Utilising learning analytics to support study success in higher education: a systematic review

D Ifenthaler, JYK Yau - Educational Technology Research and …, 2020 - Springer
Study success includes the successful completion of a first degree in higher education to the
largest extent, and the successful completion of individual learning tasks to the smallest …

A systematic review on trends in using Moodle for teaching and learning

SHPW Gamage, JR Ayres, MB Behrend - International journal of STEM …, 2022 - Springer
Abstract Background The Moodle Learning Management System (LMS) is widely used in
online teaching and learning, especially in STEM education. However, educational research …

Educational data mining: prediction of students' academic performance using machine learning algorithms

M Yağcı - Smart Learning Environments, 2022 - Springer
Educational data mining has become an effective tool for exploring the hidden relationships
in educational data and predicting students' academic achievements. This study proposes a …

Analyzing and predicting students' performance by means of machine learning: A review

JL Rastrollo-Guerrero, JA Gómez-Pulido… - Applied sciences, 2020 - mdpi.com
Predicting students' performance is one of the most important topics for learning contexts
such as schools and universities, since it helps to design effective mechanisms that improve …

[HTML][HTML] The longitudinal association between engagement and achievement varies by time, students' profiles, and achievement state: A full program study

M Saqr, S López-Pernas, S Helske, S Hrastinski - Computers & Education, 2023 - Elsevier
There is a paucity of longitudinal studies in online learning across courses or throughout
programs. Our study intends to add to this emerging body of research by analyzing the …

Student retention using educational data mining and predictive analytics: a systematic literature review

DA Shafiq, M Marjani, RAA Habeeb… - IEEE Access, 2022 - ieeexplore.ieee.org
Student retention is an essential measurement metric in education, indicated by retention
rates, which are accumulated as students re-enroll from one academic year to the next. High …

Predicting student performance in higher educational institutions using video learning analytics and data mining techniques

R Hasan, S Palaniappan, S Mahmood, A Abbas… - Applied Sciences, 2020 - mdpi.com
Technology and innovation empower higher educational institutions (HEI) to use different
types of learning systems—video learning is one such system. Analyzing the footprints left …

[HTML][HTML] Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic success

J Jovanović, M Saqr, S Joksimović, D Gašević - Computers & Education, 2021 - Elsevier
Predictive modelling of academic success and retention has been a key research theme in
Learning Analytics. While the initial work on predictive modelling was focused on the …

Effectiveness of blended learning in nursing education

MC Sáiz-Manzanares, MC Escolar-Llamazares… - International journal of …, 2020 - mdpi.com
Currently, teaching in higher education is being heavily developed by learning management
systems that record the learning behaviour of both students and teachers. The use of …

Predictive power of regularity of pre-class activities in a flipped classroom

J Jovanovic, N Mirriahi, D Gašević, S Dawson… - Computers & …, 2019 - Elsevier
Flipped classroom (FC) is an active learning design requiring students to complete assigned
pre-class learning activities in preparation for face-to-face sessions. Students' timely …