Research trends in measurement and intervention tools for self-regulated learning for e-learning environments\u2014systematic review (2008\u20132018)

Eric Araka,Robert Oboko,Rhoda Gitonga,Elizaphan Maina

doi:10.1186/s41039-020-00129-5

Abstract

For the last one decade, research in self-regulated learning (SRL) and educational psychology has proliferated. Researchers and educators have focused on how to support leaners grow their SRL skills on both face-to-face and e-learning environments. In addition, recent studies and meta-analysis have greatly contributed to the domain knowledge on the use of SRL strategies and how they contribute and boost academic performance for learners. However, there is little systematic review on the literature on the techniques and tools used to measure SRL on e-learning platforms. This review sought to outline recent advances and the trends in this area to make it more efficient for researchers to establish the empirical studies and research patterns among different studies in the field of SRL. The findings from this study are concurrent with existing empirical evidence that traditional methods designed for classroom supports are being used for measuring SRL on e-learning environments. Few studies have used learner analytics and educational data mining (EDM) techniques to measure and promote SRL strategies for learners. The paper finally points out the existing gaps with the tools presently used to measure and support SRL on learning management systems and recommends further studies on the areas of EDM which can support SRL.

Highlights

Educational environments fall along a continuum from physical classroom where faceto-face interactions are common to fully online learning environments where asynchronous interactions are the default
In terms of the type and source of data used for self-regulated learning (SRL) measurement or intervention, 16 out of the 30 studies used self-report tools such as structured questionnaires and interviews to measure the level of SRL skills in learners while 9 studies analyzed log data extracted from educational learning environments such as massive open online courses (MOOCs) or learning management systems (LMS) to establish the levels of SRL for each learner
This study identified an observational trend that the use of learning analytics and educational data mining (EDM) in measuring and promoting SRL has started to emerge and advancing, literature indicates that there is continued use of self-report tools that were originally created for the traditional face-to-face classroom set-up

Summary

Introduction

Educational environments fall along a continuum from physical classroom where faceto-face interactions are common to fully online learning environments where asynchronous interactions are the default. This continuum of educational environments has provided opportunities for blended and web facilitated courses where learning materials and student-instructor interactions are delivered online with little or no face-toface meetings (Allen & Seaman, 2013). There is a recognized shift towards technology supported learning commonly known as e-learning with most of institutions of higher learning adopting elearning for fully online courses or complementary to the face-to-face sessions in blended learning approach in order to curb the challenge of large backlog of students to be admitted (Hadullo, Oboko, & Omwenga, 2018; Luna, Castro, & Romero, 2017). MOOCs are defined as open education systems for open and distance learning where students register for courses with limited admission restrictions such as prerequisite courses and selection criteria

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