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…

Online supplementary education has been prevalent in recent years due to the advent of technology (e.g., live streaming) and the COVID-19 pandemic. However, the performance of students in this mode of education varies greatly, and the underlying reasons are yet to be investigated. This study aims to understand the impact of various factors and…

A neurological disorder, along with several behavioral issues, may be to blame for a child's subpar performance in the academic journey (such as anxiety, depression, learning disorders, and irritability). These symptoms can be used to diagnose children with ASD, and supervised machine learning models can help differentiate between ASD traits and…

Recent progress in artificial intelligence (AI) has aroused interest in the growth and development of educational AI tools (EAITs). Teachers' adoption of EAITs in classrooms has helped in shaping instructional decisions taken by them in an attempt to promote intelligently and actively students' meaningful learning of contents areas. Nevertheless,…

Artificial intelligence (AI) has the potential to support self-regulated learning (SRL) because of its strong anthropomorphic characteristics. However, most studies of AI in education have focused on cognitive outcomes in higher education, and little research has examined how psychological needs affect SRL with AI in the K-12 setting. SRL is a…

Journalism is a highly technology-dependent profession, and students, educators, and professionals must develop specific digital skills. This study uses the theory of disruptive innovation to examine how journalism educators adapt their programs in response to changing media environments. A survey of accredited journalism and mass communication…

As generative artificial intelligence (GenAI) increasingly penetrates language education, understanding learners' continued intention to use this technology becomes crucial. This study examines EFL learners' continuance intention to use GenAI for language learning through PLS-SEM and fsQCA methodologies. Participants were undergraduate EFL…

As artificial intelligence (AI) advances rapidly, it has been incorporated into formal education to facilitate subject-based learning. Integration of AI technologies to support learning requires teachers to intentionally design AI-assisted learning. However, there have been a limited number of empirical studies investigating teachers' behavioural…

This study addresses the challenge of teaching genetics effectively to high school students, a topic known to be particularly challenging. Leveraging the growing importance of artificial intelligence (AI) in education, the research explores the perspectives, attitudes, and behavioral intentions of pre-service teachers regarding the integration of…

Recent trends in "educational technology" have led to emergence of methods such as teaching analytics (TA) in understanding and management of the teaching-learning processes. Didactically, "teaching analytics" is one of the promising and emerging methods within the Education domain that have proved to be useful, towards…

Lack of student persistence and retention is significantly hurting the US in producing the required number of qualified graduates, especially in STEM fields. Although many factors contribute to students falling off track, one of the controllable factors is the identification of at-risk students followed by early intervention. Predicting the…

Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…

This study aimed to employ machine learning techniques to uncover the pivotal determinants influencing the reading proficiency of fourth-grade students across 65 regions, as participants in the PIRLS 2021 assessment. The primary objective was to discern and assess key factors at the student, family and school levels that predict high and low…

Large-scale international studies offer researchers a rich source of data to examine the relationship among variables. Machine learning embodies a range of flexible statistical procedures to identify key indicators of a response variable among a collection of hundreds or even thousands of potential predictor variables. Among these, penalized…

The purpose of this study is to classify the predictors of satisfaction and intention to use in Massive Open Online Courses (MOOC). Informed by a scientific literature review, this work poses a behavioral model to explain intention to use via various constructs. To this end, the authors have carried out a study through an online survey of Spanish…