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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
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
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
1.1. Quantifying the problem
Rethinking Dropout in Online Higher Education: the case of the UOC
CC-BYEsterUsarralde
5
1.1. Quantifying the problem
27.8%
Rethinking Dropout in Online Higher Education: the case of the UOC
6
1.1. Quantifying the problem
Economic and
social costs
Rethinking Dropout in Online Higher Education: the case of the UOC
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
1.2. Taking a break or dropping out?
Rethinking Dropout in Online Higher Education: the case of the UOC
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
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
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
3. Summary
• Conclusions
• Current and future work
12
Rethinking Dropout in Online Higher Education: the case of the UOC
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
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
Rethinking dropout in online higher education: The case of the Universitat Oberta de Catalunya

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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