Building an Intelligent Tutoring System: Some Guidelines from a Study of Human Tutors

Abstract

One reason that intelligent tutoring systems (ITSs) are rarely found outside of the research lab has to do with the guidelines available to developers of these systems. First, some of these guidelines are stated as general, abstract goals such as “adapt to the student.” What ITS developers need, however, are specific strategies and techniques which can be implemented in an ITS to accomplish those goals. Second, not all of the guidelines have an empirical basis. One solution to both of these problems is to study human tutors. This paper demonstrates this approach, and discusses an empirical study of human tutors which was conducted to address these issues. Specifically, it discusses 1) the knowledge acquisition method which we designed to capture the appropriate empirical data, 2) how we used this method to study human tutors and students in the medical problem-solving domain of immunohematology (blood banking), 3) several guidelines which appeared to drive the tutors' behavior (e.g., “limit the number of interrupts to the student”), and 4) specific tutoring strategies which can be incorporated into an ITS to make its behavior follow these guidelines.

The Scope and Importance of Human Interruption in Human-Computer Interaction Design

“…Other application domains require interruption-management support: intelligent tutoring systems (Galdes & Smith, 1990), computer-mediated communication (Bannon, 1986;McCarthy & Monk, 1994), telephone communications (Katz, 1995;Stuart, Desurvire, & Dews, 1991), U.S. Navy's Multi-Modal Watchstation (MMWS; Obermayer & Nugent, 2000;Osga, 2000), Navy damage control systems (Perse, Callahan, & Malone, 1991), office environments (Rouncefield, Hughes, Rodden, & Viller, 1994;Speier et al, 1997;Zijlstra & Roe 1999), and Internet instant messaging (Czerwinski, Cutrell, & Horvitz, 2000a, 2000b. This design problem also applies to areas of air-traffic control, Internet push technology, head-mounted display systems, unmanned air vehicles, medical-device monitoring and procedures, automated command and control, automated highway systems, and intelligent software agents.…”

“…Burton and Brown (1979) reported on their effort to design a computer-based tutor for an ICAI (Intelligent Computer-Assisted Instruction) system that teaches math skills. Galdes and Smith (1990) said that Burton and Brown's guidelines are useful, but are not significantly rigorous and need to be empirically validated. It is built to detect human-learning errors and interrupt the user with attempts to help overcome learning problems.…”