Mind the Gap

Author:

Kent Carmel1,Akanji Abayomi2,du Boulay Benedict2,Bashir Ibrahim2,Fikes Thomas G.3,Rodríguez De Jesús Sue A.3ORCID,Ramirez Hall Alysha3,Alvarado Paul3,Jones Jennifer E.3,Cukurova Mutlu4ORCID,Sher Varshita2,Blake Canan4,Fisher Arthur2,Greenwood Juliet3,Luckin Rosemary4

Affiliation:

1. The Open University, UK

2. EDUCATE Ventures Research, UK

3. Arizona State University, USA

4. University College London, UK

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.

Publisher

IGI Global

Reference44 articles.

1. Baker, R., Ocumpaugh, J., & Andres, A. (2018). BROMP Quantitative Field Observations: A Review. In R. Feldman (Ed.), Learning Science: Theory, Research, and Practice. Academic Press.

2. Berti, A., van Zelst, S. J., & van der Aalst, W. (2019). Process mining for python (PM4Py): bridging the gap between process and data science. arXiv preprint arXiv:1905.06169.

3. Virtual learning environment engagement and learning outcomes at a ‘bricks-and-mortar’ university

4. A control-systems approach to behavioral self regulation;C. S.Carver,1981

5. The Scree Test For The Number Of Factors

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