Rethinking dropout in online higher education: The case of the Universitat Oberta de Catalunya
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In recent years, several studies have been carried out into the reasons why students drop out of online higher education, following the rise in the relative weight of this form of education. However, more effort has gone into analyzing the causes of this phenomenon than into trying to characterize students who drop out, that is defining what a dropout student is. But obtaining a proper definition of dropout is just as important as describing its causes. It also appears that the definition of dropout is very sensitive to context. As one of the main findings of this article, we reach a pure empirical definition, at a programme level, of students who drop out of an online higher education context with non-mandatory enrollment. This definition is based on the probability of students not continuing a specific academic programme following several consecutive semesters of “theoretical break”, and is highly adaptable to institutions offering distance education with no permanence requirements, that is ones offering the possibility of taking breaks. Our findings show that there are differences regarding the number of consecutive semesters that define dropout depending on whether the programme requires previous experience or not. Additionally, we observe significant differences in the dropout rate between specific programmes, as well as a higher level of dropout in the first semesters. Analyzing the reasons behind these facts should help higher education institutions to make more sound and efficient decisions.
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Learners who fail and learners who drop out have different needs.
“there are different situations, and learners from each group will have different needs (Grau-Valldosera and Minguillón 2014).”
From Experiences in the use of an adaptive intelligent system to enhance online learners' performance: a case study in Economics and Business courses (2021) · cites this paper as Grau-Valldosera and Minguillón 2014
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- Authors
- Grau-Valldosera, J., & Minguillón, J.
- Affiliations
- Universitat Oberta de Catalunya (ES)
- Venue
- The International Review of Research in Open and Distributed Learning
- Publisher
- Athabasca University Press
- Published
- 2014-01-15
- Volume
- 15
- Issue
- 1
- ISSN
- 1492-3831 (ISSN-L)
- OpenAlex
- W1480756546
- Cited by
- 71
- References
- 37
- Citations by year
- 2026: 5 · 2025: 2 · 2024: 10 · 2023: 7 · 2022: 5 · 2021: 8 · 2020: 10 · 2019: 4 · 2018: 6 · 2017: 6 · 2016: 3 · 2015: 4 · 2014: 1
- FWCI
- 12.87
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- The International Review of Research in Open and Distributed Learning (publishedVersion, cc-by)
- O2 - Repositori Institucional (Universitat Oberta de Catalunya) (publishedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Érudit (Université de Montréal) (submittedVersion, cc-by)
- Funders
- Universitat Oberta de Catalunya
- Topics
- Social Sciences › Demography › Evasion and Academic Success Factors
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Education › Higher Education Research Studies
- Keywords
- school dropout, online higher education, distance education, dropout rates, Universitat Oberta de Catalunya
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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