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Emerson, Andrew; Rodríguez, Fernando J.; Mott, Bradford; Smith, Andy; Min, Wookhee; Boyer, Kristy Elizabeth; Smith, Cody; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2019
Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…
Descriptors: Programming, Computer Science Education, Feedback (Response), Prediction
Agrawal, Akshay; Venkatraman, Jagadish; Leonard, Shane; Paepcke, Andreas – International Educational Data Mining Society, 2015
In Massive Open Online Courses (MOOCs), struggling learners often seek help by posting questions in discussion forums. Unfortunately, given the large volume of discussion in MOOCs, instructors may overlook these learners' posts, detrimentally impacting the learning process and exacerbating attrition. In this paper, we present YouEDU, an…
Descriptors: Large Group Instruction, Distance Education, Technology Uses in Education, Educational Technology
Rowe, Elizabeth; Baker, Ryan S.; Asbell-Clarke, Jodi – International Educational Data Mining Society, 2015
Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We…
Descriptors: Educational Games, Science Instruction, Video Games, Coding
Kai, Shiming; Paquette, Luc; Baker, Ryan S.; Bosch, Nigel; D'Mello, Sidney; Ocumpaugh, Jaclyn; Shute, Valerie; Ventura, Matthew – International Educational Data Mining Society, 2015
Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students' affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of…
Descriptors: Video Technology, Interaction, Physics, Affective Behavior
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use