zhang, J. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13661-y · Cited by 9 · see citing works
“Over the last few years, there has been growing academic interest in artificial intelli - gence (AI) and how to apply it effectively in the teaching process (Dahri et al., 2024).”
Influential
Dimensions of artificial intelligence acceptance among pre-service EFL teachers: exploring usability, usefulness, social norms, ethics and intentions using ChatGPT
AL-Qadri, A. H., & Al-khresheh, M. H. (2025) · The Electronic Library · doi:10.1108/el-12-2024-0391 · Cited by 10 · see citing works
Outsourcing thinking to AI? Focused immersion, AI dependency, and the double-edged impact on critical thinking
Tian, J., & Zhang, R. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-026-07153-8 · Cited by 15 · see citing works
“…use AI as a cognitive scaffold — requesting explanations, counter-arguments, and alternative perspectives — and then actively interrogating these outputs, which can stimulate evaluation and metacognitive monitoring in academic tasks (Cheng and Jiang, 2022; Dahri et al., 2024; Wang and Fan, 2025).”
Acceptance of and Satisfaction with ChatGPT as Learning Tool in Higher Education Through the Technology Acceptance Model (TAM): A Case from the Philippines
Giray, L., Fabros, B. G., Villarama, J. A., Gumalin, D. L., & Saavedra, J. B. (2025) · Internet Reference Services Quarterly · doi:10.1080/10875301.2025.2542212 · Cited by 7 · see citing works
“In their study on ChatGPT’s acceptability, Dahri et al. (2024) revealed how personal competency and social elements support the aim of utilizing AI in metacognitive self-regulated learning among pre-service teachers.”
ChatGPT and higher education student well-being: role of subjective norm and anthropomorphism with TAM
Noor, N., Tong, A., & Zainol, Z. (2025) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-03-2025-0071 · Cited by 8 · see citing works
Research on the factors influencing the adoption of artificial intelligence technology by university librarians
Subuhpoto, S., Liu, G., Su, W., & Aziz, F. (2025) · The Electronic Library · doi:10.1108/el-03-2025-0077 · Cited by 8 · see citing works
Understanding generative artificial intelligence adoption in higher education faculty: evidence from Chinese Universities and technical and vocational colleges
Luo, Y., Zhou, G., & Cui, Y. (2026) · Education and Information Technologies · doi:10.1007/s10639-025-13885-y · Cited by 14 · see citing works
‘A double‐edged tool’: A psychological needs perspective of generative AI and postgraduate international students' engagement in UK higher education
Adekoya, O. D., Ajonbadi, H. A., Mordi, C., Samuel, P., & Nguyen, H. (2026) · British Educational Research Journal · doi:10.1002/berj.70138 · Cited by 11 · see citing works
Promoting Interdisciplinary Learning With Generative AI Through Self‐Regulated Scaffolding
Xia, Q., Yang, Y., Wang, W., & Yin, H. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70214 · Cited by 11 · see citing works
The convergence of GETAMEL and protection motivation theory: A study on augmented reality-based gamification adoption among science teachers
Ateş, H., & GÜNDÜZALP, C. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13480-1 · Cited by 12 · see citing works
“Research confirms that ease of use significantly influences perceptions of usefulness, reinforcing the role of usability in technology adoption (Al-Adwan et al., 2024; Ateş & Yilmaz, 2024; Dahri et al., 2024; Venkatesh & Davis, 2000).”
AI misuse and passiveness of students in medical education
Hosseini, S. M. (2025) · AJP Advances in Physiology Education · doi:10.1152/advan.00164.2025 · Cited by 7 · see citing works
Uncovering structural relationships between AI literacy, AI ethics, AI problem-solving, and self-regulated learning
Bećirović, S., Augustín, M., Mattoš, B., & Dančo, J. (2026) · Discover Computing · doi:10.1007/s10791-026-10042-y · Cited by 7 · see citing works
Scale development and validation of knowledge-attitudes-practices (KAP) on artificial intelligence (AI) productivity tools in education
Sanchez, J. M. P., Sumalinog, G. G., Mananay, J. A., Goles, C. E., Alejandro, I. M. V., & Fernandez, C. B. (2025) · STEM Education · doi:10.3934/steme.2025045 · Cited by 10 · see citing works
Artificial intelligence and academic writing questionnaire (AI-AWQ): development and validation among medical students’ experiences using exploratory factor analysis
Khojasteh, L., Karimian, Z., Nasiri, E., Kafipour, R., & Farahmandi, A. Y. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08288-z · Cited by 7 · see citing works
“Data analysis was conducted using SPSS software, version 26, for Exploratory Factor Analysis.”
The impact of quality of information on classroom engagement with GenAI tools: integrating TAM and SOR framework
Li, F., Chen, J., Shao, T., & Sun, J. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1756708 · Cited by 5 · see citing works
DeepL Translate can be a scaffold to speaking fluency: Technology Acceptance Model (TAM)
Imran, M. C., Marzuki, M., Sasabobe, L., Jubhari, Y., & Sujarwo, S. (2025) · EDULEC Education Language and Culture Journal · doi:10.56314/edulec.v5i1.302 · Cited by 5 · see citing works
Exploring ChatGPT’s role in EFL learning through the technology acceptance model: Perspectives from Saudi students
Alsaedi, N. S. (2025) · Contemporary Educational Technology · doi:10.30935/cedtech/17302 · Cited by 4 · see citing works
The impact of DeepSeek’s perceived interactivity on medical students’ self-directed learning ability
Ju, Y., Li, J., Zhang, X., Wu, M., Pang, X., Li, Z., Wang, J., Li, J., Zhang, Y., & Dai, X. (2026) · Scientific Reports · doi:10.1038/s41598-025-33780-3 · Cited by 4 · see citing works
“Many surveyed educators stated they use AI technologies due to positive peer experiences 60 .”
Öğrencilerin Programlama Derslerinde Üretken Yapay Zekâ Araçlarını Kabulü: Genişletilmiş Teknoloji Kabul Modeli ile Türkiye'den Bulgular
Büyükeke, A. (2025) · Üniversite Araştırmaları Dergisi · doi:10.32329/uad.1728785 · Cited by 4 · see citing works
Leveraging Case-Based Learning Exercises in Pharmacology Courses to Promote AI Readiness Among Student Pharmacists
Munusamy, S., Rao, S., & Rajagopalan, V. (2026) · American Journal of Pharmaceutical Education · doi:10.1016/j.ajpe.2026.101943 · Cited by 5 · see citing works
Unlocking the multifaceted power of self-regulated learning and generative AI in foreign language morphological skills
Huang, F., & Zhang, H. (2026) · Applied Linguistics · doi:10.1093/applin/amag009 · Cited by 4 · see citing works
Examining the use of artificial intelligence in pre-service teacher education
Ponomarenko, E. B., Sergeeva, O. V., ZHELTUKHINA, M. R., Baranova, K. M., Budkevich, R. L., & Melnik, M. V. (2026) · Contemporary Educational Technology · doi:10.30935/cedtech/18458 · Cited by 5 · see citing works
Empowering Learners: GenIA and Their Impact on Self-regulated learning
Safsouf, Y., & Mouachi, R. (2024) · ITM Web of Conferences · doi:10.1051/itmconf/20246901004 · Cited by 4 · see citing works
“The study revealed a strong acceptance of GenAI chatbots among trainee teachers as tools to support self-regulated learning (SRL) in teaching [18].”
Predicting the actual use of artificial intelligence features of Apple Vision Pro using PLS-SEM
Al-Maroof, R. S., Tawafak, R. M., Al-Rahmi, W. M., Alhashmi, K. A., & Alyoussef, I. Y. (2025) · Contemporary Educational Technology · doi:10.30935/cedtech/16208 · Cited by 4 · see citing works
Exploring educators’ perspectives on ChatGPT integration in engineering and management education
Bhaskar, P., Khan, M., & Bhaskar, P. (2025) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-04-2025-0088 · Cited by 5 · see citing works
AI in Tourism Education: A Review of AIGC Teaching and Evaluation Tools
Tan, Z., Yang, Y., Yang, X., Liu, X., Wei, Q., & Kong, L. H. (2025) · International Conference on Education and Training Technologies (ICETT) · doi:10.1109/icett66247.2025.11136881 · Cited by 3 · see citing works
“The integration of AI in education has transformed traditional teaching and learning paradigms through several key applications [33].”
AI-based career management to improve the quality of decision making in higher education
Fawaid, A., Baharun, H., Hamzah, M., Rohimah, R., Munawwaroh, I., & Putri, D. F. (2025) · IEEE Integrated STEM Education Conference (ISEC) · doi:10.1109/isec64801.2025.11147274 · Cited by 41 · see citing works
“With a system that can analyze data quickly and accurately, higher education can provide more targeted career recommendations for students, based on their abilities, interests, and relevant job market trends[27].”
Are pre-service teachers ready to teach the Alpha generation? The impact of pre-service teachers' ChatGPT literacy levels on behavioral intentions toward ChatGPT-4.0
Kılıç, E., Almasri, F., & Çelik, H. E. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100486 · Cited by 5 · see citing works
Factors influencing users’ attitudes towards intelligent chatbots in Chinese academic libraries: the role of algorithm literacy
Lu, H., & Li, X. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-06392-5 · Cited by 3 · see citing works
“In terms of AI device adoption, Dahri et al. (2024) integrated factors such as perceived AI trust and perceived AI capability into the TAM to study ChatGPT usage behavioral intentions.”
Artificial Intelligence for Employee Growth: A Unified Model of Factors Influencing AI-Supported Staff Development Through SEM Analysis
Zahrani, A. A. (2025) · IEEE Access · doi:10.1109/access.2025.3647788 · Cited by 3 · see citing works
“For example, digital infrastructure has been shown to influence e-learning adoption [76], [77], cloud computing acceptance [78], [82], and AI integration in organizational [79].”

Exploring the Acceptance of ChatGPT as a Learning Tool among Academicians: A Qualitative Study
Mukred, M., Mokhtar, U. A., & Hawash, B. (2023) · Jurnal Komunikasi Malaysian Journal of Communication · doi:10.17576/jkmjc-2023-3904-16 · Cited by 17 · see citing works
ChatGPT as a Study Partner : An Extended TAM Approach to Self-directed Learning Adoption
Dipas, K. A. D., & Kim, J. (2026) · The Korean Data Analysis Society · doi:10.37727/jkdas.2026.28.2.523
ChatGPT in the academia: exploring teachers' and students' practices and perspectives in higher education
Begum, M., Butt, M. N., & Ullah, S. (2025) · Asian Education and Development Studies · doi:10.1108/aeds-06-2025-0257 · Cited by 2 · see citing works
Teachers’ Adoption of ChatGPT in Higher Education: Integrating Technology Acceptance, Trust, and Perceived Risk
Alzahrani, L. (2026) · International Journal of Research and Innovation in Social Science · doi:10.47772/ijriss.2026.100800157
ChatGPT in the Malaysian Classroom: Assessing Student Acceptance and Effectiveness Through UTAUT2 and IS Success Models
Sabeh, H. N., Kee, D. M. H., Mohammed, R. B., Albarwary, S. A., & Khalilov, S. (2025) · International Multi-Conference on Systems, Signals & Devices (SSD) · doi:10.1109/ssd64182.2025.10989952 · Cited by 4 · see citing works

Authors: Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., & Soomro, R. B.
Affiliations: University of Technology Malaysia (MY)
King Saud University (SA)
Ural Federal University (RU)
Corresponding author: Dahri, Nisar Ahmed
Yahaya, Noraffandy
ORCID: Dahri, Nisar Ahmed
Yahaya, Noraffandy
Al-Rahmi, Waleed Mugahed
Aldraiweesh, Ahmed
Alturki, Uthman
Shutaleva, Anna
Venue: Heliyon
Publisher: Elsevier BV
Published: 2024-04
Volume: 10
Issue: 8
Pages: e29317
ISSN: 2405-8440 (ISSN-L)
DOI: 10.1016/j.heliyon.2024.e29317
PMC: PMC11016976
OpenAlex: W4394611033
Cited by: 239
References: 113
Citations by year: 2026: 117 · 2025: 99 · 2024: 23
FWCI: 89.86
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor, 3 d)
Locations: Heliyon (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Greater South Information System
Funders: King Saud University (RSP2024R159)
Universiti Teknologi Malaysia (Q.J130000.21A2.07E10)
Research Management Centre, Universiti Teknologi Malaysia
Microsoft Research
Topics: Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Physical Sciences › Computer Science › Information Systems › Education and Learning Interventions
Keywords: ChatGPT, technology acceptance, pre-service teachers, artificial intelligence in education, trust in AI, teacher professional development, AI integration in schools

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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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