Identifying Reasons That Contribute to Dropout Rates in Open and Distance Learning
Bibliographic Data
| ID | 21729547 |
|---|---|
| Authors | Kokila Ranasinghe (0000-0001-9021-0076, Open University of Sri Lanka), T Lakshini D Fernando (0000-0002-1796-1022, Open University of Sri Lanka), Nimali Vineeshiya (0000-0002-2551-3174, Open University of Sri Lanka), Aras Bozkurt (0000-0002-4520-642X, Anadolu University) |
| Year | 2025 |
| Volume | 26 |
| Issue | 2 |
| Pages | 162-183 |
| Publication date | 2025-05-08 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The International Review of Research in Open and Distributed Learning (JOURNAL) |
| Journal identifiers | ISSN: 1492-3831 • E-ISSN: 1492-3831 |
| Publisher | Athabasca University Press (PUBLISHER • CA) |
| DOI | 10.19173/irrodl.v26i2.8067 |
| OpenAlex | W4410193528 |
| Language | EN |
This study examined the reasons for high dropout numbers in programs offered through open and distance education (ODE). A mixed method approach was employed to collect data from a purposive sample of instructors and students at the Open University of Sri Lanka. A total of 38 reasons were revealed, of which aligned with existing dropout models as well as a few country- and institute-specific reasons. Results indicated that internal and external reasons mainly influenced students to drop out; student characteristics and skills also contributed to the students’ decision. The most influential reasons were job and family commitment, workload, time management, and flexibility, indicating that employed students were the more severely affected fraction of the dropout population. The researchers attempted to create a holistic picture of the dropout phenomenon in ODE, providing a foundation for policymakers and educators to implement targeted interventions and individualized support mechanisms to foster student retention
Distance education · Educational technology · Machine learning · Mathematics education · Open Education · World Wide Web · Computer Science · Online and Blended Learning · Online Learning and Analytics · Psychology
| Highly cited | No |
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