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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
Ting Sun; Stella Yun Kim – Educational and Psychological Measurement, 2024
Equating is a statistical procedure used to adjust for the difference in form difficulty such that scores on those forms can be used and interpreted comparably. In practice, however, equating methods are often implemented without considering the extent to which two forms differ in difficulty. The study aims to examine the effect of the magnitude…
Descriptors: Difficulty Level, Data Interpretation, Equated Scores, High School Students
Yan Xia; Selim Havan – Educational and Psychological Measurement, 2024
Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…
Descriptors: Data Interpretation, Factor Analysis, Statistical Inference, Research Problems
Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
Marsela Thanasi-Boçe; Julian Hoxha – Education and Information Technologies, 2024
Entrepreneurship education has evolved to meet the demands of a dynamic business environment, necessitating innovative teaching methods to prepare entrepreneurs for market uncertainties. Large Language Models (LLMs) like the Generative Pre-trained Transformer 4 (GPT-4), recognized for their exceptional performance on public datasets, are examined…
Descriptors: Entrepreneurship, Business Administration Education, Technology Integration, Artificial Intelligence
Lonneke Boels; Arthur Bakker; Wim Van Dooren; Paul Drijvers – Educational Studies in Mathematics, 2025
Many students persistently misinterpret histograms. This calls for closer inspection of students' strategies when interpreting histograms and case-value plots (which look similar but are different). Using students' gaze data, we ask: "How and how well do upper secondary pre-university school students estimate and compare arithmetic means of…
Descriptors: Secondary School Students, Learning Strategies, Data Interpretation, Graphs