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Guiyun Feng; Honghui Chen – Education and Information Technologies, 2025
Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…
Descriptors: Educational Research, Artificial Intelligence, Data Use, Algorithms
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Khor, Ean Teng – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of the study is to build predictive models for early detection of low-performing students and examine the factors that influence massive open online courses students' performance. Design/methodology/approach: For the first step, the author performed exploratory data analysis to analyze the dataset. The process was then…
Descriptors: Prediction, Low Achievement, Algorithms, Artificial Intelligence
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David Joyner, Editor; Benjamin Paaßen, Editor; Carrie Demmans Epp, Editor – International Educational Data Mining Society, 2024
The Georgia Institute of Technology is proud to host the seventeenth International Conference on Educational Data Mining (EDM) in Atlanta, Georgia, July 14-July 17, 2024. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New tools, new prospects, new risks--educational data…
Descriptors: Data Analysis, Pattern Recognition, Technology Uses in Education, Artificial Intelligence
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Chenguang Pan; Zhou Zhang – International Educational Data Mining Society, 2024
There is less attention on examining algorithmic fairness in secondary education dropout predictions. Also, the inclusion of protected attributes in machine learning models remains a subject of debate. This study delves into the use of machine learning models for predicting high school dropouts, focusing on the role of protected attributes like…
Descriptors: High School Students, Dropouts, Dropout Characteristics, Artificial Intelligence
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Amitabh Verma – Journal of Educators Online, 2025
This study provides a thorough bibliometric analysis of the research landscape concerning the application of soft computing in higher education. This study collects 5,140 pieces including books, book chapters, journal articles published in respected journals, and conference papers presented at notable international conferences that were published…
Descriptors: Bibliometrics, Computer Uses in Education, Computer Science, Higher Education
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Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1