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Waters, Andrew; Studer, Christoph; Baraniuk, Richard – Journal of Educational Data Mining, 2014
Identifying collaboration between learners in a course is an important challenge in education for two reasons: First, depending on the courses rules, collaboration can be considered a form of cheating. Second, it helps one to more accurately evaluate each learners competence. While such collaboration identification is already challenging in…
Descriptors: Cooperation, Large Group Instruction, Online Courses, Probability
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
Maxwell, Martha – 1998
Simple Bayesian approaches can be applied to answer specific questions in evaluating an individualized reading program. A small reading and study skills program located in the counseling center of a major research university collected and compiled data on student characteristics such as class, number of sessions attended, grade point average, and…
Descriptors: Bayesian Statistics, Data Collection, Decision Making, Higher Education
Educational Testing Service, Princeton, NJ. – 1971
The conference theme was "The Promise and Perils of Educational Information Systems," defined as collections of test data on knowledges, skills, interests, and attitudes maintained for the purpose of educational decision making. Topics covered were: "Longer Education: Thinner, Broader, or Higher" (Fritz Machlup); "Testing:…
Descriptors: Bayesian Statistics, Bias, Blacks, Conferences