Research Article

Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education

Volume: 6 Number: 1 April 20, 2026
TR EN

Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education

Abstract

Integrating an Artificial Intelligence into education has emerged as a promising approach to enhancing student success across diverse academic settings. This study examines how student outcomes, including academic performance, engagement, and overall well-being, can be improved through the strategic use of aArtificial Intelligence tool. By leveraging AI-driven based tools and technologies, educators can personalize learning experiences, deliver timely feedback, and identify individualized learning pathways tailored to students' specific needs. Drawing on primary data collected from undergraduate economics courses, this research presents a model for navigating AI integration to support personalized learning and academic achievement. We used A simple correlation analysis was used to explore the relationship between assignments, tasks, and student performance, allowing for the early identification of students at risk. These insights were used to inform targeted interventions through AI-supported learning with course specific Chat Bot (AI agent.). Further the study analyzed how much overall course grade improved after the integration of personalized learning tool given to targeted at Risk Students. Results gave evidence of improvement, which further open the door for all the educator with any disciple to include in any class size to improve and help the students in their academic success pathways. This study demonstrates the result oriented idea, and could be base for further study in this area.

Keywords

Supporting Institution

Rutgers University

Ethical Statement

This study adhered to ethical guidelines concerning student data privacy and informed consent. AI integration was used solely for pedagogical enhancement, with no automated decision-making impacting student grades. Limitations include the small sample size limited to a single instructor's course and the potential for algorithmic bias in AI interpretation of engagement data (Luckin, 2023).

References

  1. Adeshola, I., & Adepoju, A. P. (2023). The opportunities and challenges of ChatGPT in education. Interactive Learning Environments. https://doi.org/10.1080/10494820.2023.2253858
  2. Brusilovsky, P. (2024). AI in education, learner control, and human–AI collaboration. International Journal of Artificial Intelligence in Education, 34, 122–135. https://doi.org/10.1007/s40593-023-00356-z
  3. Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://curriculumredesign.org/our-work/artificial-intelligence-in-education
  4. Korinek, A. (2023). Generative AI for economic research: Use cases and implications for economists. Journal of Economic Literature, 61(4), 1281–1317. https://doi.org/10.1257/jel.20231736
  5. Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599. https://doi.org/10.1016/j.compedu.2009.09.008
  6. Nguyen, A., Ngo, H. N., Hong, Y., & Dang, B. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11316-w
  7. Siemens, G., & Baker, R. S. J. d. (2012). Learning analytics and educational data mining: Towards communication and collaboration. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK ’12) (pp. 252–254). ACM. https://doi.org/10.1145/2330601.2330661
  8. U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations (Report). https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf

Details

Primary Language

English

Subjects

Agricultural Extension and Communication

Journal Section

Research Article

Publication Date

April 20, 2026

Submission Date

December 21, 2025

Acceptance Date

January 14, 2026

Published in Issue

Year 2026 Volume: 6 Number: 1

APA
Pandey, S., Govındasamy, R., & Vellangany, I. (2026). Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education. Eurasian Journal Of Agricultural Economics (EJAE), 6(1), 61-76. https://izlik.org/JA56DN82BW
AMA
1.Pandey S, Govındasamy R, Vellangany I. Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education. Eurasian Journal Of Agricultural Economics (EJAE). 2026;6(1):61-76. https://izlik.org/JA56DN82BW
Chicago
Pandey, Sonal, Ramu Govındasamy, and Isaac Vellangany. 2026. “Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education”. Eurasian Journal Of Agricultural Economics (EJAE) 6 (1): 61-76. https://izlik.org/JA56DN82BW.
EndNote
Pandey S, Govındasamy R, Vellangany I (April 1, 2026) Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education. Eurasian Journal Of Agricultural Economics (EJAE) 6 1 61–76.
IEEE
[1]S. Pandey, R. Govındasamy, and I. Vellangany, “Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education”, Eurasian Journal Of Agricultural Economics (EJAE), vol. 6, no. 1, pp. 61–76, Apr. 2026, [Online]. Available: https://izlik.org/JA56DN82BW
ISNAD
Pandey, Sonal - Govındasamy, Ramu - Vellangany, Isaac. “Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education”. Eurasian Journal Of Agricultural Economics (EJAE) 6/1 (April 1, 2026): 61-76. https://izlik.org/JA56DN82BW.
JAMA
1.Pandey S, Govındasamy R, Vellangany I. Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education. Eurasian Journal Of Agricultural Economics (EJAE). 2026;6:61–76.
MLA
Pandey, Sonal, et al. “Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education”. Eurasian Journal Of Agricultural Economics (EJAE), vol. 6, no. 1, Apr. 2026, pp. 61-76, https://izlik.org/JA56DN82BW.
Vancouver
1.Sonal Pandey, Ramu Govındasamy, Isaac Vellangany. Leveraging Artificial Intelligence for Personalized Learning and Student Success: Evidence from Economics Education. Eurasian Journal Of Agricultural Economics (EJAE) [Internet]. 2026 Apr. 1;6(1):61-76. Available from: https://izlik.org/JA56DN82BW