Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…

In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…

Predicting student performance in international large-scale assessments (ILSAs) is crucial for understanding educational outcomes on a global scale. ILSAs, such as the Program for International Student Assessment and the Trends in International Mathematics and Science Study, serve as vital tools for policymakers, educators, and researchers to…

This study empirically examines the predictive relationship between Institutional Autonomy (IA) and Academic Freedom (AF) whilst controlling for the mediating effect of corporate governance (CG) amongst selected higher education institutions in Ghana. It also looks at the difference between females and males and their perceptions of the predictive…

The fundamental goal of education is to teach students to become self-regulated learners who actively and efficiently manage their learning processes by deploying self-regulated learning strategies. Based on this stance, the present study investigated whether these strategies predicted the writing performance of English major students. Eleven…

Childhood adversity takes a toll on lifelong health. However, investigations of unpredictability as a form of adversity are lacking. Environmental unpredictability across multiple developmental periods and ecological levels was examined using a multiethnic, longitudinal birth cohort (1998-2000) oversampled for unmarried parents. Data were from the…

Non-cognitive factors, such as motivation, have shown to play a significant role in adolescences science learning. However, there is little longitudinal research investigating students' intrinsic motivation in science learning over school years. Based on self-determination theory, this study examines the change in, and associations between,…

Several recommender systems have been proposed to suggest courses to students based on their transcripts. In this paper, we evaluate whether these systems can be generalized to other academic activities, such as research projects and extracurricular activities. We follow previous grade-aware and content-based approaches, where course descriptions…

Prior work has developed a range of automated measures ("detectors") of student self-regulation and engagement from student log data. These measures have been successfully used to make discoveries about student learning. Here, we extend this line of research to an underexplored aspect of self-regulation: students' decisions about when to…

This study examined the effectiveness of online English learning among college students by integrating data from multiple learning behavior sources. The research revealed a bidirectional regulatory relationship between device environment and cognitive strategies, clarified the critical threshold for the regulation of metacognitive strategies, and…

In this study, we examined how variables such as the age of faculty members, autism awareness, and readiness to work with individuals with autism predict their attitudes toward individuals with Autism Spectrum Disorder. This study included 240 faculty members from various faculties. Data were analyzed using stepwise multiple regression analysis.…

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…

Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes.…

The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…

This article focuses on the possible relationship between predictions, developed during the resolution of geometrical tasks within a Paper-and-Pencil Environment (PPE), and subsequent explorations within a Dynamic Geometry Environment (DGE). Building on Fischbein's Theory of Figural Concepts, and to gain insight into the transition of predictions…