| 71854 |
Creator |
c9d52ef4a11ad1277436a89c20d0a5d4 |
| 71854 |
Creator |
71122b7715e55a3f53d5c14540adcbbb |
| 71854 |
Creator |
ext-3af40bd1f940d490b6532d731887a9e1 |
| 71854 |
Date |
2020-08-11 |
| 71854 |
Is Part Of |
repository |
| 71854 |
abstract |
The measurement of learning engagement is a major research theme, both in the learning
analytics community and the broader area of educational research. The complexity of
conceptualizing as well as operationalizing the construct of engagement generates
a wide range of instruments, such as self-report surveys, log data from technology-enhanced
learning systems, think-aloud and tests. In this empirical work, we investigate the
alignment of behavioural traces of engagement with self-report measures and their
impact on academic performance. The unique contribution of this study was the integration
of temporal, behavioural, affective, and cognitive dimensions of engagement by combing
digital traces at three different learning phases with self-report, formative as well
as summative assessments. Using a two-step cluster analysis based on data from 1,027
undergraduate students in a first-year 8-week statistics course, we identified four
distinct temporal engagement patterns (i.e. nonactive, active before tutorial, active
before quiz, and active before exams). Our analysis showed that early engagement (i.e.
before tutorial) was significantly associated with course performance and self-report
measures, while late engagement patterns had weaker correlations. This study shed
further lights on a potential source of heterogeneity and collinearity in engagement
measures (i.e. timing of engagement) that should be accounted for in learning analytics
model. In order to design effective intervention, it is crucial to consider different
profiles of learners based on their engagement patterns as well as the temporal relation
between trace data, self-report, and academic performance. |
| 71854 |
authorList |
authors |
| 71854 |
editorList |
editors |
| 71854 |
status |
peerReviewed |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207043 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207044 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207045 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207046 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207047 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1207048 |
| 71854 |
uri |
http://data.open.ac.uk/oro/document/1214034 |
| 71854 |
type |
Article |
| 71854 |
type |
BookSection |
| 71854 |
label |
Tempelaar, Dirk; Nguyen, Quan and Rienties, Bart (2020). Learning Analytics and
the Measurement of Learning Engagement. In: Ifenthaler, Dirk and Gibson, David eds.
Adoption of Data Analytics in Higher Education Learning and Teaching. Advances
in Analytics for Learning and Teaching. Cham: Springer, pp. 159–176. |
| 71854 |
Publisher |
ext-1c5ddec173ca8cdfba8b274309638579 |
| 71854 |
Title |
Learning Analytics and the Measurement of Learning Engagement |
| 71854 |
in dataset |
oro |