Levels and Correlation Between Artificial Intelligence Competence and Lifelong Learning Competence Among Higher Education Students
Main Article Content
Abstract
This study aimed to examine the levels of Artificial Intelligence (AI) competence and lifelong learning competence, as well as to investigate the relationships and predictive effects between AI competence and lifelong learning competence among higher education students. The sample consisted of 435 undergraduate students from public universities in Thailand, selected through stratified and simple random sampling methods. Data were collected using questionnaires and analyzed using descriptive statistics and inferential statistics which are Pearson’s correlation coefficient and linear regression analysis.
The findings revealed that students demonstrated a high overall level of AI competence (x̄ = 3.78) and lifelong learning competence (x̄ = 4.03). Among the AI competence dimensions, ethical awareness in AI use showed the highest mean score (x̄ = 4.06), whereas basic knowledge and understanding of AI showed the lowest mean score (x̄ = 3.37). Pearson’s correlation analysis indicated that AI competence was positively correlated with lifelong learning competence at a statistically significant level (r = .44–.68, p < .01). AI evaluation and creative application competence showed the strongest relationship with analytical and synthetic thinking for learning (r = .68). Regression analysis further revealed that AI competence could explain 46% of the variance in lifelong learning competence, increasing to 55% when considering individual dimensions. Among these dimensions, AI evaluation and creative application competence demonstrated the strongest predictive effect (β = .34).
The study recommends that higher education institutions should design learning environments that emphasize thinking with AI rather than merely using AI tools. In addition, AI ethics and self-directed learning should be systematically integrated into educational practices to foster genuine lifelong learners in the AI-driven era.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
1. กองบรรณาธิการสงวนสิทธิ์ในการพิจารณาและตัดสินการตีพิมพ์บทความในวารสาร
2. บทความทุกเรื่องจะได้รับการตรวจสอบทางวิชาการโดยผู้ทรงคุณวุฒิ แต่ข้อความและเนื้อหาในบทความที่ตีพิมพ์เป็นความรับผิดชอบของผู้เขียนแต่เพียงผู้เดียว มิใช่ความคิดเห็นและความรับผิดชอบของมหาวิทยาลัยศรีปทุม
3. การคัดลอกอ้างอิงต้องดำเนินการตามการปฏิบัติในหมู่นักวิชาการโดยทั่วไป และสอดคล้องกับกฎหมายที่เกี่ยวข้อง
References
Baker, R. S. (2019). Challenges for the future of educational data mining: The Baker learning analytics prizes. Journal of Educational Data Mining, 11(1), 1-17.
Candy, P.C., (2002). Lifelong learning and information literacy. July 2002, White Paper prepared for UNESCO, the U.S. National Commission on Libraries and Information Science, and the National Forum on Information Literacy, for use at the Information Literacy Meeting of Experts, Prague, The Czech Republic.
Drachsler, H., & Greller, W. (2016). Privacy and analytics: It's a DELICATE issue a checklist for trusted learning analytics. In Proceedings of the sixth international conference on learning analytics & knowledge, 89-98. ACM. https://doi.org/10.1145/2883851.2883893
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., et al. (2023). 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, https://doi.org/10.1016/j.ijinfomgt.2023.102642
Facione, P. A. (2011). Critical thinking: What it is and why it counts. Insight Assessment.
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education. Center for Curriculum Redesign. DOI: 10.58863/20.500.12424/4276068
Jarvis, P. (2007). Globalisation, lifelong learning and the learning society. Routledge.
Jivet, I., Scheffel, M., Schmitz, M., Robbers, S., Specht, M., & Drachsler, H. (2021). From students with love: An empirical study on learner goals, self-regulated learning and sense-making of learning analytics in higher education. The Internet and Higher Education, 50. https://doi.org/10.1016/j.iheduc.2021.100804
Knowles, M. S. (1984). Andragogy in Action. Applying Modern Principles of Adult Education. San Francisco, CA: Jossey Bass.
Ng, D.T.K., Leung, J.K.L., Chu, K.W.S. and Qiao, M.S. (2021), AI Literacy: Definition, Teaching, Evaluation and Ethical Issues. Proceedings of the Association for Information Science and Technology, 58: 504-509. https://doi.org/10.1002/pra2.487
NSTDA. (2022). National AI Strategy. https://www.nstda.or.th/nac/2025/exhibitions/honor01/
Mezirow, J. (1997), Transformative Learning: Theory to Practice. New Directions for Adult and Continuing Education, 1997: 5-12. https://doi.org/10.1002/ace.7401
Ministry of Education [MOE] Thailand. (2024). Announcement from the Ministry of Education on the Ministry of Education's: Educational Policy for the Fiscal Year B.E. 2568-2569. (2024, November 13). Government Gazette. No. 141 Section 309 D, 11–13.
OECD. (2021). The future of education and skills: Education 2030. OECD Publishing.
Phosapim, S. (2025). Integration of AI Technology with Teaching and Learning in Education. Journal of Interdisciplinary Study Education Science, 1(1), 24-33. (in Thai)
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Siritharo, P. J. (2025). The Use of AI Technology in Adaptive Learning. Chintasit Academic Journal, 2(3), 208-218. (in Thai)
Thavirath, J. (2025). AI and Education: The Ultimate Intelligent Assistant for Enhancing Learning. Journal of Social Studies Perspectives, 1(2), 98-107. (in Thai)
UNESCO. (2020). Embracing lifelong learning for all. UNESCO.
UNESCO. (2021). AI and education: Guidance for policymakers. UNESCO.
Zawacki-Richter, O., Marín, V.I., Bond, M. et al. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators?. Int J Educ Technol High Educ 16, 39. https://doi.org/10.1186/s41239-019-0171-0
Zimmerman, B. J. (2002). Becoming a Self-Regulated Learner: An Overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2