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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
Göktepe Yildiz, Sevda; Göktepe Körpeoglu, Seda – Education and Information Technologies, 2023
Traditionally, students' various educational characteristics are evaluated according to the grades they get or the results of their answers to the scales. There are some limitations in making an evaluation based on the results. The fuzzy logic approach, which tries to eliminate these limitations, has recently been used in the field of education.…
Descriptors: Foreign Countries, Students, Student Attitudes, Problem Solving
Sánchez-Fernández, Magdalena; Borda-Mas, Mercedes – Education and Information Technologies, 2023
University students are a high-risk population with problematic online behaviours that include generalized problematic Internet/smartphone use and specific problematic Internet uses (for example, social media or gaming). The study of their predictive factors is needed in order to develop preventative strategies. This systematic review aims to…
Descriptors: College Students, Student Behavior, Telecommunications, Handheld Devices
