Student performance analysis and prediction in classroom learning: A review of educational data mining studies
Student performance modelling is one of the challenging and popular research topics in
educational data mining (EDM). Multiple factors influence the performance in non-linear …
educational data mining (EDM). Multiple factors influence the performance in non-linear …
[HTML][HTML] A systematic review of artificial intelligence techniques for collaborative learning over the past two decades
This systematic review focuses on publications related to studies of the use of artificial
intelligence (AI) for collaborative learning. The use of AI for collaborative learning is a recent …
intelligence (AI) for collaborative learning. The use of AI for collaborative learning is a recent …
Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced
computing technologies, AI performance prediction model is widely used to identify at-risk …
computing technologies, AI performance prediction model is widely used to identify at-risk …
Predicting at-risk students at different percentages of course length for early intervention using machine learning models
Online learning platforms such as Massive Open Online Course (MOOC), Virtual Learning
Environments (VLEs), and Learning Management Systems (LMS) facilitate thousands or …
Environments (VLEs), and Learning Management Systems (LMS) facilitate thousands or …
The role of demographics in online learning; A decision tree based approach
Research has shown online learners' performance to have a strong association with their
demographic characteristics, such as regional belonging, socio-economic standing …
demographic characteristics, such as regional belonging, socio-economic standing …
[HTML][HTML] Individuals in a group: Metacognitive and regulatory predictors of learning achievement in collaborative learning
Self-regulated learning theory acknowledges the importance of an individual's
metacognitive monitoring and group-level regulation for learning achievement in …
metacognitive monitoring and group-level regulation for learning achievement in …
The influences of an experienced instructor's discussion design and facilitation on an online learning community development: A social network analysis study
F Ouyang, C Scharber - The Internet and Higher Education, 2017 - Elsevier
Instructors' discussion design and facilitation have critical influences on online learning
community development. Emerging network analysis methods were used to examine the …
community development. Emerging network analysis methods were used to examine the …
A study on academic staff personality and technology acceptance: The case of communication and collaboration applications
Over the recent years, the communication and collaboration based on online applications
has been ubiquitous, being used in teaching, learning and research. In this context, the …
has been ubiquitous, being used in teaching, learning and research. In this context, the …
Practical early prediction of students' performance using machine learning and eXplainable AI
Predicting students' performance in advance could help assist the learning process; if “at-
risk” students can be identified early on, educators can provide them with the necessary …
risk” students can be identified early on, educators can provide them with the necessary …
Predicting student dropout in self-paced MOOC course using random forest model
A significant problem in Massive Open Online Courses (MOOCs) is the high rate of student
dropout in these courses. An effective student dropout prediction model of MOOC courses …
dropout in these courses. An effective student dropout prediction model of MOOC courses …