Kent, Carmel;
Akanji, Abayomi;
du Boulay, Benedict;
Bashir, Ibrahim;
Fikes, Thomas;
Rodríguez De Jesús, Sue;
Ramirez Hall, Alysha;
... Luckin, Rose; + view all
(2022)
Mind the Gap: From Typical LMS Traces to Learning to Learn Journeys.
In: Trajkovski, Goran and Demete, Marylee and Hayes, Heather, (eds.)
Applying Data Science and Learning Analytics Throughout a Learner's Lifespan.
IGI Global: Hershey PA, USA.
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Abstract
Many universities aim to improve students' 'learning to learn' (LTL) skills to prepare them for post-academic life. This requires evaluating LTL and integrating it into the university's curriculum and assessment regimes. Data is essential to provide evidence for the evaluation of LTL, meaning that available data sources must be connected to the types of evidence required for evaluation. This chapter describes a case study using an LTL ontology to connect the theoretical aspects of LTL with a university's existing data sources and to inform the design and application of learning analytics. The results produced by the analytics indicate that LTL can be treated as a dimension in its own right. The LTL dimension has a moderate relationship to academic performance. There is also evidence to suggest that LTL develops at an uneven pace across academic terms and that it exhibits different patterns in online as compared to face-to-face delivery methods.
| Type: | Book chapter |
|---|---|
| Title: | Mind the Gap: From Typical LMS Traces to Learning to Learn Journeys |
| ISBN-13: | 9781799896449 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.4018/978-1-7998-9644-9.ch001 |
| Publisher version: | http://doi.org/10.4018/978-1-7998-9644-9.ch001 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Clickstream, Clustering, Data Collection, Higher Education, Hybrid Analysis, Learning Analytics, Learning Management System, Learning to Learn, Ontology, Process Mining |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media UCL > Provost and Vice Provost Offices > School of Education UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10144816 |
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