College students in the 21st century face unprecedented levels of stress, which has led to a global and deleterious impact on their mental health. The mental health of college students is widely considered to be a public health crisis according to the World Health Organization (WHO), and universities are challenged to provide adequate resources…

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…

Co-teaching and related collaborative models of instruction are widely used in primary and secondary schools in many school systems. This systematic review and meta-analysis investigated the effects of such models on students' academic achievement and how these effects are moderated by factors of theoretical and practical relevance. Although…

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…

Academic burnout seriously affects the academic performance and mental health of college students. This study developed a multi-mediation model to investigate the relationship between academic self-efficacy and academic burnout. A total of 1431 undergraduate students (51.85% female) were recruited to participate in this study. And we used SPSS…

This cluster-randomised study investigated the effects of a Norwegian early warning system, the IKO model. IKO is a Norwegian acronym for identification, assessment, and follow-up, and the model aims to improve schools' abilities to identify and support students who are at risk of dropping out during the school year. The study involved 7677…

In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…

As science, technology, engineering, and mathematics (STEM) scholars, educators, and students themselves, the authors have collectively been involved in trying to promote student success in STEM for many years. As they analyzed data from a STEM student retention program, they explored aspects of the student retention literature, finding that there…

Advising programs for undecided/exploratory students risk reinvention of the wheel through lack of familiarity with existing literature. This lack can also leave the scholar and the practitioner unable to identify potential gaps within the research. Applying the methodological approach of qualitative historiography to literature from 1950 to 2022,…

Current theoretical and operational definitions of underachievement require that students show sustained suppressed academic achievement. Yet, early detection may allow for effective intervention before underachievement becomes a chronic issue. While existing identification procedures were not designed to detect underachievement before low…

Fourteen empirical studies on academic burnout were synthesized and reviewed with a meta-analytic approach based on the framework of job demand, control, support model. It was found that demand, control, and support were associated with academic burnout. The three dimensions of burnout were negatively related to demand and positively related to…

Many children start school developmentally vulnerable and struggle to keep up with their peers. Children experiencing socioeconomic-disadvantage are at higher risk of poor developmental outcomes. A high-quality education and wrap-around community-service model, such as the Doveton Model, at Doveton College, Australia, may improve outcomes for…

Despite the significance of grit and motivational regulation strategies (MRS) to language learning, limited research has been conducted on their longitudinal interplay. The present study explores the relationship between these two constructs in an English as a second language (L2) learning context through a longitudinal design. This study utilizes…

Background/purpose: This research aims to examine the effect of a Cognitive-Behavioral Coaching (CBC) model on the academic performance of adolescents with attention deficit hyperactivity disorder (ADHD) and to analyze the relationship between academic performance, self-esteem, and relationship with parents. Materials/methods: The sample comprised…

Converging evidence suggests that traditional domain-general working memory (WM) training does not have reliable far-transfer effects, but produces reliable, modest near-transfer effects on structurally similar untrained tasks. Given the critical role of WM in academic development, WM training that incorporates task-specific features may maximize…