Learning Analytics to Reveal Links Between Learning Design and Self-Regulated Learning

Yizhou Fan,Nora’Ayu Ahmad Uzir,Dragan Gašević,Qiong Wang,Wannisa Matcha

doi:10.1007/s40593-021-00249-z

Abstract

The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of learning analytics (LA), shows that SRL skills are best exhibited in choices of learning tactics that are reflective of metacognitive control and monitoring. However, in spite of high significance for evaluation of learning experience, the link between learning design and learning tactics has been under-explored. In order to fill this gap, this paper proposes a novel learning analytic method that combines three data analytic techniques, including a cluster analysis, a process mining technique, and an epistemic network analysis. The proposed method was applied to a dataset collected in a massive open online course (MOOC) on teaching in flipped classrooms which was offered on a Chinese MOOC platform to pre- and in-service teachers. The results showed that the application of the approach detected four learning tactics (Search oriented, Content and assessment oriented, Content oriented and Assessment oriented) which were used by MOOC learners. The analysis of tactics’ usage across learning sessions revealed that learners from different performance groups had different priorities. The study also showed that learning tactics shaped by instructional cues were embedded in different units of study in MOOC. The learners from a high-performance group showed a high level of regulation through strong alignment of the choices of learning tactics with tasks provided in the learning design. The paper also provides a discussion about implications of research and practice.

Highlights

In the era of rapid knowledge growth, “learning how to learn” has been a prominent phrase in the discourse around educational policy and practice (Black et al 2006)
This paper reported the findings of a study that performed a cluster analysis to detect learning tactics based on time spent on each learning action in order to unveil theoretically meaningful tactics used by massive open online course (MOOC) learners, as part of the attempt to address research question one
The links shown in epistemic network analysis may not be fully sufficient to explain the specifics of the formation process in the use of learning tactics, the findings of this study revealed the links between learning design and learning tactics, which were consistent with the pedagogical intentions of the MOOC design and teaching team

Summary

Introduction

In the era of rapid knowledge growth, “learning how to learn” has been a prominent phrase in the discourse around educational policy and practice (Black et al 2006). Improving self-regulated learning skills is an important task for both MOOC learners and MOOC designers. The development team of the MOOC paid significant attention to the learning design; to cater to the different pedagogical intentions, each unit of the MOOC use different learning resources and offered different learning pathways. It is very important for this MOOC to meet the last criteria, because in order to answer our research questions, the MOOC should be well designed and use suitable and diversified designs for the different topics. Clear evaluation criteria, and sufficient supporting resources in the course design have been found to be positively related to the use of deep learning strategies (Entwistle and Ramsden 2015)

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Conclusion