Ramzan Khuwaja

Intelligent Guide: Combining User Knowledge Assessment with Pedagogical Guidance

Despite their many successes, Intelligent Tutoring Systems (ITS) are not yet practical enough to be employed in the real world educational/training environments. We argue that this undesirable scenario can be changed by focusing on developing an ITS development methodology that transforms current ITS research to consider practical issues that are part of the main causes of underemployment of ITSs. Here we describe an ambitious research project to develop an ITS that has recently completed its first phase of development at the Computer Research Institute of Montreal. This project aims to address issues, such as, making ITS handle multiple domains, developing cost-effective knowledge assessment methodologies, organizing and structuring domains around curriculum views and addressing the needs of users by considering their immediate goals and educational/training settings. This paper concentrates on the outcomes of the first phase of our project that includes the architecture and functionality (specially user knowledge assessment and pedagogical guidance) of the Intelligent Guide.

Knowledge Representation for an Intelligent Tutoring Sytem Based on a Multilevel Causal Model

An explicit representation of knowledge is central for an Intelligent Tutoring System (ITS). In order for a system to acquire the necessary flexibility, its knowledge representation framework should distinguish between several types of knowledge and structure them in layers. Here, we present a method for representing domain knowledge for an ITS, using hierarchical knowledge structures and a multilevel causal model of the domain. The successive levels of this causal model increase in complexity to more closely approximate a complete domain model. The resulting knowledge structures have the flexibility that is needed to invoke a sophisticated instructional session.

Architecture of CIRCSIM-Tutor (v.3): a smart cardiovascular physiology tutor

This paper describes the architecture of the recent version (v.3) of a cardiovascular physiology tutor, called CIRCSIM-Tutor. The intended purpose of CIRCSIM-Tutor is to help first year medical students in developing a problem solving skill in the domain of cardiovascular physiology. This architecture was constructed using a systematic intelligent tutoring system (ITS) development methodology which combines the features of a systematic knowledge based system development methodology with an instructional system development methodology in a single framework. The architecture of CIRCSIM-Tutor (v.3) is flexible and is consistent with some important software engineering concepts. The architecture divides the functionality of CIRCSIM-Tutor into a set of subsystems which communicates with a message passing protocol. The shared resources such as domain knowledge base, lexicon, student model are kept separate as information stores which may be freely accessed by all subsystems of CIRCSIM-Tutor.<<ETX>>

A Model of Tutoring: Based on the Behavior of Effective Human Tutors

Research has shown that tutoring by humans provide the most effective method of instruction. One school of thought in the Intelligent Tutoring Systems (ITS) community believes that studying human tutors is the best way to discover how to build effective machine tutors. This paper describes a conceptual model of tutoring that is based on a study of skilled human tutors in the domain of cardiovascular physiology. This model is developed as a part of research to develop an ITS, CIRCSIM-Tutor, for first year medical students at Rush Medical College, Chicago. The major theme of this model of tutoring is that, in a problem-solving environment, it facilitates the student to integrate his/her knowledge into a coherent qualitative causal model of the domain and solve problems in the domain. The key feature of this model is that it uses multiple models of the domain in the process of facilitating knowledge integration.

Building the domain-expert for a cardiovascular physiology tutor

This paper describes the building of the domain-expert for a cardiovascular physiology tutor called CIRCSIM-Tutor using a systematic development methodology. The domain-expert is a functional component of CIRCSIM-Tutor and provides the domain intelligence to the rest of the system. The authors have developed a multi-dimensional knowledge representation technique to capture expertise in the domain, which led them to the construction of a conceptual model of the domain-expert of CIRCSIM-Tutor. The authors describe how this conceptual model is transformed via an object-oriented methodology to yield the architecture of the domain-expert of CIRCSIM-Tutor. The conceptual model is at the epistemological level and has a real-world-orientation, whereas the architecture of domain-expert emphasizes system-orientation. The resulting architecture is query-driven and provides a fully transparent access to each chunk of domain knowledge, of different types, with optimal flexibility.<<ETX>>