Learning analytics of the relationships among self-regulated learning, learning behaviors, and learning performance

Masanori Yamada,Hiroaki Ogata,Kentaro Kojima,Misato Oi,Fumiya Okubo,Atsushi Shimada

doi:10.1186/s41039-017-0053-9

Masanori Yamada, Hiroaki Ogata + Show 4 more

Open Access

https://doi.org/10.1186/s41039-017-0053-9

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Abstract

This research aims to investigate the relationship between self-regulated learning awareness, learning behaviors, and learning performance in ubiquitous learning environments. In order to conduct this research, psychometric data about self-regulated learning and log data, such as slide pages that learners read, marker, and annotate, was collected. The accessing activity of device types that stored the learning management system was collected and analyzed by applying path analysis and correlation analysis using data divided into high and low performers. The results indicated that the slide pages which learners read for a duration of between 240 and 299 s had positive effects on the promotion of annotation and the learning performance directly, and albeit indirectly, the enhancement of self-efficacy was affected by other self-regulated learning factors. The results of the correlation analysis indicated that self-efficacy and test anxiety are a key factor that has different effects on the number of the read slide pages in both high and low performers.

Highlights

Learning analytics is a key subject in educational research all over the world as the findings of learning analytics studies can be applied to improve education, create learning support services, and establish learning models, among other improvements (Gray et al 2014)
As a result, using learning logs on the learning support system, this study investigated the effects of reading time per page of the learning material on the use of learning strategies, self-regulated learning (SRL) awareness, and learning performance
This research investigated the relationship between SRL factors, learning behaviors, and learning performance

Summary

Introduction

Learning analytics is a key subject in educational research all over the world as the findings of learning analytics studies can be applied to improve education, create learning support services, and establish learning models, among other improvements (Gray et al 2014). One of the key issues in learning analytics is to collect learning logs using information and communication technologies (ICTs). As ICT advances, the methods of data collection become more various, in particular ubiquitous technologies (Yin et al 2014). Ubiquitous technologies allow us to collect access logs and location data. Psychometric data as well as learning logs should be collected in order to analyze learners’ behaviors for the provision of effective learning support, especially learning styles such as self-regulated learning (SRL) which are thought to be helpful. SRL is closely linked to the concept of autonomy, in the aspects of metacognition, motivation, and learning behavior (Schunk and Zimmerman 1998; Zimmerman 1986), which enables learners to take responsibility for their own learning

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