Which log variables significantly predict academic achievement? A systematic review and meta‐analysis

Abstract

Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance. Previous studies have provided empirical evidence that not all log variables were significantly associated with student academic achievement and the relationships varied across courses. Therefore, this study employs a systematic review with meta-analysis method to provide a comprehensive review of the log variables that have an impact on student academic achievement. We searched six databases and reviewed 88 relevant empirical studies published from 2010 to 2021 for an in-depth analysis. The results show different types of log variables and the learning contexts investigated in the reviewed studies. We also included four moderating factors to do moderator analyses. A further significance test was performed to test the difference of effect size among different types of log variables. Limitations and future research expectations are provided subsequently.

Leveraging Performance and Feedback-seeking Indicators from an Online Platform for Early Prediction of Students’ Learning Outcomes

“…Previous research has attempted to determine how variation in clickstream data from students' use of an online course management system are linked to student learning in an online course (see Wang & Mousavi, 2022). Past research has found that undergraduate students engaged in a large online course with higher self-regulated learning skills tended to revisit previously studied course content, particularly course assessments (Kizilcec et al, 2017).…”

Learning analytics and assessment: Emerging research trends, promises and future opportunities

“…The remaining two articles in this group report on systematic literature reviews of log data used to assess different learning processes. Wang and Mousavi (2022) reviewed empirical studies that leveraged student log data in different learning contexts and conducted a meta‐analysis to quantitatively determine the impact of different log data types on student academic achievement. Wang et al (2022) reviewed studies that leveraged log data gathered in open‐ended learning environments to describe learners' inquiry and problem‐solving processes.…”

Analysis of the utilization of the Learning Management System (LMS) as a learning media in the Physics Education Department Universitas Syiah Kuala

“…They acknowledged that LMS can collect vast data related to students' learning activities, engagement, and performance within the platform. This data can be analyzed to identify patterns and trends that might offer insights into students' progress and academic achievements [16]. However, the lecturers also highlighted that while LMS can provide valuable data, it should not be solely relied upon to predict students'performance.…”

“…However, the lecturers also highlighted that while LMS can provide valuable data, it should not be solely relied upon to predict students'performance. They emphasized the importance of considering other factors influencing a student's success, such as their personal circumstances, learning style, and external support systems [16].…”