Higher Education Students’ Use and Continuous Intention to Use Generative AI: A Systematic Literature Review
Main Article Content
This systematic literature review aims to examine existing studies on higher education students’ use and continuous intention to use generative AI to support their studies. Using PICOTQ to build the research question, as well as establish inclusion and exclusion criteria. PRISMA framework was used for the selection process. From 33 records, it was found that most studies were conducted in 2024. China was the country with most studies about generative AI. Most study populations were university students. The generative AI tool most frequently examined was ChatGPT. Most papers employed the UTAUT framework, and the most used factor in the studies was perceived usefulness. Future research should explore relevant moderators, and consider diverse student populations and generative AI tools beyond ChatGPT.
Keywords:
Systematic Literature Review, PRISMA, generative AI, higher education students, use, continuous intention to use
Acosta-Enriquez, B. G., Vargas, C. G. A. P., Jordan, O. H., Ballesteros, M. A. A., & Morales, A. E. P. (2024). Exploring attitudes toward ChatGPT among college students: An empirical analysis of cognitive, affective, and behavioral components using path analysis. Computers and Education: Artificial Intelligence, 7, 100320.
Al-Dokhny, A., Alismaiel, O., Youssif, S., Nasr, N., Drwish, A., & Samir, A. (2024). Can Multimodal Large Language Models Enhance Performance Benefits Among Higher Education Students? An Investigation Based on the Task–Technology Fit Theory and the Artificial Intelligence Device Use Acceptance Model. Sustainability, 16(23), 10780. https://doi.org/10.3390/su162310780
Alam, S. M. A. (2024). Exploring Public University Undergraduate Students’ Experiencing Intention to Use ChatGPT in Academic Purpose: Application of TAM Theory. Journal of Information Systems and Informatics, 6(3), 1413–1434. https://doi.org/10.51519/journalisi.v6i3.789
Alarifi, S. (2025). A Study of the Key Drivers Behind University Students’ Intention to Use and Usage of Generative AI in Academia: Evidence from ChatGPT Use in Saudi Arabia. International Journal of Business and Applied Social Science, 11(8), 1–8. https://doi.org/10.33642/ijbass.v11n8p1
Annamalai, N., Bervell, B., Mireku, D. O., & Andoh, R. P. K. (2025). Artificial intelligence in higher education: Modelling students’ motivation for continuous use of ChatGPT based on a modified self-determination theory. Computers and Education: Artificial Intelligence, 8, 100346. https://doi.org/10.1016/j.caeai.2024.100346
Chen, B., Zhu, X., & Díaz del Castillo H., F. (2023). Integrating generative AI in knowledge building. Computers and Education: Artificial Intelligence, 5, 100184. https://doi.org/10.1016/j.caeai.2023.100184
Chuan, Z., Jianming, O., Xin, Z., Tao, P., Yan, Z., Chunyao, X., Hongxia, T., Qingqi, C., & Kai, L. (2025). Conducting educational intervention research in general practice: From design to publication. Chinese General Practice Journal, 2(3), 100073. https://doi.org/10.1016/j.cgpj.2025.100073
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10039-y
Du, K. (2024). Chinese Students’ Continued Intention to Use Liulishuo App to Learn English Speaking Skills in Non-mandatory Environment: A Case in a Chinese University. International Journal of Information and Education Technology, 14(5), 681–689. https://doi.org/10.18178/ijiet.2024.14.5.2093
Duong, C. D. (2024). Modeling the determinants of HEI students’ continuance intention to use ChatGPT for learning: a stimulus–organism–response approach. Journal of Research in Innovative Teaching & Learning, 17(2), 391–407. https://doi.org/10.1108/JRIT-01-2024-0006
Eedelouei, S. (2026). Factors influencing language teachers’ judgements and decision-making about the use of generative AI tools: A systematic review. Teaching and Teacher Education, 171, 105333. https://doi.org/10.1016/j.tate.2025.105333
Esiyok, E., Gokcearslan, S., & Kucukergin, K. G. (2025). Acceptance of Educational Use of AI Chatbots in the Context of Self-Directed Learning with Technology and ICT Self-Efficacy of Undergraduate Students. International Journal of Human–Computer Interaction, 41(1), 641–650. https://doi.org/10.1080/10447318.2024.2303557
Huang, F., & Zou, B. (2024). English speaking with artificial intelligence (AI): The roles of enjoyment, willingness to communicate with AI, and innovativeness. Computers in Human Behavior, 159, 108355. https://doi.org/10.1016/j.chb.2024.108355
Imran, M., & Almusharraf, N. (2024). Google Gemini as a next generation AI educational tool: a review of emerging educational technology. Smart Learning Environments, 11(1), 22. https://doi.org/10.1186/s40561-024-00310-z
Jiang, L., Yang, S., Tang, Q., & Zhang, Z. (2024). Determinants of continuous usage intention of branded apps in omni-channel retail environment: comparison between experience-oriented and transaction-oriented apps. Data Science and Management, 7(3), 197–205. https://doi.org/10.1016/j.dsm.2024.01.004
Joseph, T. S., Gowrie, S., Montalbano, M. J., Bandelow, S., Clunes, M., Dumont, A. S., Iwanaga, J., Tubbs, R. S., & Loukas, M. (2025). The Roles of Artificial Intelligence in Teaching Anatomy: A Systematic Review. Clinical Anatomy, 38(5), 552–567. https://doi.org/10.1002/ca.24272
Jung, Y. M., & Jo, H. (2025). Understanding Continuance Intention of Generative AI in Education: An ECM-Based Study for Sustainable Learning Engagement. Sustainability, 17(13), 6082. https://doi.org/10.3390/su17136082
Krishnanraw, J., & Kamisah, I. (2025). Behavioral Intention to Use Artificial Intelligence (AI) Among Accounting Students: Evaluating the Effect of Job Relevance. Gadjah Mada International Journal of Business, 27(3), 269. https://doi.org/10.22146/gamaijb.110620
Li, K. (2023). Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model. Sustainability, 15(6), 5221. https://doi.org/10.3390/su15065221
Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhao, L., Zhu, D., Li, X., Qiang, N., Shen, D., Liu, T., & Ge, B. (2023). Summary of ChatGPT-Related research and perspective towards the future of large language models. Meta-Radiology, 1(2), 100017. https://doi.org/10.1016/j.metrad.2023.100017
Ma, T. (2025). Systematically visualizing ChatGPT used in higher education: Publication trend, disciplinary domains, research themes, adoption and acceptance. Computers and Education: Artificial Intelligence, 8, 100336. https://doi.org/10.1016/j.caeai.2024.100336
Matos, T., Santos, W., Zdravevski, E., Coelho, P. J., Pires, I. M., & Madeira, F. (2025). A systematic review of artificial intelligence applications in education: Emerging trends and challenges. Decision Analytics Journal, 15, 100571. https://doi.org/10.1016/j.dajour.2025.100571
Mohd Rahim, N. I., A. Iahad, N., Yusof, A. F., & A. Al-Sharafi, M. (2022). AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach. Sustainability, 14(19), 12726. https://doi.org/10.3390/su141912726
Ode, E., Nana, R., Boro, I. O., & Ikyanyon, D. N. (2025). A cross-country analysis of self-determination and continuance use intention of AI tools in business education: Does instructor support matter? Computers and Education: Artificial Intelligence, 8, 100402. https://doi.org/10.1016/j.caeai.2025.100402
Polyportis, A. (2024). A longitudinal study on artificial intelligence adoption: understanding the drivers of ChatGPT usage behavior change in higher education. Frontiers in Artificial Intelligence, 6. https://doi.org/10.3389/frai.2023.1324398
Polyportis, A., & Pahos, N. (2025). Understanding students’ adoption of the ChatGPT chatbot in higher education: the role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 44(2), 315–336. https://doi.org/10.1080/0144929X.2024.2317364
Rashid, S. (2025). Habit Predicting Higher Education EFL Students’ Intention and Use of AI: A Nexus of UTAUT-2 Model and Metacognition Theory. Education Sciences, 15(6), 756. https://doi.org/10.3390/educsci15060756
Russell, S., & Norvig, P. (1995). A modern, agent-oriented approach to introductory artificial intelligence. ACM SIGART Bulletin, 6(2), 24–26. https://doi.org/10.1145/201977.201989
Sadewo, S. T., Ratnawati, S., Giovanni, A., & Widayanti, I. (2025). The Influence of Personal Innovativeness on ChatGPT Continuance Usage Intention among Students. SATESI: Jurnal Sains Teknologi Dan Sistem Informasi, 5(1), 88–98. https://doi.org/10.54259/satesi.v5i1.4117
Sari, P. K., Ramadan, F., & Murti, Y. R. (2024). Examining Students’ Motivation to Continue Using AI-Chatbot for Academic Assignment. Jurnal Sistem Informasi, 20(2), 18–31. https://doi.org/10.21609/jsi.v20i2.1417
Saxena, A., & Doleck, T. (2023). A structural model of student continuance intentions in ChatGPT adoption. Eurasia Journal of Mathematics, Science and Technology Education, 19(12), em2366. https://doi.org/10.29333/ejmste/13839
Sun, P., Li, L., Hossain, M. S., & Zabin, S. (2025). Investigating students’ behavioral intention to use ChatGPT for educational purposes. Sustainable Futures, 9, 100531. https://doi.org/10.1016/j.sftr.2025.100531
Tan, C. N.-L., Tee, M., & Koay, K. Y. (2024). Discovering students’ continuous intentions to use ChatGPT in higher education: a tale of two theories. Asian Education and Development Studies, 13(4), 356–372. https://doi.org/10.1108/AEDS-04-2024-0096
Thuy An Ngo, T., Khuong An, G., Thy Nguyen, P., & Tu Tran, T. (2024). Unlocking Educational Potential: Exploring Students’ Satisfaction and Sustainable Engagement with ChatGPT Using the ECM Model. Journal of Information Technology Education: Research, 23, 021. https://doi.org/10.28945/5344
Tiwari, C. K., Bhat, M. A., Khan, S. T., Subramaniam, R., & Khan, M. A. I. (2023). What drives students toward ChatGPT? An investigation of the factors influencing adoption and usage of ChatGPT. Interactive Technology and Smart Education, 21(3), 333–355. https://doi.org/10.1108/ITSE-04-2023-0061
Veronika, S., Lee, M. S. W., Lang, B., & Putra, P. (2025). A systematic review and future agenda on continuance intentions in mobile apps. International Journal of Information Management Data Insights, 5(2), 100352. https://doi.org/10.1016/j.jjimei.2025.100352
Wang, L., & Li, W. (2024). The Impact of AI Usage on University Students’ Willingness for Autonomous Learning. Behavioral Sciences, 14(10), 956. https://doi.org/10.3390/bs14100956
Wang, P., Jing, Y., & Shen, S. (2025). A systematic literature review on the application of generative artificial intelligence (GAI) in teaching within higher education: Instructional contexts, process, and strategies. The Internet and Higher Education, 65, 100996. https://doi.org/10.1016/j.iheduc.2025.100996
Wu, Q., Li, S., Xin, S., Hou, Q., & Li, P. (2025). A study on students’ behavioural intention and use behaviour of artificial intelligence-generated content in physical education: Employing an extended the unified theory of acceptance and use of technology model. Journal of Hospitality, Leisure, Sport & Tourism Education, 36, 100547. https://doi.org/10.1016/j.jhlste.2025.100547
Wu, Q., Tian, J., & Liu, Z. (2025). Exploring the usage behavior of generative artificial intelligence: a case study of ChatGPT with insights into the moderating effects of habit and personal innovativeness. Current Psychology, 44(9), 8190–8203. https://doi.org/10.1007/s12144-024-07193-w
Yang, X., Ding, J., Biao, W., Zhang, S., & Yana, W. (2025). Design strategies for artificial intelligence based future learning centers in medical universities. BMC Medical Education, 25. https://doi.org/10.1186/s12909-025-06640-x
Yu, C., Yan, J., & Cai, N. (2024). ChatGPT in higher education: factors influencing ChatGPT user satisfaction and continued use intention. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1354929
Yu, G., Ramayah, T., & Lin, Z. (2025). Toward understanding the role of generative AI in entrepreneurship education: A systematic review. Computers and Education: Artificial Intelligence, 9, 100470. https://doi.org/10.1016/j.caeai.2025.100470
Zeng, J., & Li, X. (2024). Modeling the Continuous Intention to Use Generative AI as an Educational Tool for EFL Learners among Vocational College Students in Guangzhou, China. Journal of Innovation and Development, 8(2), 18–27. https://doi.org/10.54097/d1c3my56
Zhang, J. (2024). A Study of Undergraduates’ Behavioral Intention to Use Generative AI Tools—Ernie Bot as An Example. Highlights in Business, Economics and Management, 41, 269–276. https://doi.org/10.54097/9xw63p10
Zhou, G., & Ma, Q. (2025). Understanding user stickiness in GAI-IDLE platforms: Insights from self-determination theory. Learning and Motivation, 92, 102179. https://doi.org/10.1016/j.lmot.2025.102179
Zhou, J., & Zhang, H. (2024). Factors Influencing University Students’ Continuance Intentions towards Self-Directed Learning Using Artificial Intelligence Tools: Insights from Structural Equation Modeling and Fuzzy-Set Qualitative Comparative Analysis. Applied Sciences, 14(18), 8363. https://doi.org/10.3390/app14188363
Al-Dokhny, A., Alismaiel, O., Youssif, S., Nasr, N., Drwish, A., & Samir, A. (2024). Can Multimodal Large Language Models Enhance Performance Benefits Among Higher Education Students? An Investigation Based on the Task–Technology Fit Theory and the Artificial Intelligence Device Use Acceptance Model. Sustainability, 16(23), 10780. https://doi.org/10.3390/su162310780
Alam, S. M. A. (2024). Exploring Public University Undergraduate Students’ Experiencing Intention to Use ChatGPT in Academic Purpose: Application of TAM Theory. Journal of Information Systems and Informatics, 6(3), 1413–1434. https://doi.org/10.51519/journalisi.v6i3.789
Alarifi, S. (2025). A Study of the Key Drivers Behind University Students’ Intention to Use and Usage of Generative AI in Academia: Evidence from ChatGPT Use in Saudi Arabia. International Journal of Business and Applied Social Science, 11(8), 1–8. https://doi.org/10.33642/ijbass.v11n8p1
Annamalai, N., Bervell, B., Mireku, D. O., & Andoh, R. P. K. (2025). Artificial intelligence in higher education: Modelling students’ motivation for continuous use of ChatGPT based on a modified self-determination theory. Computers and Education: Artificial Intelligence, 8, 100346. https://doi.org/10.1016/j.caeai.2024.100346
Chen, B., Zhu, X., & Díaz del Castillo H., F. (2023). Integrating generative AI in knowledge building. Computers and Education: Artificial Intelligence, 5, 100184. https://doi.org/10.1016/j.caeai.2023.100184
Chuan, Z., Jianming, O., Xin, Z., Tao, P., Yan, Z., Chunyao, X., Hongxia, T., Qingqi, C., & Kai, L. (2025). Conducting educational intervention research in general practice: From design to publication. Chinese General Practice Journal, 2(3), 100073. https://doi.org/10.1016/j.cgpj.2025.100073
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10039-y
Du, K. (2024). Chinese Students’ Continued Intention to Use Liulishuo App to Learn English Speaking Skills in Non-mandatory Environment: A Case in a Chinese University. International Journal of Information and Education Technology, 14(5), 681–689. https://doi.org/10.18178/ijiet.2024.14.5.2093
Duong, C. D. (2024). Modeling the determinants of HEI students’ continuance intention to use ChatGPT for learning: a stimulus–organism–response approach. Journal of Research in Innovative Teaching & Learning, 17(2), 391–407. https://doi.org/10.1108/JRIT-01-2024-0006
Eedelouei, S. (2026). Factors influencing language teachers’ judgements and decision-making about the use of generative AI tools: A systematic review. Teaching and Teacher Education, 171, 105333. https://doi.org/10.1016/j.tate.2025.105333
Esiyok, E., Gokcearslan, S., & Kucukergin, K. G. (2025). Acceptance of Educational Use of AI Chatbots in the Context of Self-Directed Learning with Technology and ICT Self-Efficacy of Undergraduate Students. International Journal of Human–Computer Interaction, 41(1), 641–650. https://doi.org/10.1080/10447318.2024.2303557
Huang, F., & Zou, B. (2024). English speaking with artificial intelligence (AI): The roles of enjoyment, willingness to communicate with AI, and innovativeness. Computers in Human Behavior, 159, 108355. https://doi.org/10.1016/j.chb.2024.108355
Imran, M., & Almusharraf, N. (2024). Google Gemini as a next generation AI educational tool: a review of emerging educational technology. Smart Learning Environments, 11(1), 22. https://doi.org/10.1186/s40561-024-00310-z
Jiang, L., Yang, S., Tang, Q., & Zhang, Z. (2024). Determinants of continuous usage intention of branded apps in omni-channel retail environment: comparison between experience-oriented and transaction-oriented apps. Data Science and Management, 7(3), 197–205. https://doi.org/10.1016/j.dsm.2024.01.004
Joseph, T. S., Gowrie, S., Montalbano, M. J., Bandelow, S., Clunes, M., Dumont, A. S., Iwanaga, J., Tubbs, R. S., & Loukas, M. (2025). The Roles of Artificial Intelligence in Teaching Anatomy: A Systematic Review. Clinical Anatomy, 38(5), 552–567. https://doi.org/10.1002/ca.24272
Jung, Y. M., & Jo, H. (2025). Understanding Continuance Intention of Generative AI in Education: An ECM-Based Study for Sustainable Learning Engagement. Sustainability, 17(13), 6082. https://doi.org/10.3390/su17136082
Krishnanraw, J., & Kamisah, I. (2025). Behavioral Intention to Use Artificial Intelligence (AI) Among Accounting Students: Evaluating the Effect of Job Relevance. Gadjah Mada International Journal of Business, 27(3), 269. https://doi.org/10.22146/gamaijb.110620
Li, K. (2023). Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model. Sustainability, 15(6), 5221. https://doi.org/10.3390/su15065221
Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhao, L., Zhu, D., Li, X., Qiang, N., Shen, D., Liu, T., & Ge, B. (2023). Summary of ChatGPT-Related research and perspective towards the future of large language models. Meta-Radiology, 1(2), 100017. https://doi.org/10.1016/j.metrad.2023.100017
Ma, T. (2025). Systematically visualizing ChatGPT used in higher education: Publication trend, disciplinary domains, research themes, adoption and acceptance. Computers and Education: Artificial Intelligence, 8, 100336. https://doi.org/10.1016/j.caeai.2024.100336
Matos, T., Santos, W., Zdravevski, E., Coelho, P. J., Pires, I. M., & Madeira, F. (2025). A systematic review of artificial intelligence applications in education: Emerging trends and challenges. Decision Analytics Journal, 15, 100571. https://doi.org/10.1016/j.dajour.2025.100571
Mohd Rahim, N. I., A. Iahad, N., Yusof, A. F., & A. Al-Sharafi, M. (2022). AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach. Sustainability, 14(19), 12726. https://doi.org/10.3390/su141912726
Ode, E., Nana, R., Boro, I. O., & Ikyanyon, D. N. (2025). A cross-country analysis of self-determination and continuance use intention of AI tools in business education: Does instructor support matter? Computers and Education: Artificial Intelligence, 8, 100402. https://doi.org/10.1016/j.caeai.2025.100402
Polyportis, A. (2024). A longitudinal study on artificial intelligence adoption: understanding the drivers of ChatGPT usage behavior change in higher education. Frontiers in Artificial Intelligence, 6. https://doi.org/10.3389/frai.2023.1324398
Polyportis, A., & Pahos, N. (2025). Understanding students’ adoption of the ChatGPT chatbot in higher education: the role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 44(2), 315–336. https://doi.org/10.1080/0144929X.2024.2317364
Rashid, S. (2025). Habit Predicting Higher Education EFL Students’ Intention and Use of AI: A Nexus of UTAUT-2 Model and Metacognition Theory. Education Sciences, 15(6), 756. https://doi.org/10.3390/educsci15060756
Russell, S., & Norvig, P. (1995). A modern, agent-oriented approach to introductory artificial intelligence. ACM SIGART Bulletin, 6(2), 24–26. https://doi.org/10.1145/201977.201989
Sadewo, S. T., Ratnawati, S., Giovanni, A., & Widayanti, I. (2025). The Influence of Personal Innovativeness on ChatGPT Continuance Usage Intention among Students. SATESI: Jurnal Sains Teknologi Dan Sistem Informasi, 5(1), 88–98. https://doi.org/10.54259/satesi.v5i1.4117
Sari, P. K., Ramadan, F., & Murti, Y. R. (2024). Examining Students’ Motivation to Continue Using AI-Chatbot for Academic Assignment. Jurnal Sistem Informasi, 20(2), 18–31. https://doi.org/10.21609/jsi.v20i2.1417
Saxena, A., & Doleck, T. (2023). A structural model of student continuance intentions in ChatGPT adoption. Eurasia Journal of Mathematics, Science and Technology Education, 19(12), em2366. https://doi.org/10.29333/ejmste/13839
Sun, P., Li, L., Hossain, M. S., & Zabin, S. (2025). Investigating students’ behavioral intention to use ChatGPT for educational purposes. Sustainable Futures, 9, 100531. https://doi.org/10.1016/j.sftr.2025.100531
Tan, C. N.-L., Tee, M., & Koay, K. Y. (2024). Discovering students’ continuous intentions to use ChatGPT in higher education: a tale of two theories. Asian Education and Development Studies, 13(4), 356–372. https://doi.org/10.1108/AEDS-04-2024-0096
Thuy An Ngo, T., Khuong An, G., Thy Nguyen, P., & Tu Tran, T. (2024). Unlocking Educational Potential: Exploring Students’ Satisfaction and Sustainable Engagement with ChatGPT Using the ECM Model. Journal of Information Technology Education: Research, 23, 021. https://doi.org/10.28945/5344
Tiwari, C. K., Bhat, M. A., Khan, S. T., Subramaniam, R., & Khan, M. A. I. (2023). What drives students toward ChatGPT? An investigation of the factors influencing adoption and usage of ChatGPT. Interactive Technology and Smart Education, 21(3), 333–355. https://doi.org/10.1108/ITSE-04-2023-0061
Veronika, S., Lee, M. S. W., Lang, B., & Putra, P. (2025). A systematic review and future agenda on continuance intentions in mobile apps. International Journal of Information Management Data Insights, 5(2), 100352. https://doi.org/10.1016/j.jjimei.2025.100352
Wang, L., & Li, W. (2024). The Impact of AI Usage on University Students’ Willingness for Autonomous Learning. Behavioral Sciences, 14(10), 956. https://doi.org/10.3390/bs14100956
Wang, P., Jing, Y., & Shen, S. (2025). A systematic literature review on the application of generative artificial intelligence (GAI) in teaching within higher education: Instructional contexts, process, and strategies. The Internet and Higher Education, 65, 100996. https://doi.org/10.1016/j.iheduc.2025.100996
Wu, Q., Li, S., Xin, S., Hou, Q., & Li, P. (2025). A study on students’ behavioural intention and use behaviour of artificial intelligence-generated content in physical education: Employing an extended the unified theory of acceptance and use of technology model. Journal of Hospitality, Leisure, Sport & Tourism Education, 36, 100547. https://doi.org/10.1016/j.jhlste.2025.100547
Wu, Q., Tian, J., & Liu, Z. (2025). Exploring the usage behavior of generative artificial intelligence: a case study of ChatGPT with insights into the moderating effects of habit and personal innovativeness. Current Psychology, 44(9), 8190–8203. https://doi.org/10.1007/s12144-024-07193-w
Yang, X., Ding, J., Biao, W., Zhang, S., & Yana, W. (2025). Design strategies for artificial intelligence based future learning centers in medical universities. BMC Medical Education, 25. https://doi.org/10.1186/s12909-025-06640-x
Yu, C., Yan, J., & Cai, N. (2024). ChatGPT in higher education: factors influencing ChatGPT user satisfaction and continued use intention. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1354929
Yu, G., Ramayah, T., & Lin, Z. (2025). Toward understanding the role of generative AI in entrepreneurship education: A systematic review. Computers and Education: Artificial Intelligence, 9, 100470. https://doi.org/10.1016/j.caeai.2025.100470
Zeng, J., & Li, X. (2024). Modeling the Continuous Intention to Use Generative AI as an Educational Tool for EFL Learners among Vocational College Students in Guangzhou, China. Journal of Innovation and Development, 8(2), 18–27. https://doi.org/10.54097/d1c3my56
Zhang, J. (2024). A Study of Undergraduates’ Behavioral Intention to Use Generative AI Tools—Ernie Bot as An Example. Highlights in Business, Economics and Management, 41, 269–276. https://doi.org/10.54097/9xw63p10
Zhou, G., & Ma, Q. (2025). Understanding user stickiness in GAI-IDLE platforms: Insights from self-determination theory. Learning and Motivation, 92, 102179. https://doi.org/10.1016/j.lmot.2025.102179
Zhou, J., & Zhang, H. (2024). Factors Influencing University Students’ Continuance Intentions towards Self-Directed Learning Using Artificial Intelligence Tools: Insights from Structural Equation Modeling and Fuzzy-Set Qualitative Comparative Analysis. Applied Sciences, 14(18), 8363. https://doi.org/10.3390/app14188363
