Selecting Machine Learning Models for Student Performance Prediction Aligned with Pedagogical Objectives

• 主要な著者: Khan I., Zabil M.H.M., Ahmad A.R., Jabeur N.
• その他の著者: 58061521900
• フォーマット: Conference Paper
• 出版事項: Institute of Electrical and Electronics Engineers Inc. 2024
• 主題: Machine Learning; Sensitivity; Specificity; Students' Performance Prediction; Classification (of information); Forecasting; Machine learning; Learning classifiers; Machine learning models; Machine-learning; Performance prediction; Prediction modelling; Student performance; Student' performance prediction; Training dataset; Students

Machine learning classifiers emerge as productive tools to develop prediction models which forecast the final outcome of the students, in a course, and provide an opportunity to the instructor to take appropriate measures. A single prediction model may not be enough to achieve all the objectives of...