Showing papers on "User modeling published in 1989"

Rethinking the concept of user involvement

Abstract: Within the field of information systems, user involvement generally refers to participation in the systems development process by potential users of their representatives and is measured as a set of behaviors or activities that such individuals perform. This article argues for a separation of the constructs of user participation (a set of behaviors or activities performed by users in the system development process) and user involvement (a subjective psychological state reflecting the importance and personal relevance of a system to the user). Such a distinction is not only more consistent with conceptualizations of involvement found in other disciplines, but it also leads to a number of new and interesting hypotheses. These hypotheses promise a richer theoretical network that describes the role and importance of participation and involvement in the implementation process.

User Models in Dialog Systems

Abstract: User models have recently attracted much research interest in the field of artificial intelligence dialog systems. It has become evident that a flexible user-oriented dialog behavior of such systems can be realized only if the system disposes of a model of the user, containing assumptions about the user`s background knowledge as well as the user`s goals and plans in consulting the system. Research in the field of user models investigates how such assumptions can be automatically created, represented and exploited by the system in the course of an interaction with the user. This volume is the first survey pertaining to the field of user modeling. Most of the prominent international researchers in this area have contributed to this volume. Their papers are grouped into four sections: The introductory section contains a general view of the field as a whole, and a number of surveys of specific problems and techniques in user modeling. Sections two and three describe eight user modeling systems, with the focus lying on the automatic creation and exploitation of assumptions about the user respectively. The final section discusses several limits of current systems, and proposes solutions as to how some of the shortcomings might be overcome. In order to increase the quality and the coherency of the volume, each paper has been reviewed by all other contributors. Cross-references have been integrated wherever appropriate. All contributions are introduced in editorial prefaces pertaining to each section. A subject index and an extensive bibliography supplement the book.

Stereotypes and User Modeling

Abstract: A stereotype represents a collection of attributes that often co-occur in people. Stereotypes can play an important role in a user modeling system because they enable the system to make a large number of plausible inferences on the basis of a substantially smaller number of observations. These inferences must, however, be treated as defaults, which can be overridden by specific observations. Thus any stereotype-based user-modeling system must include techniques for nonmonotonic reasoning. This chapter will discuss the role that stereotypes can play in a user modeling system and it will outline specific techniques that can be used to implement stereotype-based reasoning in such systems.

A human activity approach to user interfaces

Abstract: How can we understand why a bank teller has different needs for a user interface than those of casual users of a machine teller, or why a graphic designer needs a different user interface than a secretary? This article presents a framework for the design of user interfaces that originates from the work situations in which computer-based artifacts are used: The framework deals with the role of the user interface in purposeful human work. Human activity theory is used in this analysis. The purpose of this article is to make the reader curious and hopefully open his or her eyes to a somewhat different way of thinking about the user interface. The article applies examples of real-life interfaces to support this process, but it does not include a systematic presentation of empirical results. I focus on the role of the computer application in use. Thus, it is necessary to consider human-computer interaction and other related work conditions. I deal with human experience and competence as being rooted in the practice of the group that conducts the specific work activity. The main conclusions are: The user interface cannot be seen independently of the use activity (i.e., the professional, socially organized practice of the users and the material conditions for the activity, including the object of the activity). The standard view in these situations is to deduce an ultimate set of operations from an abstract use activity and apply these to design and analysis. This article argues that the user interface fully reveals itself to us only when in use. What is a good user interface for those with a certain degree of competence may not be efficient for those with different levels of competence. I give certain general recommendations for the user interface, but I have no guarantee that such recommendations are applicable to the specific case wherein these concerns may be overruled by specific social or material concerns.

KNOME: Modeling What the User Knows in UC

Abstract: KNOME is the user modeling component of UC, a natural language consultation system for the UNIX operating system. During the course of an interactive session with a user, KNOME infers the user’s level of expertise from the dialog and maintains a model of the user’s knowledge of the UNIX domain. KNOME’s model of the user makes use of a double-stereotype system in which one set of stereotypes represents the user’s expertise and another represents the difficulty level of the information. KNOME is used in UC to help disambiguate the user’s statements, avoid telling the user something that the user already knows, take advantage of prior user knowledge in presenting new information, and detect situations where the user lacks pertinent facts or where the user has a misconception. UC also models its own knowledge of UNIX with meta-knowledge (explicit facts about the limitations of the system’s own knowledge base), which is used to help in correcting user misconceptions.

Programmable user models for predictive evaluation of interface designs

Abstract: A Programmable User Model (PUM) is a psychologically constrained architecture which an interface designer is invited to program to simulate a user performing a range of tasks with a proposed interface. It provides a novel way of conveying psychological considerations to the designer, by involving the designer in the process of making predictions of usability. Development of the idea leads to a complementary perspective, of the PUM as an interpreter for an “instruction language”. The methodology used in this research involves the use of concrete HCI scenarios to assess different approaches to cognitive modelling. The research findings include analyses of the cognitive processes involved in the use of interactive computer systems, and a number of issues to be resolved in future cognitive models.

Explaining control strategies in problem solving

Abstract: Explaining how knowledge-based systems reason involves presentation user modeling, dialogue structure, and the way systems understand their own problem-solving knowledge and strategies. The authors concentrate on the last of these, noting that such understanding provides any explanations's content. The authors also note that most current approaches to knowledge-based system construction require expressing knowledge and control at such low levels that it's hard to give high-level explanations. Providing an explanation example from a prototypical system (MYCIN) built using generic-task methods, they propose generic-task methodology as one way to build knowledge-based systems that contain basic explanation constructs at appropriate abstraction levels. The central concept of generic tasks is what input-output behavior (i.e. that task function), knowledge needed to perform the task, and inferences appropriate for the task are all specified together. >

GUMS — A General User Modeling Shell

Abstract: This chapter discusses the application of various kinds of default reasoning in system maintained models of users. In particular, we describe the general architecture of a domain independent system for building and maintaining long term models of individual users.The user modeling system is intended to provide a well defined set of services for an application system interacting with various users, and must build and maintain models of them. As the application system interacts with a user, it can acquire knowledge of him, and pass that knowledge on to the user model maintenance system for incorporation. We describe a prototype general user modeling shell (hereafter called GUMS) that we have implemented in Prolog. This system possesses some of the desirable characteristics we discuss.

Phrasing a text in terms the user can understand

Abstract: When humans use language, they show an essential, inbuilt responsiveness to their hearers/readers. When language is generated by machine, it is similarly necessary to ensure that that language is appropriate for its intended audience. Much of previous research on text generation and user modelling has focused on building a user model and selecting appropriate information from the knowledge base to present to the user. It is important, however, that the phrasing of a text be also tailored to the hearer - otherwise it may be just as ineffective as texts which wrongly direct attention or which rely on knowledge that the hearer does not have. This research proposes a new mechanism which allows the text planning process to specifically tailor syntactic phrasing to the hearer type. This is done in the context of an expert system explanation facility that needs to produce explanations of the expert system's behavior for a variety of different users - users who differ in goals, expectations, and expertise concerning both the expert system and its domain.

A two-view approach to constructing user interfaces

Abstract: This paper describes a system for constructing graphical user interfaces following a two-view paradigm: one view contains a textual representation of the interface in a special-purpose, "little" language, and the other view contains a direct manipulation, interactive editor for the user interface. The user interface can be edited in either view, and the changes are reflected in the other view. The language allows dialog boxes to be expressed in a simple and natural way, and has a well-defined mapping into the interactive editor. A base set of interactors is currently available, but the system can be easily extended with more interactors. We believe this approach to building user interfaces combines the advantages of the direct manipulation, WYSIWYG approach with the advantages of the textual, descriptive approach, and does not suffer from the limitations of either approach.

Plan Recognition and Its Use in Understanding Dialog

Abstract: Analysis of naturally occurring dialog suggests that human information-providers often use knowledge acquired from the dialog to understand subsequent utterances and provide cooperative, helpful responses. One of the most important ways in which an information-seeking dialog can be assimilated is by inferring the task-related plan motivating an information-seeker’s queries. This chapter presents two process models. The first dynamically constructs a model of an information-seeker’s plans and goals from an ongoing dialog, and the second reasons on this component of a user model to understand one class of problematic utterance. The chapter further addresses the problem of detecting and recovering from discrepancies between the system’s model of the user and the actual plan under construction by the user. It proposes a four-phase approach to detecting and recovering from disparate models, and argues for an enriched user model that differentiates among its components on the basis of the support it accords each component as a correct and intended part of the user’s plan.

The Use of Explicit User Models in a Generation System for Tailoring Answers to the User’s Level of Expertise

Abstract: A question-answering program providing access to a large amount of data will be most useful if it can tailor its answers to each individual user. In particular, a user’s level of knowledge about the domain of discourse is an important factor in this tailoring if the answer provided is to be both informative and understandable to the user. In this research, we address the issue of how the user’s domain knowledge can affect an answer. By studying texts, we found that the user’s level of domain knowledge affected the kind of information provided and not just the amount of information, as was previously assumed. Depending on the user’s assumed domain knowledge, a description can be either parts-oriented or process-oriented. Thus the user’s level of expertise in a domain can guide a system in choosing the appropriate facts from the knowledge base to include in an answer. We propose two distinct descriptive strategies that can be used in a question-answering program, and show how they can be mixed to include the appropriate information from the knowledge base, given the user’s domain knowledge. We have implemented these strategies in TAILOR, a computer system that generates descriptions of devices. TAILOR uses one of the two discourse strategies identified in texts to construct a description for either a novice or an expert. It can merge the strategies automatically to produce a wide range of different descriptions to users who fall between the extremes of novice or expert, without requiring an a priori set of user stereotypes.

A Taxonomy of Beliefs and Goals for User Models in Dialog Systems

Abstract: In this chapter, a taxonomy of beliefs and goals is proposed, the purpose of which is threefold: it should allow for a classification of current user models with regard to what is being modeled by them; it should support the designer of a user model in investigating what types of beliefs and goals are relevant to his/her particular application; and it should allow the evaluation of the expressive power of representation schemes for beliefs and goals. For each belief and goal type, examples are presented for their occurrence in application domains of dialog systems. In addition, a number of existing systems are compared with respect to what beliefs and goals are being modeled by their user modeling components, and the consequences of an observed dichotomy of user models with respect to complexity is discussed.

Student Modeling in Intelligent Tutoring Systems — Implications for User Modeling

Abstract: User modeling and student modeling, though similar in many ways, have generally been pursued in parallel for the past decade. This chapter explores the role of student modeling in intelligent tutoring systems from the perspective of user modeling, with the goal of determining what researchers in user modeling can learn from student modeling. The chapter focuses on three issues: the information modeled about students, how that information is represented, and how the student model is built. Several intelligent tutoring systems that do student modeling are critically examined (in particular BUGGY, LMS, GUIDON, and WUSOR), and recommendations for user modeling based on this examination are made.

User Models and Conversational Settings: Modeling the User’s Wants

Abstract: In general, the cycle of system development can be viewed as consisting of four phases: theoretical considerations, design practical implementation and experimentation evaluation of the system, documentation reorganizing the field of research, thus using the experience which has been gained by workers in the field.

The role of user models in cooperative interactive systems

Abstract: For interactive systems to communicate in a cooperative manner, they must have knowledge about their users. This article explores the role of user models in such systems, with the goal of identifying when and how user models may be useful in a cooperative interactive system. User models are classified by the types of knowledge they contain, several user modelling characteristics that serve as dimension for an additional classification of user models are presented, and user model representations are discussed. These topics help to characterize the space of user modelling in cooperative interactive systems-addressing how they can be used-but do not fully address when it is appropriate to include a user model in an interactive system. Thus, a set of design considerations for user models is presented, while a final example illustrates how these topics influence the user model for a hypothetical investment consulting system. © 1989 Wiley Periodicals, Inc.

A programming language basis for user interface

Abstract: The Mickey UIMS maps the user interface style and techniques of the Apple Macintosh onto the declarative constructs of Pascal. The relationships between user interfaces and the programming language control the interface generation. This imposes some restrictions on the possible styles of user interfaces but greatly enhances the usability of the UIMS.

Highlighting a User Model to Respond to Misconceptions

Abstract: Responses to misconceptions given by human conversational partners often contain information refuting the possible reasoning which may have led to the misconceptions This work describes generating such responses by reasoning on a highlighted model of the user to identify possible sources of the error Domain-independent structural characterizations of a highlighted user model which suggest the source of several types of misconceptions are identified Each is associated with a response strategy The system can respond to a particular misconception by consulting the highlighted user model for one of the identified structural configurations and responding with the associated strategy Transcripts of misconceptions corrected by human conversational partners show, however, that misconception responses must reflect the user's perspective on the objects involved This context-dependent aspect of correcting misconceptions is captured by a new notion of object perspective which serves to highlight certain aspects of the user model due to the preceding discourse

Realism About User Modeling

Abstract: The object of this chapter is to explore the issues raised by user modeling from an analytic point of view. It is generally assumed that systems cooperating with human beings, and especially systems with natural language interfaces, need, and can get, user models. There is also a widespread assumption that the more user model the better and, correspondingly that, while we may not yet see quite how to do it, there is no problem in principle about being able to construct ever richer models.

Graphical specification of flexible user interface displays

Abstract: This paper describes the implementation concepts behind the user interface editor of the Apogee UIMS. This editor allows many aspects of a user interface to be specified graphically without a conventional textual specification. The system supports the specification of flexible user interfaces — ones that can adapt automatically to changes in the size of objects they present and that can adapt to specific user needs in a dynamic and responsive fashion. To serve as an implementation base for this editor, the Apogee UIMS supports an active data model based on one-way constraints. This model is implemented by a small object-oriented programming language embedded within the system.

Logic and computation in MATHPERT: an expert system for learning mathematics

Abstract: MATHPERT (as in “Math Expert”) is an expert system in mathematics explicitly designed to support the learning of algebra, trigonometry, and first semester calculus. This paper gives an overview of the design of MATHPERT and goes into detail about some connections it has with automated theorem proving. These connections arise at the borderline between logic and computation, which is to be found when computational “operators” have logical side conditions that must be satisfied before they are applicable. The paper also explains how MATHPERT maintains and uses an internal model of its user to produce individually tailored explanations, and how it dynamically generates individualized and helpful error messages by comparing user errors to its own internal solution of the problem.

Learning the User’s Language: A Step Towards Automated Creation of User Models

Abstract: No matter how comprehensive the coverage of a natural language interface, users will invariably provide unparsable input: idiosyncratic phrases, linguistically deviant utterances, or sentences simply beyond the linguistic sophistication of the interface Although individual users differ significantly from each other in their preferred linguistic expression, they show surprising consistency in multiple interactions over time Addressing both observations, a general framework is developed for automated adaptation to the preferred and idiosyncratic linguistic behavior of individual users In essence, a method for flexible recovery and completion of partial parses is developed, with subsequent individualized extensions to a base grammar Thus, the system adapts to the user by growing its grammar dynamically to acquire her preferred forms of expression and recognize them directly in future interactions

But What Will the Listener Think? Belief Ascription and Image Maintenance in Dialog

Abstract: If the users of dialog systems which employ user models are to interpret the system’s behavior accurately, they must have some understanding of the content of the user model and the purposes for which the system is exploiting it. This fundamental issue has received little attention in user modeling research, but the users and designers of such systems can learn much from their own experience in everyday dialog. Listeners know that the form and content of a speaker’s utterance depends on how the speaker assesses the listener’s goals and beliefs, and also on the speaker’s own dialog motivation. Listeners thus take these factors into account when interpreting utterances, and in particular their interpretations may be incorrect if their assumptions about the speaker are inaccurate. Consequently, speakers often make special efforts to control the image that the listener has of their dialog motivation and their model of the listener. In this chapter, these phenomena are analyzed systematically and illustrated with a simulation model for a restricted type of everyday dialog.

SC-UM: user modeling in the SINIX consultant

Abstract: The SC (SINIX∗ Consultant) system is a natural language help facility for the SZNIX operating system. In order to offer individual help to a user, SC uses assumptions about the knowledge of the user. The user modeling module SC-UM provides a priori knowledge in the form of prototypical user models gained from a study of the typical knowledge of SINIX users with different levels of sophistication. In addition, an individual user model is constructed during the course of a session. Each update of the individual user model causes a new assignment of the user to a prototypical user model. ∗ SINIX is a UNIX derivative developed by Siemens AG.

Incorporating User Models into Expert Systems for Educational Diagnosis

Abstract: In this chapter we study a particular real-world domain, that of educational diagnosis. We argue that expert systems for educational diagnosis require user models, and that these user models should include several components, including the user’s background knowledge of both the student and the domain as well as the user’s goals. Our proposal is directed at enhancing the particular expert system of the CGD project. We then propose an architecture for this expert system that separates the knowledge base into relevant components and includes a user model. We further demonstrate that this divided model for the system facilitates providing the best response for a particular user, according to his background knowledge of the domain and of the student and his goals. Finally we argue that the techniques outlined here will be useful in general in expert systems, to vary the response to the user at hand.

How would your favourite user model cope with these scenarios

Abstract: In a paper presented at the 1987 CHI conference (Young & Barnard, 1987), we proposed the use of scenarios as one methodological route to the development of user models of broader scope. In this article we summarise the argument and present five such scenarios as a challenge to the state of the art in user modelling. We invite the reader to ponder the question: How well would your favourite user modelling technique handle some, most, or all of these scenarios? And have you any further scenarios to add to those presented here?

The design and implementation of an intelligent interface for information retrieval

Abstract: Commercial information (text) retrieval systems have been available since the early 1960's. While they have provided a service allowing individuals to find useful documents out of the millions of documents contained in online databases, there are, a number of problems that prevent the user from being more effective. The primary problems are an inadequate means for specifying information needs, a single way of responding to all users and their information needs, and an inadequate user interface. This thesis describes the design and implementation of I$\sp3$R, an intelligent interface for information retrieval the purpose of which is to overcome the limitations of current information retrieval systems by providing multiple ways of assisting the user to precisely specify his information need and to search for information. The system organization is based on a blackboard architecture and consists of a number of "experts" that work cooperatively to assist the user. The operation of the experts is coordinated by a control expert that makes its decisions based on a plan derived from the analysis of human search intermediaries, end user dialogues, and user model. The experts provide multiple formal search strategies, the use and collection of domain knowledge, and browsing assistance. The operation of the system is demonstrated by four scenarios.

Modeling user interface-application interactions

Abstract: The authors describe how to model the interface between the user interface and the application. Their conceptual modeling system contains constructs and abstraction mechanisms that structure knowledge in a model. They use the interaction semantics of a spreadsheet to illustrate the practical applications of their system. >