International Research journal of Management Science and Technology

  ISSN 2250 - 1959 (online) ISSN 2348 - 9367 (Print) New DOI : 10.32804/IRJMST

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LEVERAGING MACHINE LEARNING APPROACHES FOR PREDICTING STUDENTS' ACADEMIC SUCCESS: AN ANALYTICAL PERSPECTIVE

    2 Author(s):  MR. SUNIL P. PATEL,DR. HEMANT N. PATEL

Vol -  15, Issue- 5 ,         Page(s) : 48 - 58  (2024 ) DOI : https://doi.org/10.32804/IRJMST

Abstract

Predicting students academic performance stands as a crucial endeavor within educational settings such as schools and universities. This predictive ability not only aids in designing effective interventions that enhance academic outcomes but also plays a pivotal role in preventing student dropout and addressing other pertinent concerns.

D. Evawati, "Optimization of Nutrition Science Learning through Educational Technology at PGRI Adi Buana University Surabaya," Jurnal Iqra': Kajian Ilmu Pendidikan, vol. 8, no. 1, pp. 385-401, 2023.
[2] A. C. Ikegwu, H. F. Nweke, and C. V. Anikwe, "Recent trends in computational intelligence for educational big data analysis," Iran Journal of Computer Science, pp. 1-27, 2023.

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