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Mandel, Travis Scott – ProQuest LLC, 2017
When a new student comes to play an educational game, how can we determine what content to give them such that they learn as much as possible? When a frustrated customer calls in to a helpline, how can we determine what to say to best assist them? When an ill patient comes in to the clinic, how do we determine what tests to run and treatments to…
Descriptors: Reinforcement, Learning Processes, Student Evaluation, Data Collection
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DiCerbo, Kristen E.; Xu, Yuning; Levy, Roy; Lai, Emily; Holland, Laura – Educational Assessment, 2017
Inferences about student knowledge, skills, and attributes based on digital activity still largely come from whether students ultimately get a correct result or not. However, the ability to collect activity stream data as individuals interact with digital environments provides information about students' processes as they progress through learning…
Descriptors: Models, Cognitive Processes, Elementary School Students, Grade 3
Beheshti, Behzad; Desmarais, Michel C. – International Educational Data Mining Society, 2015
This study investigates the issue of the goodness of fit of different skills assessment models using both synthetic and real data. Synthetic data is generated from the different skills assessment models. The results show wide differences of performances between the skills assessment models over synthetic data sets. The set of relative performances…
Descriptors: Goodness of Fit, Student Evaluation, Skills, Models
Shute, Valerie J.; Moore, Gregory R.; Wang, Lubin – International Educational Data Mining Society, 2015
We are using stealth assessment, embedded in "Plants vs. Zombies 2," to measure middle-school students' problem solving skills. This project started by developing a problem solving competency model based on a thorough review of the literature. Next, we identified relevant in-game indicators that would provide evidence about students'…
Descriptors: Middle School Students, Problem Solving, Educational Games, Bayesian Statistics
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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
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Baker, Ryan S.; Corbett, Albert T. – Research & Practice in Assessment, 2014
Many university leaders and faculty have the goal of promoting learning that connects across domains and prepares students with skills for their whole lives. However, as assessment emerges in higher education, many assessments focus on knowledge and skills that are specific to a single domain. Reworking assessment in higher education to focus on…
Descriptors: Educational Assessment, Data Collection, Information Retrieval, Learning Processes