Is conceptualized as a process of improvement in the self-regulated learning (SRL) abilities of students.
Published in Chapter:
Mind the Gap: From Typical LMS Traces to Learning to Learn Journeys
Carmel Kent (The Open University, UK), Abayomi Akanji (EDUCATE Ventures Research, UK), Benedict du Boulay (EDUCATE Ventures Research, UK), Ibrahim Bashir (EDUCATE Ventures Research, UK), Thomas G. Fikes (Arizona State University, USA), Sue A. Rodríguez De Jesús (Arizona State University, USA), Alysha Ramirez Hall (Arizona State University, USA), Paul Alvarado (Arizona State University, USA), Jennifer E. Jones (Arizona State University, USA), Mutlu Cukurova (University College London, UK), Varshita Sher (EDUCATE Ventures Research, UK), Canan Blake (University College London, UK), Arthur Fisher (EDUCATE Ventures Research, UK), Juliet Greenwood (Arizona State University, USA), and Rosemary Luckin (University College London, UK)
Copyright: © 2022
|Pages: 26
DOI: 10.4018/978-1-7998-9644-9.ch001
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.