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

Autor/inn/en	Gilbert, Stephen B.; Blessing, Stephen B.; Guo, Enruo
Titel	Authoring Effective Embedded Tutors: An Overview of the Extensible Problem Specific Tutor (xPST) System
Quelle	In: International Journal of Artificial Intelligence in Education, 25 (2015) 3, S.428-454 (27 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.1007/s40593-015-0045-0
Schlagwörter	Intelligent Tutoring Systems; Authors; Computer Software; Computer Interfaces; Evaluation + Suchen Sie Ihr Suchwort? Intelligentes Tutorsystem; Author; Autor; Autorin; Evaluierung
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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01