| 59938 |
Creator |
c9d52ef4a11ad1277436a89c20d0a5d4 |
| 59938 |
Creator |
71122b7715e55a3f53d5c14540adcbbb |
| 59938 |
Creator |
ext-9cc362a83e99a08ded6078e1d0373533 |
| 59938 |
Date |
2019-03-16 |
| 59938 |
Is Part Of |
repository |
| 59938 |
abstract |
The combination of trace data captured from technology-enhanced learning support systems,
formative assessment data and learning disposition data based on self-report surveys,
offers a very rich context for learning analytics applications. In previous research,
we have demonstrated how such Dispositional Learning Analytics applications not only
have great potential regarding predictive power, e.g. with the aim to promptly signal
students at risk, but also provide both students and teacher with actionable feedback.
The ability to link predictions, such as a risk for drop-out, with characterizations
of learning dispositions, such as profiles of learning strategies, implies that the
provision of learning feedback is not the end point, but can be extended to the design
of learning interventions that address suboptimal learning dispositions. Building
upon the case studies we developed in our previous research, we replicated the Dispositional
Learning Analytics analyses in the most recent 17/18 cohort of students based on the
learning processes of 1017 first-year students in a blended introductory quantitative
course. We conclude that the outcomes of these analyses, such as boredom being an
important learning emotion, planning and task management being crucial skills in the
efficient use of digital learning tools, help both predict learning performance and
design effective interventions. |
| 59938 |
authorList |
authors |
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editorList |
editors |
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status |
peerReviewed |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/811075 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/811080 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817819 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817829 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817830 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817831 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817832 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/817833 |
| 59938 |
uri |
http://data.open.ac.uk/oro/document/818632 |
| 59938 |
volume |
158 |
| 59938 |
type |
Article |
| 59938 |
type |
BookSection |
| 59938 |
label |
Tempelaar, Dirk; Nguyen, Quan and Rienties, Bart (2019). Learning Feedback Based
on Dispositional Learning Analytics. In: Virvou, Maria; Alepis, Efthimios; Tsihrintzis,
George A. and Jain, Lakhmi C. eds. Machine Learning Paradigms: Advances in Learning
Analytics. Intelligent Systems Reference Library, 158. Cham: Springer, pp. 69–89.
|
| 59938 |
label |
Tempelaar, Dirk; Nguyen, Quan and Rienties, Bart (2019). Learning Feedback Based
on Dispositional Learning Analytics. In: Virvou, Maria; Alepis, Efthimios; Tsihrintzis,
George A. and Jain, Lakhmi C. eds. Machine Learning Paradigms: Advances in Learning
Analytics. Intelligent Systems Reference Library, 158. Cham: Springer, pp. 69–89. |
| 59938 |
Publisher |
ext-1c5ddec173ca8cdfba8b274309638579 |
| 59938 |
Title |
Learning Feedback Based on Dispositional Learning Analytics |
| 59938 |
in dataset |
oro |