In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…

Self-regulated learning (SRL) is a prerequisite for successful learning. However, studies have reported that many students struggle with self-regulation in online learning, indicating the need to provide students with additional support for SRL. This study adopted a design-based research methodology to iteratively design, implement, and evaluate…

The use of generative artificial intelligence (Gen-AI) to assist college students in their studies has become a trend. However, there is no academic consensus on whether Gen-AI can enhance the academic achievement of college students. Using a meta-analytic approach, this study aims to investigate the effectiveness of Gen-AI in improving the…

In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…

An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…

Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…

This essay critiques the emphasis on detecting artificial intelligence (AI) usage in student submissions and advocates for a shift towards the meaningful integration of AI in education. Citing data from Turnitin, it highlights the significant yet understated prevalence of AI in academic work. The discussion underscores the ideological, detection,…

Artificial intelligence technology has become widely used in many industries, including healthcare, agriculture, banking, social security, and home furnishings, due to the rise and development of this discipline. One of the newest areas of technology in the education industry is AI in Education, where extensive research supports instructional…

Mobile learning (M-learning), ChatGPT and social media are integral to university education, improving accessibility, personalization and interactive engagement in the learning process. This paper aimed to investigate the role of M-learning, ChatGPT and social media in university students' academic performance. It was a cross-sectional…

A growing number of educators expect that artificial intelligence (AI) will augment students' capacities and rapidly transform the teaching and learning practice. However, there is a lack of convincing evidence on the effects of Student-AI Collaboration (SAC) on a learning task's performance. A critical examination of the effects on students'…

This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided…

Educational institutions are creating a considerable amount of data regarding students, faculty and related organs. This data is an essential asset for academic institutions as it has valuable insights, knowledge and intelligence for the policymakers. Students are the fundamental entities and primary source of data creation in any educational…

This study aimed to understand the relationship between course activities and learning progress among students enrolled in the MicroMasters certificate program offered in an affordable MOOC-based learning platform. In order to capture the relationship, the differences between the engagement patterns of learners in the MicroMasters program compared…

The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…

Educational data mining (DEM) provides valuable educational information by applying data mining tools and techniques to analyze data at educational institutions. In this paper, tree-based machine learning algorithms are used to predict students' overall academic performance in their bachelor's program. The transcript data of the students in the…