Towards a methodological framework for sequence analysis in the field of self-regulated learning

Abstract

In recent decades, conceptualizations and operationalizations of self-regulated learning (SRL) have shifted from SRL as an aptitude to SRL as an event. Alongside this shift, increased technological capability has introduced computer log files to the investigation of SRL, uncovering new research avenues. One such avenue investigates the time-related characteristics of SRL through learners’ behavioural sequences. Although sequence analysis is still relatively new in SRL research, other fields have fruitful traditions in its application and may serve as a basis for applications in the field of SRL. Ten years of investigating SRL through sequence analysis have produced a wide range of methodological approaches. While this variety of methods illustrates the diversity of opportunities, it also indicates the lack of consensus regarding the most appropriate approaches often resulting in difficult to understand methods and non-transparent ways of reporting. Since the introduction of sequence analysis in the field of SRL, researchers have been emphasizing the need for a methodological framework to guide its application. Yet, to date, no such framework has been proposed, hindering our progress through (1) transparent methods and (2) comparative studies to (3) empirical and ecological applications. To help overcome this issue, this manuscript discusses the basis of a methodological framework for the use of sequence analysis in SRL research. We first make a case for why such a framework is necessary; secondly, we propose a set of guidelines which could serve as a starting point for the construction of a framework.