Development and Initial Validation of a Survey on College Students' Academic Use of Artificial Intelligence and Its Association with Study Habits, Classroom Engagement, and Academic Output Quality
Article Sidebar
Main Article Content
Abstract
Artificial intelligence (AI) is increasingly integrated into higher education, yet evidence on students’ academic use of AI and its perceived association with study habits, classroom engagement, and academic output quality remains limited in Philippine private higher education institutions. This study examined college students’ reported AI use for academic tasks and perceptions of its association with these academic behaviors, including differences by sex, year level, and daily AI use. Using a quantitative cross-sectional descriptive-comparative design, data were collected from 351 college students through an adapted and validated research instrument. Exploratory factor analysis, Cronbach’s alpha, and McDonald’s omega established satisfactory construct validity and excellent internal consistency, while descriptive statistics, t-tests, ANOVA, and Tukey post hoc tests were used for analysis. Overall, students reported neutral levels of agreement regarding AI-related academic behaviors. Male and third-year students reported significantly higher agreement than female and lower-year-level students, while no significant differences were found based on daily duration of AI use. The findings suggest that students’ sex and year level may influence perceptions and use of AI in academic contexts. The validated instrument may support future research and responsible AI integration in higher education.
Article Details
Section
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
References
Arslan, A. C., Arif, S., Calimlim, R. J. F., Khan, S. Z., & Sadia, A. (2024). The impact of AI-powered educational tools on student engagement and learning outcomes at higher education level. International Journal of Contemporary Issues in Social Sciences, 3(2), 2842–2852. https://ijciss.org/index.php/ijciss/article/view/1027
Bai̇doo-Anu, D., & Ansah, L. O. (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 50. http://doi.org/10.1186/s41239-021-00282-x
Cardon, P., Fleischmann, C., Aritz, J., Logemann, M., & Heidewald, J. (2023). The Challenges and Opportunities of AI-Assisted Writing: Developing AI Literacy for the AI Age. Business and Professional Communication Quarterly, 86(3), 257–295. https://doi.org/10.1177/23294906231176517
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. Education Sciences, 13(10), 1025. https://doi.org/10.3390/educsci13101025
Chen, S., & Zhao, Y. (2025). Why am I willing to collaborate with AI? Exploring the desire for collaboration in human-AI hybrid group brainstorming. Kybernetes. https://doi.org/10.1108/k-08-2024-2105
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage Publications, Inc.
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Chudaeva, E., & Yuen, C. L. (2025). Taking notes with artificial intelligence (AI)-based technology and academic integrity: perspectives from online learners. Education and Information Technologies, 30(17), 25197–25221. https://doi.org/10.1007/s10639-025-13718-y
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Gjermeni, F., & Prodani, F. (2024). AI and Student Engagement: A Comparative Analysis. Interdisciplinary Journal of Research and Development, 11(3), 195. https://doi.org/10.56345/ijrdv11n326
Haderer, B., & Ciolacu, M. (2022). Education 4.0: Artificial intelligence assisted task-and time planning system. Procedia Computer Science, 200, 1328–1337. https://doi.org/10.1016/j.procs.2022.01.334
Han, J., Liu, G., & Xiang, S. (2025). To engage with AI or not: learning engagement among rural junior high school students in an AI-powered adaptive learning environment. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-05676-0
Hartley, K., Hayak, M., & Ko, U. H. (2024). Artificial intelligence Supporting Independent Student learning: An evaluative case study of CHATGPT and Learning to Code. Education Sciences, 14(2), 120. https://doi.org/10.3390/educsci14020120
Hou, I., Mettille, S., Man, O., Li, Z., Zastudil, C., & MacNeil, S. (2024). The effects of generative AI on computing students' help seeking preferences. In Proceedings of the 26th Australasian Computing Education Conference (pp. 39–48). https://doi.org/10.1145/3636243.3636248
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., & Seidel, T. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Khairuddin, Z., Shahabani, N., Ahmad, S., Ahmad, A., & Zamri, N. (2024). Students’ perceptions on the artificial intelligence (AI) tools as academic support. Malaysian Journal of Social Sciences and Humanities, 9, Article e003087. https://doi.org/10.47405/mjssh.v9i11.3087
Maamor, H., Achim, N., Ahmad, N., Roszaman, N., Anuar, N., Azwa, N., Rahman, S., & Hamjah, N. (2024). The effect of artificial intelligence (AI) on students' learning. Information Management and Business Review, 16, 856–867. https://doi.org/10.22610/imbr.v16i3S(I)a.4178
Marzuki, M., Widiati, U., Rusdin, D., Darwin, , & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2). https://doi.org/10.1080/2331186X.2023.2236469
OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., Avila, R., Babuschkin, I., Balaji, S., Balcom, V., Baltescu, P., Bao, H., Bavarian, M., Belgum, J., Zoph, B. (2023). GPT-4 Technical Report. https://arxiv.org/abs/2303.08774
Rainey, C., O’Regan, T., Matthew, J., Skelton, E., Woznitza, N., Chu, K., Goodman, S., McConnell, J., Hughes, C., Bond, R., McFadden, S., & Malamateniou, C. (2021). Beauty Is in the AI of the Beholder: Are We Ready for the Clinical Integration of Artificial Intelligence in Radiography? An Exploratory Analysis of Perceived AI Knowledge, Skills, Confidence, and Education Perspectives of UK Radiographers. Frontiers in Digital Health, 3, 739327. https://doi.org/10.3389/fdgth.2021.739327
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education? Journal of Applied Learning and Teaching, 6, 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Stevkovska, M. (2024). Redesigning academic writing assignments in the age of AI-Generated content. In Advances in educational technologies and instructional design book series (pp. 209–232). https://doi.org/10.4018/979-8-3693-4310-4.ch007
Tamayo, J., Sotto, J, C., Vicente, C., & Lim, M. (2025). The Impact of AI Tools on Student Engagement and Academic Performance. GEO Academic Journal. 6. 10.56738/issn29603986.geo2025.6.94.
Tossell, C. C., Tenhundfeld, N. L., Momen, A., Cooley, K., & De Visser, E.
J. (2024). Student Perceptions of ChatGPT use in a college essay Assignment: Implications for learning, grading, and trust in Artificial intelligence. IEEE Transactions on Learning Technologies, 17, 1069–1081. https://doi.org/10.1109/tlt.2024.3355015
Vázquez-Parra, J, C., Langone, M., Lis-Gutiérrez, J, P., & Palomino-Gámez, S. (2024). Importance of University Students’ Perception of Adoption and Training in Artificial Intelligence Tools. Societies. 14. 141. 10.3390/soc14080141.
Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33–60. https://doi.org/10.1006/obhd.2000.2896
Vieriu, A. M., & Petrea, G. (2025). The Impact of Artificial Intelligence (AI) on Students’ Academic Development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343
Xie, X., & Wang, T. (2023). Artificial intelligence: A help or threat to contemporary education? Should students be forced to think and do their tasks independently? Education and Information Technologies, 29(3), 3097–3111.https://doi.org/10.1007/s10639-023-11947-7
Yau, H. K., & Cheng, A. L. F. (2012). Gender Difference of Confidence in Using Technology for Learning. The Journal of Technology & Studies, 38(2), 74–79. https://doi.org/10.21061/jots.v38i2.a.2
Zhai, X. (2022). ChatGPT User Experience: Implications for Education. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4312418
Zhou, X., Zhang, J., & Chan, C. (2024). Unveiling students’ experiences and perceptions of artificial intelligence usage in higher education. Journal of University Teaching and Learning Practice, 21. https://doi.org/10.53761/xzjprb23