NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Academic Performance Prediction Using Machine Learning Approaches: A Survey
Peer reviewed Peer reviewed
Direct linkDirect link
Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
An Evidence and Gap Map on Programs to Tackle School Dropout
Peer reviewed Peer reviewed
Direct linkDirect link
Carmen Pannone; Marta Pellegrini; Daniela Fadda; Amanda J. Neitzel; L. Francesca Scalas; Giuliano Vivanet; Ylenia Falzone – Society for Research on Educational Effectiveness, 2024
Background: Education plays a pivotal role in empowering individuals with the knowledge and skills needed for careers, economic progress, and societal engagement. Dropping out of school before achieving a qualification undermines these opportunities and has an impact on individuals and society (Audit Commission, 2010; OECD, 2023). International…
Descriptors: Elementary Secondary Education, Dropout Prevention, Dropout Programs, Dropout Rate
Contextualisation of Predictor Variables for Students' At-Risk of Dropping Out of University
Peer reviewed Peer reviewed
Direct linkDirect link
Jongile, Sonwabo – International Journal on E-Learning, 2022
The identification of predictor variables for students at-risk of dropping out of university has received increased attention in higher education settings internationally concerning the context of origin in which they are developed and the different academic context in which they are introduced, often lacking schema-theoretic perspectives to offer…
Descriptors: Predictor Variables, At Risk Students, Potential Dropouts, College Students
The Use of Deep Learning in Open Learning: A Systematic Review (2019 to 2023)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Odiel Estrada-Molina; Juanjo Mena; Alexander López-Padrón – International Review of Research in Open and Distributed Learning, 2024
No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Open Education, Educational Trends
Reported Benefits of Yoga in High Schools: A Review of the Literature
Peer reviewed Peer reviewed
Direct linkDirect link
Caldarella, Paul; Rajesh Lulla, Saanya – Education, 2022
High school is a time of changes in adolescents' physical, psychological, social, and sexual development, often resulting in stress and anxiety. Adolescents are particularly vulnerable to mental health problems. Yoga is an Indian discipline practiced globally for health and relaxation. School-based yoga programs are becoming increasingly common…
Descriptors: High School Students, Adolescents, Physical Activities, Mental Health
Disengaged and Nearing Departure: Students at Risk for Dropping out in the Age of COVID-19
Peer reviewed Peer reviewed
Direct linkDirect link
Antoni, Jennifer – Planning and Changing, 2021
The purpose of this review article was to examine the turbulence of the current educational context in light of COVID-19 and the associated school closures, for disengaged high school students, often over-aged, who are nearing the end of their academic journeys. In this review, I provide a concise overview of the way that the high school dropout…
Descriptors: Learner Engagement, At Risk Students, High School Students, Student Experience