In recent years, several studies have been carried out into the reasons why students drop out of online higher 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 is.
As one of the
main findings of this article, the authors (Josep Grau-Valldosera and Julià Minguillón) reach a pure empirical definition, at a programme level, of students who drop out of an online higher education context with non-mandatory enrolment. 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. Analyzing the reasons behind these facts should help higher education institutions to make more sound and efficient decisions.
Rethinking dropout in online higher education: The case of the Universitat Oberta de Catalunya
1. Rethinking Dropout in Online
Higher Education: the case of the
Universitat Oberta de Catalunya
Josep Grau-Valldosera, Julià Minguillón
Grau-Valldosera, J., & Minguillón, J. (2014). Rethinking dropout in online higher education: The case of
the Universitat Oberta de Catalunya. The International Review Of Research In Open And Distributed
Learning, 15(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1628
1
2. Rethinking dropout
• Quantifying the problem
• Taking a break or dropping out?
The model
• Enrollment patterns
• Evidences from data
Summary
• Conclusions
• Current and future work
Index
2
Rethinking Dropout in Online Higher Education: the case of the UOC
3. 1. Rethinking dropout
• How do we define dropout in an open university?
• Quantifying the problem
• Taking a break or dropping out?
3
Rethinking Dropout in Online Higher Education: the case of the UOC
4. 4
1.1. Quantifying the problem
Rethinking Dropout in Online Higher Education: the case of the UOC
CC-BYEsterUsarralde
5. 5
1.1. Quantifying the problem
27.8%
Rethinking Dropout in Online Higher Education: the case of the UOC
6. 6
1.1. Quantifying the problem
Economic and
social costs
Rethinking Dropout in Online Higher Education: the case of the UOC
7. 7
1.2. Taking a break or dropping out?
Bologna (EHEA) degrees (Catalan), 2008/1 – 2013/2
Rethinking Dropout in Online Higher Education: the case of the UOC
8. 8
1.2. Taking a break or dropping out?
Rethinking Dropout in Online Higher Education: the case of the UOC
9. 2. The model
• Empirical approach based on historical enrollment
data
• Enrollment patterns
• Evidences from data
9
Rethinking Dropout in Online Higher Education: the case of the UOC
10. 10
2.1. Enrollment patterns
Students are aligned starting from their first
semester:
1 1 1 Student with three consecutive semesters
1 0 1 1 Student taking a break the 2nd semester
1 1 0 0 0 0 Student with four consecutive breaks
:
:
1 ... 1 0 ... 0 1 How many consecutive ‘0’ before ‘1’?
P(Xi=1 | Xi-1, ..., Xi-N=0) < ε
Rethinking Dropout in Online Higher Education: the case of the UOC
11. 11
2.2. Evidences from data
Data from LRU (IRRODL paper):
ε = 1% N varies from 5 to 12 semesters
ε = 5% N varies from 3 to 5
ε = 10% N varies from 2 to 3
But using EHEA data shows that N=1 or 2 (10%)!
Rethinking Dropout in Online Higher Education: the case of the UOC
12. 3. Summary
• Conclusions
• Current and future work
12
Rethinking Dropout in Online Higher Education: the case of the UOC
13. 13
3.1. Conclusions
• No need to use the official dropout definition
• Small window (N=2 or 3) for reasonable Type I
error (10%)
• Recent data (EHEA) shows that taking a break is
almost the same than dropping out!
• Enrollment patterns show dropout is a decaying
phenomenon, but highly accumulative
Rethinking Dropout in Online Higher Education: the case of the UOC
14. 14
3.2. Current and future work
• N=2 “ensures” a student is a dropout
• Build predictive models using data from the 1st semester
• Learner background
• Enrollment data
• Navigational and interaction patterns
• Formative evaluation
• Academic performance
• But N=1 is a very good predictor as well
• Ask students taking 2nd semester breaks
• Actions for “waking up” true breaks
Rethinking Dropout in Online Higher Education: the case of the UOC