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Download full textLiu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Blikstein, Paulo; Worsley, Marcelo – Journal of Learning Analytics, 2016
New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…
Descriptors: Data Analysis, Data Collection, Educational Research, Constructivism (Learning)
D'Mello, S. K., Ed.; Calvo, R. A., Ed.; Olney, A., Ed. – International Educational Data Mining Society, 2013
Since its inception in 2008, the Educational Data Mining (EDM) conference series has featured some of the most innovative and fascinating basic and applied research centered on data mining, education, and learning technologies. This tradition of exemplary interdisciplinary research has been kept alive in 2013 as evident through an imaginative,…
Descriptors: Data Analysis, Educational Research, Educational Technology, Interdisciplinary Approach
Direct linkPardos, Zachary A.; Dailey, Matthew D.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
The well established, gold standard approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pre-test and post-test design. RCTs have been used in the intelligent tutoring community for decades to determine which questions and tutorial feedback work best. Practically speaking, however,…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Pretests Posttests, Educational Research
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
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
