The Role of AI Personalization in Shaping Students’ Decision-making: The Mediating Role of Students’ Intentions and the Moderating Effect of Academic Technology Experience in Higher Education

Abendan, C. F., Kilag, O. K., Uy, F., & Vestal, P. (2023). Transforming learning in the digital age: The confluence of innovation and education. Excellencia: International Multi-disciplinary Journal of Education, 1 (5), 1-13.
Adeyemi, A. M., & Adeyemi, S. B. (2014). Institutional Factors as Predictors of Students’ Academic Achievement in College of Education in South Western Nigeria. International Journal of Educational Administration and Policy Studies, 6 (8), 141-153.
Aithal, P. S., & Maiya, A. K. (2023). Innovations in higher education industry-shaping the future. International Journal of Case Studies in Business, IT, and Education (IJCSBE), 7 (4), 283-311.
Aithal, P. S., Prabhu, S., & Aithal, S. (2024). Future of higher education through technology prediction and forecasting. Poornaprajna International Journal of Management, Education, and Social Science (PIJMESS), 1 (1), 1-50.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179-211.
Akinrinola, O., Okoye, C. C., Ofodile, O. C., & Ugochukwu, C. E. (2024). Navigating and reviewing ethical dilemmas in AI development: Strategies for transparency, fairness, and accountability. GSC Advanced Research and Reviews, 18 (3), 50-58. 
AlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). Chatgpt as an educational tool: Opportunities, challenges, and recommendations for communication, business writing, and Composition courses. Journal of Artificial Intelligence and Technology, 3 (2), 60-68.
Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52 (3), 322-352.
Angelen, J., & Siddik, M. M. (2023). Role of Artificial Intelligence (AI) in marketing. Journal of Survey in Fisheries Sciences, 10 (3S), 6540-6549.
Anurogo, D., La Ramba, H., Putri, N. D., & Putri, U. M. P. (2023). Digital literacy 5.0 to enhance multicultural education. Multicultural Islamic Education Review, 1 (2), 109-179.
Anwar, M., & Herayono, A. (2024). The effect of Theory of Planned Behavior (TBP) and creativity-based industry perception on digital entrepreneurship: An innovativeness as mediator. PaperASIA, 40 (3b), 96-105. 
Ashraf, S., Beinborn, M., Chikoti, C., Gezer, D., Kaliu, T. A., Kumar, K., & Posset, K. R. (2024). Youth shaping the future of science, technology, and education at AI for good. Financing Sustainable Development: Challenges and the Way Forward, 3 , 73-101.
Ayeni, O. O., Al Hamad, N. M., Chisom, O. N., Osawaru, B., & Adewusi, O. E. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18 (2), 261-271.
Bhuiyan, M. S. (2024). The role of AI-enhanced personalization in customer experiences. Journal of Computer Science and Technology Studies, 6 (1), 162-169.
Bulchand-Gidumal, J., William Secin, E., O’Connor, P., & Buhalis, D. (2024). Artificial intelligence’s impact on hospitality and tourism marketing: exploring key themes and addressing challenges. Current Issues in Tourism, 27 (14), 2345-2362.
Chan-Olmsted, S., Chen, H., & Kim, H. J. (2024). In smartness we trust: Consumer experience, smart device personalization and privacy balance. Journal of Consumer Marketing, 41 (6), 597-609. 
Chinnadurai, J., Karthik, A., Ramesh, J. V. N., Banerjee, S., Rajlakshmi, P. V., Rao, K. V., & Rajaram, A. (2024). Enhancing online education recommendations through clustering-driven deep learning. Biomedical Signal Processing and Control, 97 , 106669.
Cho, S. A., & Jeon, Y. J. J. (2023). The decision-making process regarding the continuance intention of using branded apps: an integrated approach to the PAM and the TPB. International Journal of Contemporary Hospitality Management, 35 (12), 4158-4176.
Cingillioglu, I. (2024). What impacts matriculation decisions? A double-blind experiment via an AI-led chatbot trained with social media data (Doctoral Dissertation). The University of Sydney Business School, 1-254
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates, Routledge, 1-567
du Plooy, E., Casteleijn, D., & Franzsen, D. (2024). Personalized adaptive learning in higher education: A scoping review of key characteristics and impact on academic performance and engagement. Heliyon, 1-24.
Dudekula, K. V., Syed, H., Basha, M. I. M., Swamykan, S. I., Kasaraneni, P. P., Kumar, Y. V. P., & Azar, A. T. (2023). Convolutional neural network-based personalized program recommendation system for smart television users. Sustainability, 15 (3), 1-18.
Ellikkal, A., & Rajamohan, S. (2024). AI-enabled personalized learning: empowering management students for improving engagement and academic performance. Vilakshan-XIMB Journal of Management, 1-17.
Fanani, A., & Syafrudin, T. (2024). Persuasive promotions: leveraging location proximity in college selection strategies for prospective students. Indonesian Journal of Advanced Research, 3 (4), 455-468.
Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18 (3), 233-239. 
George, B., & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13 (9), 1-20.
Hamad, F., Shehata, A., & Al Hosni, N. (2024). Predictors of blended learning adoption in higher education institutions in Oman: theory of planned behavior. International Journal of Educational Technology in Higher Education, 21 (1), 1-28.
Hanaysha, J. R., Shriedeh, F. B., & In’airat, M. (2023). Impact of classroom environment, teacher competency, information and communication technology resources, and university facilities on student engagement and academic performance. International Journal of Information Management Data Insights, 3 (2), 1-12.
Hart, P. F., & Rodgers, W. (2024). Competition, competitiveness, and competitive advantage in higher education institutions: a systematic literature review. Studies in Higher Education, 49 (11), 2153-2177.
Hayes, A. F. (2022). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-based Approach, (3rd ed.). The Guilford Press, 3-732
Holmström, E., & Larsson, A. (2024). From data to loyalty: A quantitative study of consumer’s response to AI-driven personalized marketing, Jönköping International Business School, 1-78
Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024). Leveraging artificial intelligence for personalized marketing campaigns to improve conversion rates. International Journal of Engineering Research and Development, 20 (8), 253-270.
Kaswan, K. S., Dhatterwal, J. S., & Ojha, R. P. (2024). AI in personalized learning. In: Advances in Technological Innovations in Higher, CRC Press, 103-117.
Kedi, W. E., Ejimuda, C., Idemudia, C., & Ijomah, T. I. (2024). AI software for personalized marketing automation in SMEs: Enhancing customer experience and sales. World Journal of Advanced Research and Reviews, 23 (1), 1981-1990.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44 (2), 544-564.
Kivinen, L. K. (2023). AI-driven chatbot as a support tool for developers during the onboarding process, Haaga-Helia University of Applied Science, 1-80.
Lee, J. C., & Xiong, L. (2023). Exploring learners’ continuous usage decisions regarding mobile-assisted language learning applications: A social support theory perspective. Education and Information Technologies, 28 (12), 16743-16769.
Liao, X., Zhao, X., Wang, Z., Zhao, Z., Han, K., Gupta, R., & Wu, G. (2023). Driver digital twin for online prediction of personalized lane-change behavior. IEEE Internet of Things Journal, 10 (15), 13235-13246.
Liu, B., & Cheng, H. (2022, January). A stratified sampling method for teaching evaluation of curriculum ideological and political for higher education. In: 2022 3rd International Conference on Education, Knowledge and Information Management (ICEKIM), 115-119.
Mainstay. (2024). Georgia State University chatbot supports every student with personalized text messaging. https://mainstay.com/case-study/how-georgia-state-university-supports-every-student-with-personalized-text-messaging/
Majjate, H., Bellarhmouch, Y., Jeghal, A., Yahyaouy, A., Tairi, H., & Zidani, K. A. (2023). AI-powered academic guidance and counseling system based on student profile and interests. Applied System Innovation, 7(1), 1-17.
Martins, R. M., & Gresse von Wangenheim, C. (2024). Teaching computing to middle and high school students from a low socio-economic status background: a systematic literature Review. Informatics in Education, 23 (1), 179-222.
McGuinness, C., & Fulton, C. (2019). Digital literacy in higher education: a case study of student engagement with e-tutorials using blended learning. Journal of Information Technology Education: Innovations in Practice, 18, 1-28.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. International Journal of Human-Computer Studies, 58 (6), 871-900. 
Mintii, I., & Semerikov, S. (2024, May). Optimizing teacher training and retraining for the age of AI-powered personalized learning: a bibliometric analysis. In: International Scientific-Practical Conference ”Information Technology for Education, Science and Technics”, 339-357.
Modi, T. B. (2023). Artificial intelligence ethics and fairness: A study to address bias and fairness issues in ai systems, and the ethical implications of AI applications. Revista Review Index Journal of Multidisciplinary, 3 (2), 24-35.
Naamati-Schneider, L., & Alt, D. (2024). Beyond digital literacy: the era of AI-powered assistants and evolving user skills. Education and Information Technologies, 29, 1-31.
Naqvi, G., Subhani, W., Rana, N., & Ahmad, M. (2023). Understanding AI behavior: learning and decision making in artificial intelligence. Statistics, Computing and Interdisciplinary Research, 5 (1), 15-28.
Newell, B. R., & Shanks, D. R. (2014). Unconscious influences on decision making: A critical review. Behavioral and brain sciences, 37 (1), 1-19.
Obeagu, E. I., & Obeagu, G. U. (2024). Culturally tailored education: a key to adolescent sickle cell disease prevention. Elite Journal of Public Health, 2 (3), 52-62.
Ofosu-Ampong, K. (2023). Gender differences in perception of artificial intelligence-based tools. Journal of Digital Art & Humanities, 4 (2), 52-56.
Olabiyi, W. (2025). Bridging the digital divide: strategies for enhancing e-learning accessibility for underprivileged students at open Libyan university. Information, 16 (1), 1-28.
Patel, K. (2024). Ethical reflections on data-centric AI: balancing benefits and risks. International Journal of Artificial Intelligence Research and Development, 2 (1), 1-17.
Purcărea, I. M. (2023). The importance of digital marketing for higher education in improving the educational value chain. Journal of Information Systems & Operations Management, 17 (2), 176-235.
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). E-commerce and consumer behavior: A review of AI-powered personalization and market trends. GSC Advanced Research and Reviews, 18 (3), 66-77.
Reddy, V. M., & Nalla, L. N. (2024). Personalization in e-commerce marketing: leveraging big data for tailored consumer engagement. Revista de Inteligencia Artificial en Medicina, 15 (1), 691-725.
Saaida, M. B. (2023). AI-driven transformations in higher education: opportunities and challenges. International Journal of Educational Research and Studies, 5(1), 29-36.
Serrano, J. (2023). Bridging educational frontiers: AI-adaptive learning, subscription strategies, and the quest for global online MBA accessibility, University of Vaasa School of Management, 2-109.
Song, C., Shin, S. Y., & Shin, K. S. (2024). Implementing the dynamic feedback-driven learning optimization framework: a machine learning approach to personalize educational pathways. Applied Sciences, 14 (2), 1-22.
Soutar, G. N., & Turner, J. P. (2002). Students’ preferences for university: A conjoint analysis. International journal of educational management, 16 (1), 40-45.
Tsai, W. H. S., & Men, L. R. (2017). The influence of social media on consumer engagement and purchase intention: The moderating role of social media content. Journal of Business Research, 78, 134-141. 
Wang, C., Wang, H., Li, Y., Dai, J., Gu, X., & Yu, T. (2024). Factors influencing university students’ behavioral intention to use generative artificial intelligence: Integrating the theory of planned behavior and AI literacy. International Journal of Human-Computer Interaction, 1-23.
Wang, Z., Yuan, R., Luo, J., Liu, M. J., & Yannopoulou, N. (2023). Does personalized advertising have their best interests at heart? A quantitative study of narcissists’ SNS use among Generation Z consumers. Journal of Business Research, 165 , 1-15.
Wu, W., Huang, Y., & Qian, L. (2024). Social trust and algorithmic equity: the societal perspectives of users’ intention to interact with algorithm recommendation systems. Decision Support Systems, 178 , 114115.
Yang, C. C., & Ogata, H. (2023). Personalized learning analytics intervention approach for enhancing student learning achievement and behavioral engagement in blended learning. Education and Information Technologies, 28 (3), 2509-2528.
Zanker, M., Rook, L., & Jannach, D. (2019). Measuring the impact of online personalisation: Past, present and future. International Journal of Human-Computer Studies, 131, 160-168.
Zhang, J., & Zhang, Z. (2024). AI in teacher education: unlocking new dimensions in teaching support, inclusive learning, and digital literacy. Journal of Computer Assisted Learning, 40 (4), 1871-1885.
Zitha, I., Mokganya, G., & Sinthumule, O. (2023). Innovative strategies for fostering student engagement and collaborative learning among extended curriculum programme students. Education Sciences, 13 (12), 2-15.