The Architecture of Cognition
Statistics for Managers Using Microsoft Excel
Statistics for Managers Using Microsoft Excel
Using Evaluation to Shape ITS Design: Results and Experiences with SQL-Tutor
User Modeling and User-Adapted Interaction
Constraint-Based Tutors: A Success Story
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
WETAS: A Web-Based Authoring System for Constraint-Based ITS
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
KERMIT: A Constraint-Based Tutor for Database Modeling
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Andes: A Coached Problem Solving Environment for Physics
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Tailoring Feedback by Correcting Student Answers
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
An Intelligent Tutoring System Incorporating a Model of an Experienced Human Tutor
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Jess in Action: Java Rule-Based Systems
Jess in Action: Java Rule-Based Systems
Intelligent tutoring systems have forgotten the tutor: adding a cognitive model of human tutors
Intelligent tutoring systems have forgotten the tutor: adding a cognitive model of human tutors
VersaTutor: architecture for a constraint-based intelligent tutor generator
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
An Intelligent SQL Tutor on the Web
International Journal of Artificial Intelligence in Education
A comparative analysis of cognitive tutoring and constraint-based modeling
UM'03 Proceedings of the 9th international conference on User modeling
Learning Linked Lists: Experiments with the iList System
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
International Journal of Artificial Intelligence in Education
International Journal of Artificial Intelligence in Education
FeGA: A Feedback-Generating Agent
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Problem Solving Process Oriented Diagnosis in Logic Programming
Proceedings of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding
International Journal of Artificial Intelligence in Education
METEOR: medical tutor employing ontology for robustness
Proceedings of the 16th international conference on Intelligent user interfaces
International Journal of Artificial Intelligence in Education
Leveraging a domain ontology to increase the quality of feedback in an intelligent tutoring system
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Employing UMLS for generating hints in a tutoring system for medical problem-based learning
Journal of Biomedical Informatics
Clinical reasoning gains in medical PBL: an UMLS based tutoring system
Journal of Intelligent Information Systems
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Two approaches to building intelligent tutoring systems are the well-established model-tracing paradigm and the relatively newer constraint-based paradigm. Proponents of the constraint-based paradigm claim that it affords performance at levels comparable to that of model-tracing tutors, but with significantly less development effort. We have built both a model-tracing and constraint-based tutor for the same problem domain (statistical hypothesis testing) and report on our findings with the goals of evaluating proponents' claims, more generally contrasting and comparing the two approaches, and providing guidance for others interested in building intelligent tutoring systems. Principally we conclude that two characteristics of the problem domain are key in distinguishing the appropriateness of the approaches for a given problem domain. First, the constraint-based paradigm is feasible only for domains in which the solution itself is rich in information. There is no such restriction for model tracing. Second, model tracing demonstrates superiority with respect to the ability to provide targeted, high-quality remediation; this superiority increases with the complexity of the solution process goal structure. Finally, we observe that the development effort required to build a model-tracing tutor is greater than that for building a constraint-based tutor. This increased effort is a function of additional design requirements that are responsible for the improved remediation.