The use of educational data mining and machine learning to analyse large data sets collected by educational institutions has the potential to discover valuable insights for decision-making. One such area that has gained attention is to predict student performance by analysing large educational data sets. In the relevant literature, many studies…

Learning processes can now be transferred to digital environments, allowing for the tracking of learners' digital footprints. The field of learning analytics focuses on the efficient use of these digital records to improve both learning experiences and processes. Dashboards are the tangible outputs of learning analytics. The use of dashboards in…

The evolution of individual and global learning preferences is influenced by correlation factors. This study introduces a novel evolutionary modeling approach to observe and analyze factors that affect the evolution of learning preferences. The influencing factors considered in this study are closely interwoven with the underlying personality of…

Personalized learning (PL) is a student-centered instructional approach in which learning goals, pacing, content, and environments are customized to address individual student needs (Bernacki et al., 2021; Ellis, 2009; Lee, 2014; Miliband, 2006; Office of Educational Technology, 2010; Sota, 2016; Zhang et al., 2020). In grades K-12, PL has been…

Although the fields of educational data mining and learning analytics have grown significantly in terms of analytical sophistication and the breadth of applications, the impact on theory-building has been limited. To move these fields forward, studies should not only be driven by learning theories, but should also use analytics to in form and…

In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…

Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

Interpersonal online interactions are key to digital learning pedagogies and student experiences. Researchers use learner log and text data collected by technologies that mediate learner interactions online to provide indicators about interpersonal interactions. However, analytical approaches used to derive these indicators face conceptual,…

The effective use of self-regulation strategies has been considered significant in online learning environments. It is known that learners must be supported in this context. Academic help-seeking (AHS), as one of the main self-regulated learning strategies, is associated with academic success. However, learners may avoid seeking help for…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers' data-driven pedagogical decision-making. While many LADs have been designed, teachers' capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a…

Purpose: The main argument behind this paper is learning in the digital age should not be restricted to creating digital infrastructures for supporting current forms of learning nor taking schools in their current form as God-given, natural entities, but changing current forms of education by developing new frameworks and socio-technical…

Interactions among students in online learning environments are difficult to monitor but can be crucial for their academic performance. Moodle is one of the best and most popular online learning platforms, where its log records can reveal important information on students' engagement and the respective performance. This study examines the degree…

The application of learning analytics in an online learning environment is increasing among researchers in educational fields because it can assist in providing standard and measurable decision making about student success. In this regard, there is a need for the online learning society and practitioners to be informed about how learning analytics…

A lot of studies have shown that there is an "inverse U-curve" relationship between learners' grades and cognitive load. Learners' grades are closely related to their learning behavior characteristics on online learning. Is there any relationship between online learners' behavior characteristics and cognitive load? Based on this, the…