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Hanall Sung; Martina A. Rau; Barry D. Van Veen – IEEE Transactions on Learning Technologies, 2024
In many science, technology, engineering, and mathematics (STEM) domains, instruction on foundational concepts heavily relies on visuals. Instructors often assume that students can mentally visualize concepts but students often struggle with internal visualization skills--the ability to mentally visualize information. In order to address this…
Descriptors: Intelligent Tutoring Systems, Visualization, Measures (Individuals), Educational Development
Dickmann, Thomas; Opfermann, Maria; Dammann, Elmar; Lang, Martin; Rumann, Stefan – Chemistry Education Research and Practice, 2019
Visualizations and visual models are of substantial importance for science learning (Harrison and Treagust, 2000), and it seems impossible to study chemistry without visualizations. More specifically, the combination of visualizations with text is especially beneficial for learning when dual coding is fostered (Mayer, 2014). However, at the same…
Descriptors: Science Instruction, Models, Visualization, Visual Stimuli
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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