Problem Solving and Explanation in Intelligent Tutoring Systems: Issues for Future Research

The paper focuses on the issues of providing an adaptive support for learners in intelligent tutoring systems when learners solve practical problems. The results of the analysis of support policies of learners in the existing intelligent tutoring systems are given and the revealed problems are emphasized. The concept and the architectural parts of an intelligent tutoring system are defined. The approach which provides greater adaptive abilities of systems of such kind offering two modes of problem-solving and using a two-layer model of hints is described. It is being implemented in the intelligent tutoring system for the Minimax algorithm at present. In accordance with the proposed approach the learner solves problems in the mode which is the most appropriate for him/her and receives the most suitable hint.

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Online Homework Managers and Intelligent Tutoring Systems: A Study of Their Impact on Student Learning in the Introductory Financial Accounting Classroom

Issues in Accounting Education ◽

10.2308/iace-50441 ◽

2013 ◽

Vol 28 (3) ◽

pp. 513-535 ◽

Cited By ~ 13

Author(s):

William Hahn ◽

Chris Fairchild ◽

William B. Dowis

Keyword(s):

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Financial Accounting ◽

Future Research ◽

Control Group ◽

Online Homework ◽

Research Directions ◽

Tutoring Systems ◽

Future Research Directions

ABSTRACT: The online homework manager (OHM) and the intelligent tutoring system (ITS) are two supplemental teaching tools available for accounting educators' use in the introductory financial accounting course. While research related to these systems is limited, prior studies find a tenuous performance advantage related to their use. To advance the literature in this area, this paper evaluates the performance benefit related to an OHM and an ITS, each employed independently as an additional study aid during the first course unit in one of two sections of the introductory financial accounting course. A third section used paper-and-pencil only and served as a control group. Results of tests on several performance measures did not identify a learning advantage associated with either the OHM or the ITS. Nor was a learning advantage identified when this study's results were compared to exam results from 14 previous semesters. Implications for accounting educators and future research directions are discussed.

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Intelligent Tutoring Systems for Distributed Learning

Designing Distributed Learning Environments with Intelligent Software Agents ◽

10.4018/978-1-59140-500-9.ch006 ◽

2011 ◽

pp. 162-183 ◽

Cited By ~ 1

Author(s):

Mohamed Ally

Keyword(s):

Research And Development ◽

Multidisciplinary Team ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Distributed Learning ◽

Future Research ◽

Student Model ◽

Tutoring Systems ◽

Individual Learner ◽

Teaching Situation

This chapter provides information on how to design intelligent tutoring systems for distributed learning to cater to individual learner needs and styles. It argues that intelligent tutoring systems must use the expertise that tutors use in a one-to-one teaching situation to build intelligent tutoring systems for distributed learning. Also, the appropriate psychological and educational theories must be used to build the domain module, student model, and pedagogical module. The components of intelligent tutoring systems are described, and the author makes the case that to build effective intelligent tutoring systems, a multidisciplinary team should be involved. Finally, the author identifies trends that are influencing the development of intelligent tutoring systems and suggests areas for future research and development.

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