Educational data mining techniques for student performance prediction: method review and comparison analysis
Y Zhang, Y Yun, R An, J Cui, H Dai… - Frontiers in psychology, 2021 - frontiersin.org
Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
Educational anomaly analytics: features, methods, and challenges
Anomalies in education affect the personal careers of students and universities' retention
rates. Understanding the laws behind educational anomalies promotes the development of …
rates. Understanding the laws behind educational anomalies promotes the development of …
Predicting first-time-in-college students' degree completion outcomes
About one-third of college students drop out before finishing their degree. The majority of
those remaining will take longer than 4 years to complete their degree at “4-year” …
those remaining will take longer than 4 years to complete their degree at “4-year” …
Student's performance prediction model and affecting factors using classification techniques
A Hussain, M Khan, K Ullah - Education and Information Technologies, 2022 - Springer
Educational institutions are creating a considerable amount of data regarding students,
faculty and related organs. This data is an essential asset for academic institutions as it has …
faculty and related organs. This data is an essential asset for academic institutions as it has …
Clustering-based EMT model for predicting student performance
Predicting students' performance has emerged as an attractive task among researchers.
They use supervised and unsupervised educational data mining (EDM) techniques to build …
They use supervised and unsupervised educational data mining (EDM) techniques to build …
Analysis of Machine Learning Classification Approaches for Predicting Students' Programming Aptitude
A Çetinkaya, ÖK Baykan, H Kırgız - Sustainability, 2023 - mdpi.com
With the increasing prevalence and significance of computer programming, a crucial
challenge that lies ahead of teachers and parents is to identify students adept at computer …
challenge that lies ahead of teachers and parents is to identify students adept at computer …
Performing learning analytics via generalised mixed-effects trees
Nowadays, the importance of educational data mining and learning analytics in higher
education institutions is being recognised. The analysis of university careers and of student …
education institutions is being recognised. The analysis of university careers and of student …
Integrating nearest neighbors with neural network models for treatment effect estimation
N Kiriakidou, C Diou - arXiv preprint arXiv:2305.06789, 2023 - arxiv.org
Treatment effect estimation is of high-importance for both researchers and practitioners
across many scientific and industrial domains. The abundance of observational data makes …
across many scientific and industrial domains. The abundance of observational data makes …
Decision support software for forecasting patient's length of stay
Length of stay of hospitalized patients is generally considered to be a significant and critical
factor for healthcare policy planning which consequently affects the hospital management …
factor for healthcare policy planning which consequently affects the hospital management …
[PDF][PDF] Prediction of student's performance using support vector machine classifier
Analyzing students' performances based on both subjective and quantitative components is
fundamental because sometimes these performances and so many other factors have led …
fundamental because sometimes these performances and so many other factors have led …