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Singelmann, Lauren Nichole – ProQuest LLC, 2022
To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where…
Descriptors: Engineering Education, Design, Educational Innovation, Models
Onoue, Akira; Shimada, Atsushi; Minematsu, Tsubasa; Taniguchi, Rin-Ichiro – International Association for Development of the Information Society, 2019
This study aimed to cluster learners based on the structures of the knowledge maps they created. Learners drew their own knowledge maps to reflect their learning activities. Our system collected individual knowledge maps from many learners and clustered them to generate an integrated version of the knowledge maps of each cluster. We applied the…
Descriptors: Concept Mapping, Learning Processes, Cluster Grouping, Graphs
Niu, Ke; Niu, Zhendong; Zhao, Xiangyu; Wang, Can; Kang, Kai; Ye, Min – International Educational Data Mining Society, 2016
User clustering algorithms have been introduced to analyze users' learning behaviors and help to provide personalized learning guides in traditional Web-based learning systems. However, the explicit and implicit coupled interactions, which means the correlations between user attributes generated from learning actions, are not considered in these…
Descriptors: Web Based Instruction, Student Needs, User Needs (Information), Mathematics
Gershman, Samuel J.; Blei, David M.; Niv, Yael – Psychological Review, 2010
A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…
Descriptors: Conditioning, Statistical Inference, Inferences, Bayesian Statistics

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