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Direct linkAshima Kukkar; Rajni Mohana; Aman Sharma; Anand Nayyar – Education and Information Technologies, 2024
In the profession of education, predicting students' academic success is an essential responsibility. This study introduces a novel methodology for predicting students' pass or fail outcome in certain courses. The system utilises academic, demographic, emotional, and VLE sequence information of students. Traditional prediction methods often…
Descriptors: Predictor Variables, Academic Achievement, Pass Fail Grading, Long Term Memory
Gil, Paulo Diniz; da Cruz Martins, Susana; Moro, Sérgio; Costa, Joana Martinho – Education and Information Technologies, 2021
This study presents a data mining approach to predict academic success of the first-year students. A dataset of 10 academic years for first-year bachelor's degrees from a Portuguese Higher Institution (N = 9652) has been analysed. Features' selection resulted in a characterising set of 68 features, encompassing socio-demographic, social origin,…
Descriptors: Data Use, Decision Making, Predictor Variables, Academic Achievement
Roslan, Muhammad Haziq Bin; Chen, Chwen Jen – Education and Information Technologies, 2023
This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…
Descriptors: Foreign Countries, Secondary School Students, Academic Achievement, English Instruction
