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Development of a Model for Retention of MS/MPhil Students at Virtual University (VU) of Pakistan

Development of a Model for Retention of MS/MPhil Students at Virtual University (VU) of Pakistan

Muhammad Yasir Rafiq, Mueen Ud-Din Azad, Aamer Rafique, Lu Shi Chang
Copyright: © 2020 |Volume: 18 |Issue: 2 |Pages: 18
ISSN: 1539-3100|EISSN: 1539-3119|EISBN13: 9781799804864|DOI: 10.4018/IJDET.2020040101
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MLA

Rafiq, Muhammad Yasir, et al. "Development of a Model for Retention of MS/MPhil Students at Virtual University (VU) of Pakistan." IJDET vol.18, no.2 2020: pp.1-18. http://doi.org/10.4018/IJDET.2020040101

APA

Rafiq, M. Y., Azad, M. U., Rafique, A., & Chang, L. S. (2020). Development of a Model for Retention of MS/MPhil Students at Virtual University (VU) of Pakistan. International Journal of Distance Education Technologies (IJDET), 18(2), 1-18. http://doi.org/10.4018/IJDET.2020040101

Chicago

Rafiq, Muhammad Yasir, et al. "Development of a Model for Retention of MS/MPhil Students at Virtual University (VU) of Pakistan," International Journal of Distance Education Technologies (IJDET) 18, no.2: 1-18. http://doi.org/10.4018/IJDET.2020040101

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Abstract

Due to the of use of ICTs and ODL, Virtual University (VU) has become one of leading distance learning university in Pakistan. However, the retention rate among online learners found considerably low. The primary objective of this research was to dig out determinants of retention of MS /MPhil students at VU and modeling their retention by considering important influences. For sampling purpose, three departments with the most students were considered and complete enumeration was done. There were 4,608 students from three departments; Computer Science & Technology, Management Sciences and Education have been included in this study. To dig out the important retention factors, this research has used a Chi-Square test, optimal scaling, a decision tree using CHAID analysis, and then developed a suitable model for student retention. Binary logistic regression techniques were applied. Results have revealed that gender, scholarship, province, location, and division are significant factors and contributing in predicting students' retention at VU. Detailed outputs are shown in respective tables and figures. At the end, different recommendations and suggestions are proposed.

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