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Investigating the Importance of Demographic Features for EDM-Predictions

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Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023

Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology

Proceedings of the International Conference on Educational Data Mining (EDM) (13th, Online, July 10-13, 2020)

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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing

Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014)

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Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection