Student Dropout Analysis: A Literature Review in the Context of Higher Education

Authors

  • Kanika Dhingra Department of Computer Science, Banasthali Vidyapith University, Rajasthan. Author
  • Sanjay Kumar Sharma Department of Computer Science, Banasthali Vidyapith University, Rajasthan Author

Keywords:

Student dropout prediction, Machine Learning, Educational Data Mining, Learning Analytics, Higher education

Abstract

Education is a crucial requirement in everyone’s life in order to make them employable and earn their living. However, attaining education with good academic achievement remains a key challenge to address. Over the time it has been observed that all students who enroll for the education do not accomplish the goal of attaining a degree. Some of the students dropout before completion of the course due to numerous reasons. Higher education dropouts have a wide range of effects on society as a whole, the job market, and the higher education system in addition to the student. These include the loss of funds intended for higher education, reduced labour competitiveness, and incomplete education. Students, their parents, universities, the economy, and society at large are all impacted by dropout rates. Therefore, determining the causes of dropout is crucial so that policies can be put in place to lessen it.

Downloads

Published

13-03-2026

Conference Proceedings Volume

Section

Articles

How to Cite

Dhingra, K. ., & Sharma, S. K. (2026). Student Dropout Analysis: A Literature Review in the Context of Higher Education. DMPedia Lecture Notes in Computer Science & Engineering, IMPACT26, 91-98. https://digitalmanuscriptpedia.com/conferences/index.php/DMP-LNCSE/article/view/12