OCTAL: online course tool for adaptive learning

Authors:
Daniel Armendariz;Zachary MacHardy;Daniel D. Garcia
Affiliations:
University of California, Berkeley, Berkeley, CA, USA;University of California, Berkeley, Berkeley, CA, USA;University of California, Berkeley, Berkeley, CA, USA
Venue:
Proceedings of the first ACM conference on Learning @ scale conference
Year:
2014

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Adaptive Assessment Using Granularity Hierarchies and Bayesian Nets

ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems

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Abstract

The Online Course Tool for Adaptive Learning (OCTAL) is an adaptive exercise system that customizes the progression of question topics to each student. By creating a concept dependency graph of topics in a course and modeling a student's knowledge state, the tool presents questions that test knowledge within a student's zone of proximal development. We intend OCTAL to be a formative assessment tool that is not tied to any specific course by providing language-agnostic questions on computer science concepts. While the tool will be generalizable for many courses, our first prototype includes a concept map and question set for UC Berkeley's introductory computer science course, CS10: The Beauty and Joy of Computing. Using the tool, we will launch an experiment in the spring to investigate metacognitive improvements in the identification of knowledge gaps by presenting online course material in a nonlinear fashion.