This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…

Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…

This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…

This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

The 2015 reauthorization of the Elementary and Secondary Education Act placed a 1.0% cap on the participation of students with disabilities in the alternate assessment based on alternate academic achievement standards (AA-AAAS). U.S. Department of Education regulations clarified that states must develop participation guidelines and a definition of…

This study demonstrates how to evaluate a university-wide online course designed to support student transition into university by using Propensity Score Matching (PSM) and Doubly Robust Estimation (DRE). Using data from seven academic years, from 2016/17 to 2022/23, with more than 28,000 students, we examine whether enrolment in this optional…

This study investigated the mediated distributed leadership effects on student achievement through teacher job satisfaction and disciplinary climate in Turkish high schools. We employed school-, teacher-, and student-level datasets drawn from the 2018 PISA and TALIS datasets and performed a multilevel structural equation model (MSEM). The results…

Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…

Data ethics have emerged as an essential topic in education. Educators must know how to use data effectively and responsibly. This is a complex and systemic issue that involves bringing awareness to all stakeholders, building human capacity, modifying policy, and considering equitable solutions to data use. This article posits an initial framework…

Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…

Information and communication technology (ICT) has become an essential part of the daily lives of tertiary students. However, research into assessing digital competency and its effects on academic performance is still limited. This paper explores students' needs for digital competence, the impact of digital access on academic performance, and the…

With the advent of closed-circuit television systems (CCTV) in the era of technology, a massive amount of video data is generated daily. CCTV are installed at several educational institutions to monitor students' behavior and ensure their safety. Human activity monitoring is done manually. Abnormal human actions refer to rare or unusual actions in…

Business analytics is an emerging and prominent tool in many industries seeking to exploit the advantages of data-driven decision making. Simultaneously, educational institutions are developing and delivering business analytics offerings to equip business professionals with the tools necessary to implement business analytics in modern businesses.…

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…