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Student Dropout Risk Prediction with Academic Trend Analysis -Using AI/ML

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Last date : 27-Oct-2026

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Student Dropout Risk Prediction with Academic Trend Analysis -Using AI/ML


Sanzal Chandrakant Fulewale



Sanzal Chandrakant Fulewale "Student Dropout Risk Prediction with Academic Trend Analysis -Using AI/ML" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.1066-1083, URL: https://www.ijtsrd.com/papers/ijtsrd101683.pdf

Student dropout is one of the most complex challenges facing the education systen worldwide. Is order to evaluate the success of Machine Learning and Deep Leaming algorithms in predicting student dropout, a systematic review was conducted. The search was carried out in several electronic bibliographic databases, including Scopus, IEEE, and Web of Science, covering up to June 2023, having 246 articles as search reports. Exclusion criteria such as review articles. editorials, letters, and comments, were established. The final review included 23 studies in which perfornance metric such as accuracy/precision, sensitivity/recall, specificity, and area under the curve (AUC) were evaluated. In addition aspects related to study modality, training, testing strategy, cross-validation, and confounding matrix were considered. The review results revealed that the most used Machine Learning algorithm was Random Forest, present in 21.73% of the studies; this algorithm obtained an accuracy of 99% in the prediction of student dropout, higher than all the algorithms used in the total number of studies reviewed.

student dropout risk prediction with academic trend analysis


IJTSRD101683
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
1066-1083
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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