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Predicting University Major Selection and Academic Performance through the Combination of Apriori Algorithm and Deep Neural Network
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Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
Predicting Pre-Service Teachers' Computational Thinking Skills Using Machine Learning Classifiers
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Jin, Hao-Yue; Cutumisu, Maria – Education and Information Technologies, 2023
Computational thinking (CT) skills of pre-service teachers have been explored extensively, but the effectiveness of CT training has yielded mixed results in previous studies. Thus, it is necessary to identify patterns in the relationships between predictors of CT and CT skills to further support CT development. This study developed an online CT…
Descriptors: Preservice Teachers, Computation, Thinking Skills, Predictor Variables
Predicting Students' Academic Performance by Mining the Educational Data through Machine Learning-Based Classification Model
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Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
Identifying Determinants of Big Data Adoption in the Higher Education Sector Using a Multi-Analytical SEM-ANN Approach
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Baig, Maria Ijaz; Yadegaridehkordi, Elaheh; Shuib, Liyana; Sallehuddin, Hasimi – Education and Information Technologies, 2023
Even though big data offers new opportunities to organizations, big data adoption (BDA) is still in the early stages of introduction, and its determinants remain unclear in many sectors. Therefore, this research intended to identify the determinants of BDA in the education sector. A theoretical model was developed based on the integration of the…
Descriptors: Foreign Countries, Learning Analytics, Higher Education, Structural Equation Models
Modelling the Relationships between STEM Learning Attitude, Computational Thinking, and 21st Century Skills in Primary School
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Mensure Alkis Küçükaydin; Hakan Çite; Hakan Ulum – Education and Information Technologies, 2024
Students enter the science, technology, engineering, and mathematics (STEM) pipeline in primary school, but leak out of it over time for various reasons. To prevent leaks, it is important to understand the variables that affect attitudes towards STEM learning from an early age. This study sought to examine the predictors of young students' STEM…
Descriptors: Foreign Countries, Elementary School Students, STEM Education, Student Attitudes
Comparative Analysis of Algorithms with Data Mining Methods for Examining Attitudes towards STEM Fields
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Göktepe Körpeoglu, Seda; Göktepe Yildiz, Sevda – Education and Information Technologies, 2023
Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…
Descriptors: Comparative Analysis, Algorithms, Data Collection, Student Attitudes