| 61295 |
Creator |
c9d52ef4a11ad1277436a89c20d0a5d4 |
| 61295 |
Creator |
480e8a34e82efe72669859ad8f018ff8 |
| 61295 |
Creator |
58223ce596eb9c58116b04bc3e385989 |
| 61295 |
Creator |
ext-de03abc70ba380c7566b6cae0fadfbba |
| 61295 |
Date |
2019 |
| 61295 |
Is Part Of |
p10421726 |
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Is Part Of |
repository |
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abstract |
Studies on engagement and learning design in Massive Open Online Courses (MOOCs) have
laid the groundwork for understanding how people learn in this relatively new type
of informal learning environment. To advance our understanding of how people learn
in MOOCs, we investigate the intersection between learning design and the temporal
process of engagement in the course. This study investigates the detailed processes
of engagement using educational process mining (EPM) in a FutureLearn science course
(N = 2086 learners) and applying an established taxonomy of learning design to classify
learning activities. The analyses were performed on three groups of learners categorised
based upon their clicking behaviour. The process-mining results show at least one
dominant pathway in each of the three groups, though multiple popular additional pathways
were identified within each group. All three groups remained interested and engaged
in the various learning and assessment activities. The findings from this study suggest
that in the analysis of voluminous MOOC data there is value in first clustering learners
and then investigating detailed progressions within each cluster that take the order
and type of learning activities into account. The approach is promising because it
provides insight into variation in behavioural sequences based on learners’ intentions
for earning a course certificate. These insights can inform the targeting of analytics-based
interventions to support learners and inform MOOC designers about adapting learning
activities to different groups of learners based on their goals. |
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authorList |
authors |
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status |
peerReviewed |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861652 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861657 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861658 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861659 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861660 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/861661 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/864640 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887550 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887551 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887552 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887553 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887554 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887555 |
| 61295 |
uri |
http://data.open.ac.uk/oro/document/887556 |
| 61295 |
type |
AcademicArticle |
| 61295 |
type |
Article |
| 61295 |
label |
Rizvi, Saman ; Rienties, Bart ; Rogaten, Jekaterina and Kizilcec, René F. Investigating
Variation in Learning Processes in a FutureLearn MOOC. Journal of Computing in Higher
Education (In Press). |
| 61295 |
label |
Rizvi, Saman ; Rienties, Bart ; Rogaten, Jekaterina and Kizilcec, René F. (2019).
Investigating Variation in Learning Processes in a FutureLearn MOOC. Journal of Computing
in Higher Education (Early Access). |
| 61295 |
label |
Rizvi, Saman ; Rienties, Bart ; Rogaten, Jekaterina and Kizilcec, René F. (2019).
Investigating Variation in Learning Processes in a FutureLearn MOOC. Journal of Computing
in Higher Education (Early Access). |
| 61295 |
Title |
Investigating Variation in Learning Processes in a FutureLearn MOOC |
| 61295 |
in dataset |
oro |