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Showing all 6 results
Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2012
Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…
Descriptors: Tutoring, Feedback (Response), Intelligent Tutoring Systems, Academic Achievement
Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2012
Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…
Descriptors: Teaching Methods, Mathematics, Behavior Patterns, Academic Achievement
Rus, Vasile; Moldovan, Cristian; Niraula, Nobal; Graesser, Arthur C. – International Educational Data Mining Society, 2012
In this paper we address the important task of automated discovery of speech act categories in dialogue-based, multi-party educational games. Speech acts are important in dialogue-based educational systems because they help infer the student speaker's intentions (the task of speech act classification) which in turn is crucial to providing adequate…
Descriptors: Educational Games, Feedback (Response), Classification, Expertise
Sudol, Leigh Ann; Rivers, Kelly; Harris, Thomas K. – International Educational Data Mining Society, 2012
In complex problem solving domains, correct solutions are often comprised of a combination of individual components. Students usually go through several attempts, each attempt reflecting an individual solution state that can be observed during practice. Classic metrics to measure student performance over time rely on counting the number of…
Descriptors: Problem Solving, Tutors, Feedback (Response), Probability
Eagle, Michael; Johnson, Matthew; Barnes, Tiffany – International Educational Data Mining Society, 2012
We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…
Descriptors: Data Analysis, Interaction, Network Analysis, Problem Solving
Stamper, John C.; Lomas, Derek; Ching, Dixie; Ritter, Steve; Koedinger, Kenneth R.; Steinhart, Jonathan – International Educational Data Mining Society, 2012
Traditional experimental paradigms have focused on executing experiments in a lab setting and eventually moving successful findings to larger experiments in the field. However, data from field experiments can also be used to inform new lab experiments. Now, with the advent of large student populations using internet-based learning software, online…
Descriptors: Internet, Feedback (Response), Computer Software, Data Collection


