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Jensen, Emily; Hutt, Stephen; D'Mello, Sidney K. – Grantee Submission, 2019
Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…
Descriptors: Generalization, Longitudinal Studies, Psychological Patterns, Identification
Jensen, Emily; Hutt, Stephen; D'Mello, Sidney K. – International Educational Data Mining Society, 2019
Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…
Descriptors: Generalization, Longitudinal Studies, Psychological Patterns, Identification
Podaeva, Natalia Georgievna; Agafonov, Pavel Alexandrovich – Journal of Educational Psychology - Propositos y Representaciones, 2020
In the context of the sociocultural approach, the authors studied the problem of the development of the students' conceptual mental structures in the process of geometry teaching. An educational activity for the development of a generalized ability to solve geometry construction problems in electronic educational environment served as a…
Descriptors: Mathematics Instruction, Elective Courses, Electronic Learning, Courseware
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