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Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
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Canto, Natalia Gil; de Oliveira, Marcelo Albuquerque; Veroneze, Gabriela de Mattos – European Journal of Educational Research, 2022
The article aims to develop a machine-learning algorithm that can predict student's graduation in the Industrial Engineering course at the Federal University of Amazonas based on their performance data. The methodology makes use of an information package of 364 students with an admission period between 2007 and 2019, considering characteristics…
Descriptors: Engineering Education, Prediction, Graduation, Industrial Arts
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Choi, Ikkyu; Hao, Jiangang; Deane, Paul; Zhang, Mo – ETS Research Report Series, 2021
"Biometrics" are physical or behavioral human characteristics that can be used to identify a person. It is widely known that keystroke or typing dynamics for short, fixed texts (e.g., passwords) could serve as a behavioral biometric. In this study, we investigate whether keystroke data from essay responses can lead to a reliable…
Descriptors: Accuracy, High Stakes Tests, Writing Tests, Benchmarking