Pramuditha Suraweera

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The paper presents KERMIT, a Knowledge-based Entity Relationship Modelling Intelligent Tutor. KERMIT is a problem-solving environment for the university-level students, in which they can practise conceptual database design using the Entity-Relationship data model. KERMIT uses Constraint-Based Modelling (CBM) to model the domain knowledge and generate(More)
This paper presents a project the goal of which is to develop ASPIRE, a complete authoring and deployment environment for constraint-based intelligent tutoring systems (ITSs). ASPIRE is based on our previous work on constraint-based tutors and WETAS, the tutoring shell. ASPIRE consists of the authoring server (ASPIRE-Author), which enables domain experts to(More)
Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized. Although(More)
The paper presents SmartEgg, an animated pedagogical agent developed for SQLT-Web, an intelligent SQL tutor on the Web. It has been shown in previous studies that pedagogical agents have a significant motivational impact on students. Our hypothesis was that even a very simple and constrained agent, like SmartEgg, would enhance learning. We report on an(More)
KERMIT is an intelligent tutoring system that teaches conceptual database design using the Entity-Relationship data model. Database design is an open-ended task: although there is an outcome defined in abstract terms, there is no procedure to use to find that outcome. So far, constraint based modelling has been used in a tutor that teaches a database(More)
Building a domain model consumes a major portion of the time and effort required for building an Intelligent Tutoring System. Past attempts at reducing the knowledge acquisition bottleneck by automating the knowledge acquisition process have focused on procedural tasks. We present CAS (Constraint Acquisition System), an authoring system for automatically(More)
There have been several attempts to automate knowledge acquisition for ITSs that teach procedural tasks. The goal of our project is to automate the acquisition of domain models for constraint-based tutors for both procedural and non-procedural tasks. We propose a three-phase approach: building a domain ontology, acquiring syntactic constraints directly from(More)
Evaluation is an integral part of research that provides a true measure of effectiveness. This paper presents a study conducted to evaluate the effectiveness of CAS, a knowledge acquisition authoring system developed for generating the domain knowledge required for constraint-based tutoring systems with the assistance of a domain expert. The study involved(More)
Semi-naive Bayesian techniques seek to improve the accuracy of naive Bayes (NB) by relaxing the attribute independence assumption. We present a new type of semi-naive Bayesian operation, Subsumption Resolution (SR), which efficiently identifies occurrences of the specialization-generalization relationship and eliminates generalizations at classification(More)