Conditional Acceptance of AI-Assisted Gamified Learning among Senior High School and Higher Education Students: The Roles of Learning Value, Engagement, and Responsible-Use Safeguards
##doi.readerDisplayName##:
https://doi.org/10.65166/g5h1et20关键词:
artificial intelligence, gamified learning, student acceptance, learning engagement, responsible AI, educational technology摘要
Artificial intelligence-assisted gamified learning combines generative AI functions with game-based instructional elements to support explanation, practice, feedback, and student participation. However, student acceptance may depend not only on prior exposure but also on perceived educational value, engagement, and confidence in responsible-use safeguards. This study examined the factors associated with the acceptance of AI-assisted gamified learning among 136 students in the Philippines, comprising 91 higher education students and 45 senior high school students. A cross-sectional analytical survey design was used. Data were analyzed using descriptive statistics, Cronbach's alpha, Welch's independent-samples t tests, Pearson correlation, hierarchical multiple regression with HC3 robust standard errors, sensitivity analysis, and supplementary content analysis of open-ended responses. Students reported generally favorable perceptions of exposure, learning value, safeguards, and acceptability, while motivation and engagement were rated at a moderate level. Higher education students reported significantly greater acceptability than senior high school students. Acceptability was strongly associated with perceived learning value and motivation and engagement and was moderately associated with responsible-use safeguards. In the final regression model, learning value, motivation and engagement, and safeguards remained statistically significant factors associated with acceptability, whereas prior exposure did not. Open-ended responses emphasized concerns regarding overdependence, weakened critical thinking, competition, accuracy, privacy, teacher guidance, and unequal access. The findings indicate that student acceptance is conditional on pedagogical usefulness, meaningful engagement, teacher mediation, transparency, privacy protection, academic-integrity safeguards, and equitable access.
##plugins.themes.default.displayStats.downloads##
参考
Atento, R. G. (2025). Exploring E-Learning for Sustainable Development: Integrating SDGs in Management Education at Philippine Higher Education Institutions. International Journal of Health & Business Analytics, 1(1). https://doi.org/10.65166/2qcjx561
Bendal, A., Sabasa, S. A., Espelita, C. A. M. H., & Atento, R. G. O. (2026). Artificial intelligence as disruptive technology in accounting: A qualitative study of practitioner perceptions on automation, judgment, and decision support. Journal of Enterprise Strategy & Management Innovation, 1(1). https://doi.org/10.65166/0sdayg70
Bermido, C. M., Quinto, L. F., & Atento, R. G. O. (2025). A qualitative thematic review of contemporary challenges affecting health professions education: Implications for higher education leadership. International Journal of Health and Business Analytics, 1(2). https://doi.org/10.65166/yfm5w791
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43. https://doi.org/10.1186/s41239-023-00411-8
Dancel, M. R., España, G. B., Asnar, D. A., Batol, C. Y., & Atento, R. G. (2026). Introversion and passive social media engagement among generation Z college students: A descriptive-correlational study. International Journal of Behavioral and Social Analytics, 1(1). https://doi.org/10.65166/d56jma06
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268. https://doi.org/10.1207/S15327965PLI1104_01
Delcker, J., Heil, J., Ifenthaler, D., Seufert, S., & Spirgi, L. (2024). First-year students' AI-competence as a predictor for intended and de facto use of AI-tools for supporting learning processes in higher education. International Journal of Educational Technology in Higher Education, 21, Article 18. https://doi.org/10.1186/s41239-024-00452-7
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining "gamification." In Proceedings of the 15th International Academic MindTrek Conference: Envisioning future media environments (pp. 9-15). Association for Computing Machinery. https://doi.org/10.1145/2181037.2181040
Dichev, C., & Dicheva, D. (2017). Gamifying education: What is known, what is believed and what remains uncertain: A critical review. International Journal of Educational Technology in Higher Education, 14, Article 9. https://doi.org/10.1186/s41239-017-0042-5
Espelita, C. A. M. H., Atento, A. G. B., & Atento, R. G. O. (2026). Social media marketing and enrollment intent among college-bound learners: Evidence from a private higher education institution in Region IV-A, Philippines. Journal of Enterprise Strategy & Management Innovation, 1(1). https://doi.org/10.65166/bcn4pt87
Fabro, R. B. B., Rivera, J. C., Sambrano, L. C., Dinoy, L. J. M., Alcozer, N. G., & Agustin, M. C. (2024). Perceptions and extent of utilization of generative artificial intelligence (AI) among Filipino students. International Journal of Education and Research, 12(7), 107-126.
Lolong, J. R. V., Aparejado, A. S. S., Carino, S. Y. M., Valderama, M. L., & Atento, R. G. (2026). Dark triad personality traits and academic dishonesty-related tendencies among senior high school students: A correlational study. International Journal of Behavioral and Social Analytics, 1(1). https://doi.org/10.65166/2xe1ga71
Rao, L., Tian, Y., & Atento, R. G. O. (2025). Adoption and perceived effectiveness of AI in education: Personalization, outcomes, and equity. International Journal of Health & Business Analytics, 1(1). https://doi.org/10.65166/qgq89291
Romero-Rodríguez, J.-M., Ramírez-Montoya, M.-S., Buenestado-Fernández, M., & Lara-Lara, F. (2023). Use of ChatGPT at university as a tool for complex thinking: Students' perceived usefulness. Journal of New Approaches in Educational Research, 12(2), 323-339. https://doi.org/10.7821/naer.2023.7.1458
Sailer, M., & Homner, L. (2020). The gamification of learning: A meta-analysis. Educational Psychology Review, 32, 77-112. https://doi.org/10.1007/s10648-019-09498-w
Shahzad, M. F., Xu, S., & Javed, I. (2024). ChatGPT awareness, acceptance, and adoption in higher education: The role of trust as a cornerstone. International Journal of Educational Technology in Higher Education, 21, Article 46. https://doi.org/10.1186/s41239-024-00478-x
Strzelecki, A. (2024). Students' acceptance of ChatGPT in higher education: An extended unified theory of acceptance and use of technology. Innovative Higher Education, 49(2), 223-245. https://doi.org/10.1007/s10755-023-09686-1
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, Article 15. https://doi.org/10.1186/s40561-023-00237-x
UNESCO. (2023). Guidance for generative AI in education and research.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Vergara, J. P. C. (2024). Navigating the generative artificial intelligence era: Charting the course for curricular reform in higher education in the Philippines. University of the Philippines Center for Integrative and Development Studies.
Yan, H. (2026). Craftsmanship spirit, professional values, and learning motivation among Chinese higher vocational college students. International Journal of Behavioral and Social Analytics, 1(1). https://doi.org/10.65166/wvm4ge89
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21, Article 21. https://doi.org/10.1186/s41239-024-00453-6
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education-Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
##submission.downloads##
已出版
期次
栏目
##submission.license##
##submission.copyrightStatement##
##submission.license.cc.by-nc-sa4.footer##This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). Authors retain copyright of their articles but grant the Asian Journal of Educational Leadership, Management and Pedagogy (AJELMP) the right of first publication.
Under this license, others may share and adapt the work for non-commercial purposes, provided appropriate credit is given and derivative works are distributed under the same license.
