Department of Computer and Information Science

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Browsing Department of Computer and Information Science by Author "Douglas, Sarah A."

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    Context, User Models and Interface Design
    (University of Oregon, 1988-07-12) Douglas, Sarah A.
    Most of the existing analytical descriptions of users characterize their performance as a function of the cognitive representation of the command sequences of the computer-based task (e.g. Anderson, Farrell, & Sauers, 1984; Card, Moran & Newell, 1983; Polson & Kieras, 1985; Norman, 1986). This is represented as goal-oriented schemata: procedures, plans, or production rules. Thus, the interface designer need only lay out the command sequences adequate to achieve a set of core tasks to make predictions about user behavior. These models are by and large restricted to descriptions of error-free, skilled (expert) performance or error-free learner subsets of expert knowledge. Attempts to extend these analytical models to accommodate learner error soon find themselves coping with the problems of prior knowledge (c.f. Douglas & Moran, 1983; Riley, 1986). That is, elements of performance that are independent of the computer task representation. Additionally, the existing models make no attempt to represent the ongoing interactive nature of human behavior at the interface. This problem of taking into account aspects of human performance at the interface which are independent of the task representation can be called the context problem. In the remainder of this paper I will attempt to delineate the nature of this problem by defining the notion of context, giving examples of context accommodation in interface design, and discussing the practical and theoretical problems that context creates for user models and interface design.
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    Detecting and Repairing Tutoring Failures
    (University of Oregon, 1988-06-21) Douglas, Sarah A.
    During the course of studying a number of protocols of human tutors working with human students, I became aware of a complex process of interaction failure and repair. Although much ITS research has been devoted to the understanding and modeling of the detection and repair of student performance failure and misconception in learning curriculum concepts, there is little understanding of an equivalent self-detection and repair issue with tutor performance failure and misconception about what the student is taught. Indeed, there seems to have been a failure to examine the heart of intelligent tutoring systems, what Wenger ( 1987) terms knowledge communication. Communication is an inherent dyadic relation whose primary performance feature is interaction. In particular, interaction between humans, as all human performance, appears filled with both slips and bugs. Humans are highly tuned to the detection and repair of these problems. In the remainder of this paper, I present examples of some of the types of tutor interaction failure that I discovered in these protocols, discuss the detection and repair strategies used, and, finally, discuss the implications of these findings for ITS. My conclusion about tutoring failures is that some types can possibly be reduced by use of an intelligent tutoring system, but that others, called model failures, are an inherent part of the teaching of complex domains. Knowledge and the communication of knowledge are inextricably intertwined. Since we cannot create error-free ITS, we should study in more detail the mechanisms of failure detection and repair that are inherent in human interaction. I believe that achieving this goal will require a much finer grain of analysis of the process of student response during both problem .presentation and remediation and will place a greater emphasis on the detailed design of the interface of ITS.