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Should I Stay, or Should I Go? Revisiting Student Retention Models in Distance Education
Author(s) -
Marko Radovan
Publication year - 2019
Publication title -
turkish online journal of distance education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.374
H-Index - 22
eISSN - 1309-4564
pISSN - 1302-6488
DOI - 10.17718/tojde.598211
Subject(s) - dropout (neural networks) , distance education , openness to experience , learning styles , task (project management) , retention rate , mathematics education , diversity (politics) , affect (linguistics) , face (sociological concept) , psychology , computer science , sociology , social psychology , engineering , social science , computer security , machine learning , anthropology , systems engineering , communication
Supporters of distance education highlight the many advantages of online learning as compared to face-to-face education, such as greater openness, diversity of teaching materials, adjustment to student learning styles, the speed of learning, and more. Despite the advantages, the growing number of programs, and the increased acceptance of distance education in national strategies worldwide, distance learning providers are faced with the problem of dropouts. Studies have shown that the dropout rate in distance educational programs is higher than the dropout rate in traditional programs. Understanding of the reasons and determinants behind dropping out of an educational program is a challenging task for educators, researchers, and policy-makers. In this paper, we describe the main characteristics of distance education, and analyze the models that try to describe and prevent students from dropping out of these programs. Our analysis suggests that the circumstances that affect the dropout rate should be considered in the planning and implementation of distance education programs.

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