Authoring Effective Embedded Tutors: An Overview of the Extensible Problem Specific Tutor (xPST) System

Date
2015-09-01
Authors
Gilbert, Stephen
Blessing, Stephen
Guo, Enruo
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Altmetrics
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Research Projects
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Computer Science
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Psychology
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Abstract

The Extensible Problem Specific Tutor (xPST) allows authors who are not cognitive scientists and not programmers to quickly create an intelligent tutoring system that provides instruction akin to a model-tracing tutor. Furthermore, this instruction is overlaid on existing software, so that the learner’s interface does not have to be made from scratch. The xPST architecture allows for extending its capabilities by the addition of plug-ins that communicate with additional third-party software. After reviewing this general architecture, we describe three major implementations that we have created using the xPST system, each using different third-party software as the learner’s interface. We have conducted three evaluations of authors using xPST to create tutoring content, and these are considered in turn. These evaluations show that xPST authors can quickly learn the system, and can efficiently produce successful embedded instruction.

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This is a manuscript of an article published as Gilbert, Stephen B., Stephen B. Blessing, and Enruo Guo. "Authoring Effective Embedded Tutors: An Overview of the Extensible Problem Specific Tutor (xPST) System." International Journal of Artificial Intelligence in Education 25, no. 3 (2015): 428-454. DOI:10.1007/s40593-015-0045-0. Posted with permission.

Keywords
Authoring tool, Cognitive tutor, Model-Tracing Tutor, xPST
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