Background: Undergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer-supported collaborative inquiry approaches, such as KB--the focus of this…

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student's organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student's strategy.…

Big data in education promotes access to the analysis of learning behavior, yielding many valuable analysis results. However, with obscure and insufficient guidelines commonly followed when applying the analysis results, it is difficult to translate information knowledge into actionable strategies for educational practices. This study aimed to…

Learning analytics dashboards (LADs) are often used to display real-time data indicating student learning trajectories and outcomes. Successful use of LADs requires teachers to orient their dashboard reviews with clear goals, apply appropriate strategies to interpret visualized information on LADs and monitor and evaluate their interpretations to…

The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…

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'…

To determine the impact of cognitive style on change of concept of engagement in the flipped classroom, a sequential analysis from the perspective of Bloom's Taxonomy was conducted to establish if significant differences existed between the learning achievements and engagement of students with different cognitive styles. The participants were…

Blended learning (BL) is regarded as an effective strategy for combining traditional face-to-face classroom activities with various types of online learning tools (e.g., e-books). An effective feature of e-books is the ability to use digital notes. When e-books are used in BL, the strategic adoption of note-taking provides benefits that influence…

Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…

Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students' behavior, performance, and…

Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain…

In the learning sciences, heterogeneity among students usually leads to different learning strategies or patterns and may require different types of instructional interventions. Therefore, it is important to investigate student subtyping, which is to group students into subtypes based on their learning patterns. Subtyping from complex student…

Purpose: This study aims to explore Chilean students' digital technology usage patterns and approaches to learning. Design/Approach/Methods: We conducted this study in two stages. We worked with one semester learning management systems (LMS), library, and students' records data in the first one. We performed a k-means cluster analysis to identify…

The purpose of this study was to explore and analyze the utilization of learning analytics data produced by a learning management system as an indicator of learners' self-regulation. In the Spring of 2021, 258 learners at a four-year, mid-Atlantic university provided access to their learning management system data. Of those 258 learners, 86…

For university students, self-regulation of study behaviour is important. However, students are not always capable of effective self-regulation. Providing study behaviour information via a learning analytics dashboard (LAD) may support phases within self-regulated learning (SRL). However, it is unclear what information a LAD should provide, how to…