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A Framework for Capturing Distinguishing User Interaction Behaviors in Novel Interfaces
As novel forms of educational software continue to be created, it is often difficult to understand a priori which ensemble of interaction behaviours is conducive to learning. In this paper, weExpand
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Exploring gaze data for determining user learning with an interactive simulation
This paper explores the value of eye-tracking data to assess user learning with interactive simulations (IS). Our long-term goal is to use this data in user models that can generate adaptive supportExpand
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Providing Adaptive Support in an Interactive Simulation for Learning: An Experimental Evaluation
Recent rise of Massive Open Online Courses (MOOCs) with unlimited participants, makes employing learning tools such as interactive simulations all but inevitable. Interactive simulations giveExpand
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The Usefulness of Log Based Clustering in a Complex Simulation Environment
Data mining techniques have been successfully employed on user interaction data in exploratory learning environments. In this paper we investigate using data mining techniques for analyzing studentExpand
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Student Modeling: Supporting Personalized Instruction, from Problem Solving to Exploratory Open Ended Activities
The field of intelligent tutoring systems has successfully delivered techniques and applications to provide personalized coaching and feedback for problem solving in a variety of domains. The core ofExpand
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Comparing Representations for Learner Models in Interactive Simulations
Providing adaptive support in Exploratory Learning Environments is necessary but challenging due to the unstructured nature of interactions. This is especially the case for complex simulations suchExpand
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Comparing and Combining Eye Gaze and Interface Actions for Determining User Learning with an Interactive Simulation
This paper presents an experimental evaluation of eye gaze data as a source for modeling user’s learning in Interactive Simulations (IS). We compare the performance of classifier user models trainedExpand
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Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity
Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments.Expand
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Towards a More Accurate Knowledge Level Estimation
Adaptive testing or Computer Adaptive Testing (CAT), adjusts the set of questions to the learner’s estimated ability level, in order to reduce the guessing or slipping in answering too difficult orExpand
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