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Map** artificial intelligence in education research: A network‐based keyword analysis
In this study, we review 1830 research articles on artificial intelligence in education (AIED),
with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary …
with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary …
[HTML][HTML] Predicting student's dropout in university classes using two-layer ensemble machine learning approach: A novel stacked generalization
Student dropout is a serious problem globally. It affects not only the individual who drops out
but also the former school, family, and society in general. With the current development of …
but also the former school, family, and society in general. With the current development of …
A systematic review for MOOC dropout prediction from the perspective of machine learning
J Chen, B Fang, H Zhang, X Xue - Interactive Learning …, 2024 - Taylor & Francis
High dropout rate exists universally in massive open online courses (MOOCs) due to the
separation of teachers and learners in space and time. Dropout prediction using the …
separation of teachers and learners in space and time. Dropout prediction using the …
Towards predicting student's dropout in university courses using different machine learning techniques
J Kabathova, M Drlik - Applied Sciences, 2021 - mdpi.com
Featured Application The found model with the best values of the performance metrics,
found as the result of comparing several machine learning classifiers, can identify students …
found as the result of comparing several machine learning classifiers, can identify students …
Analysis of the factors influencing learners' performance prediction with learning analytics
The advancement of learning analytics has enabled the development of predictive models to
forecast learners' behaviors and outcomes (eg, performance). However, many of these …
forecast learners' behaviors and outcomes (eg, performance). However, many of these …
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 …
Early dropout prediction in online learning of university using machine learning
HS Park, SJ Yoo - JOIV: International Journal on Informatics Visualization, 2021 - joiv.org
Recently, most universities plan to open or open online learning courses, but the problem
of dropout of online learning is still a problem for universities. Online learning has the …
of dropout of online learning is still a problem for universities. Online learning has the …
Time-on-task metrics for predicting performance
Time-on-task is one key contributor to learning. However, how time-on-task is measured
often varies, and is limited by the available data. In this work, we study two different time-on …
often varies, and is limited by the available data. In this work, we study two different time-on …
Early dropout prediction for programming courses supported by online judges
Many educational institutions have been using online judges in programming classes,
amongst others, to provide faster feedback for students and to reduce the teacher's …
amongst others, to provide faster feedback for students and to reduce the teacher's …
[PDF][PDF] Improving dropout forecasting during the COVID-19 pandemic through feature selection and multilayer perceptron neural network
Nowadays, online education in universities is mature from the situation of COVID-19 spread.
It has greatly changed the learning environment in the classroom and has also resulted in …
It has greatly changed the learning environment in the classroom and has also resulted in …