Learning Management System (LMS) can track student interactions with digital learning resources during an online learning activity. Learners with different goals, motivations and preferences may exhibit different behaviours when accessing these materials. These different behaviours may further affect their learning performance. The purpose of this…

This study aimed to develop a prediction model to classify students based on their academic procrastination tendencies, which were measured and classified as low and high using a self-report tool developed based on the students' assignment submission behaviours logged in the learning management system's database. The students' temporal learning…

Developed to maximize learning performance, learning analytics dashboards (LAD) are becoming increasingly commonplace in education. An LAD's effectiveness depends on how it is used and varies according to users' academic levels. In this study, two LADs and a learning support system were used in a higher education course to support students'…

Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…

The COVID-19 pandemic precipitated a global shift to fully remote learning via learning management systems (LMS). Despite this significant shift, there has been a paucity of research exploring how students of varying academic performance engage with online learning resources. This study investigates the utilization of LMS among students with…

This empirical study uses a random forest algorithm to examine the factors that influence learners' persistence in online learning at a prominent Korean institution. The data were collected from students who began their studies in Spring 2021, and encompassed a range of variables including individual attributes, academic engagement, academic…

Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…

This study investigates factors that stimulate better academic performance for female students in learning quantitative topics, such as those involving mathematical-related tasks. We explore the differences in self-regulated learning (e.g., sources of motivation and execution of learning strategies), learning behaviors, and learning achievement of…

This study investigates how the course format change caused by covid-19 pandemic affected learning behaviors and performance of college students enrolled in a large introductory history course. Clickstream log files capturing how students were interacting with online learning contents were analyzed to identify the learning behaviors of students…

The study aims to examine student emotions and behavior in a Gamified Learning Environment (GLE) in detail. In the study, in order to reveal the behavior (dynamics) and feelings (emotions) that emerge within the framework of the mechanics applied in the GLE process, it is within the scope of the main objectives of the study to determine how…

One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…

One of the biggest challenges for online learning is upholding academic integrity in online assessments. In particular, institutions and faculties attach importance to exam security and academic dishonesty in the online learning process. The aim of this study was to compare the test-taking behaviors and academic achievements of students in…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

Learning management systems (LMSs) are ubiquitous in higher education, yet few studies have examined changes in student engagement online with year level. Using data mining of LMSs, we examined the frequency and timing with which first, second, and third year science students accessed the various LMS resources. We compared online access with both…