Artificial Intelligence–Based Learning Support for First-Year Undergraduate Students at Nakhon Phanom University

Authors

  • Nedphommin Puttra Academic Resources Center, Nakhon Phanom University, Nakhon Phanom 48000, Thailand.

Keywords:

Artificial Intelligence, Learning Support, Nakhon Phanom University

Abstract

This study aimed to investigate the use of Artificial Intelligence (AI) to support the learning of first-year undergraduate students at Nakhon Phanom University. It also sought to compare students’ learning achievement before and after the implementation of AI and to examine their satisfaction with the use of AI as a learning support tool.The population consisted of 2,500 first-year undergraduate students at Nakhon Phanom University. A sample of 345 students was selected using the Taro Yamane sample size determination table. The research instrument was a questionnaire. The statistical methods used for data analysis included frequency, percentage, mean, standard deviation, and t-test.

The findings revealed that students’ overall use of AI to support learning was at a high level. Students’ post-test learning achievement scores were significantly higher than their pre-test scores at the .05 level of statistical significance. Additionally, students reported a high level of satisfaction with the use of AI in all aspects. The results indicate that integrating artificial intelligence into instructional practices can enhance learning effectiveness, promote personalized learning opportunities, and appropriately support the academic development of students in higher education.

References

กระทรวงการอุดมศึกษา วิทยาศาสตร์ วิจัยและนวัตกรรม. (2569). แผนปฏิบัติราชการรายปี พ.ศ. 2569 กระทรวงการอุดมศึกษา วิทยาศาสตร์ วิจัยและนวัตกรรม. https://www.mhesi.go.th/index.php/aboutus/stg-policy/12026-GovernmentAactionplan2569_MHESI.html

สำนักงานเลขาธิการสภาการศึกษา. (2564). แนวโน้มการจัดการศึกษาในยุคดิจิทัล. สกศ.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promise and implications forteaching and learning. Boston, MA: Center for Curriculum Redesign.

Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2020). What matters to student success: A review of the literature. National Postsecondary Education Cooperative.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

OECD. (2021). Digital education outlook 2021: Pushing the frontiers with AI, blockchain and robots. Paris:OECD Publishing. https://www.oecd.org/en/publications/oecd-digital-education-outlook-2021_589b283f-en.html

Rovinelli, R. J., & Hambleton, R. K. (1977). On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch Journal of Educational Research, 2, 49–60.

UNESCO. (2023). Guidance for generative AI in education and research.UNESCO. https://shorturl.asia/Hm3F4

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?. https://link.springer.com/content/pdf/10.1186/s41239-019-0171-0%E2%80%8C.pdf

Zawacki-Richter, O., Bond, M., Marin, V. I., & Gouverneur, F. (2021). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 18(1), 1–27. https://www.researchgate.net/publication/336846972_Systematic_review_of_research_on_artificial_intelligence_applications_in_higher_education_-where_are_the_educators

Downloads

Published

2026-04-30

How to Cite

Puttra, N. (2026). Artificial Intelligence–Based Learning Support for First-Year Undergraduate Students at Nakhon Phanom University. Journal of Social Science Kamphaeng Saen, 1(1), 1–10. retrieved from https://so17.tci-thaijo.org/index.php/JSSK/article/view/1725

Issue

Section

Research Article