Campus Units

Industrial and Manufacturing Systems Engineering, Virtual Reality Applications Center, Human Computer Interaction, Education, School of, Computer Science

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2015

Journal or Book Title

International Journal of Artificial Intelligence in Education

Volume

25

Issue

3

First Page

428

Last Page

454

DOI

10.1007/s40593-015-0045-0

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.

Comments

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.

Copyright Owner

International Artificial Intelligence in Education Society

Language

en

File Format

application/pdf

Published Version

Share

COinS