Topic
User modeling
About: User modeling is a research topic. Over the lifetime, 10701 publications have been published within this topic receiving 278012 citations.
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TL;DR: The objectives, progress, and unfulfilled hopes that have occurred over the last ten years are reviewed, and some interesting computational environments and their underlying conceptual frameworks are illustrated.
Abstract: A fundamental objective of human–computer interaction research is to make systems more usable, more useful, and to provide users with experiences fitting their specific background knowledge and objectives. The challenge in an information-rich world is not only to make information available to people at any time, at any place, and in any form, but specifically to say the “right” thing at the “right” time in the “right” way. Designers of collaborative human–computer systems face the formidable task of writing software for millions of users (at design time) while making it work as if it were designed for each individual user (only known at use time). User modeling research has attempted to address these issues. In this article, I will first review the objectives, progress, and unfulfilled hopes that have occurred over the last ten years, and illustrate them with some interesting computational environments and their underlying conceptual frameworks. A special emphasis is given to high-functionality applications and the impact of user modeling to make them more usable, useful, and learnable. Finally, an assessment of the current state of the art followed by some future challenges is given.
775 citations
TL;DR: This article considers cases of both success and failure in past user interface tools, and extracts a set of themes which can serve as lessons for future work.
Abstract: A user interface software tool helps developers design and implement the user interface. Research on past tools has had enormous impact on today's developers—virtually all applications today are built using some form of user interface tool. In this article, we consider cases of both success and failure in past user interface tools. From these cases we extract a set of themes which can serve as lessons for future work. Using these themes, past tools can be characterized by what aspects of the user interface they addressed, their threshold and ceiling, what path of least resistance they offer, how predictable they are to use, and whether they addressed a target that became irrelevant. We believe the lessons of these past themes are particularly important now, because increasingly rapid technological changes are likely to significantly change user interfaces. We are at the dawn of an era where user interfaces are about to break out of the “desktop” box where they have been stuck for the past 15 years. The next millenium will open with an increasing diversity of user interface on an increasing diversity of computerized devices. These devices include hand-held personal digital assistants (PDAs), cell phones, pages, computerized pens, computerized notepads, and various kinds of desk and wall size-computers, as well as devices in everyday objects (such as mounted on refridgerators, or even embedded in truck tires). The increased connectivity of computers, initially evidenced by the World Wide Web, but spreading also with technologies such as personal-area networks, will also have a profound effect on the user interface to computers. Another important force will be recognition-based user interfaces, especially speech, and camera-based vision systems. Other changes we see are an increasing need for 3D and end-user customization, programming, and scripting. All of these changes will require significant support from the underlying user interface sofware tools.
761 citations
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TL;DR: This work reviews work on Bayesian user models that can be employed to infer a user's needs by considering a users' background, actions, and queries and proposes an overall architecture for an intelligent user interface.
Abstract: The Lumiere Project centers on harnessing probability and utility to provide assistance to computer software users. We review work on Bayesian user models that can be employed to infer a users needs by considering a user's background, actions, and queries. Several problems were tackled in Lumiere research, including (1) the construction of Bayesian models for reasoning about the time-varying goals of computer users from their observed actions and queries, (2) gaining access to a stream of events from software applications, (3) developing a language for transforming system events into observational variables represented in Bayesian user models, (4) developing persistent profiles to capture changes in a user expertise, and (5) the development of an overall architecture for an intelligent user interface. Lumiere prototypes served as the basis for the Office Assistant in the Microsoft Office '97 suite of productivity applications.
751 citations
TL;DR: This paper defines user adaptation as the cognitive and behavioral efforts performed by users to cope with significant information technology events that occur in their work environment and identifies four adaptation strategies which are hypothesized to result in three different individual-level outcomes.
Abstract: This paper defines user adaptation as the cognitive and behavioral efforts performed by users to cope with significant information technology events that occur in their work environment. Drawing on coping theory, we posit that users choose different adaptation strategies based on a combination of primary appraisal (i.e., a user's assessment of the expected consequences of an IT event) and secondary appraisal (i.e., a user's assessment of his/her control over the situation). On that basis, we identify four adaptation strategies (benefits maximizing, benefits satisficing, disturbance handling, and self-preservation) which are hypothesized to result in three different individual-level outcomes: restoring emotional stability, minimizing the perceived threats of the technology, and improving user effectiveness and efficiency. A study of the adaptation behaviors of six account managers in two large North American banks provides preliminary support for our model. By explaining adaptation patterns based on users' initial appraisal and subsequent responses to an IT event, our model offers predictive power while retaining an agency view of user adaptation. Also, by focusing on user cognitive and behavioral adaptation responses related to the technology, the work system, and the self, our model accounts for a wide range of user behaviors such as technology appropriation, avoidance, and resistance.
750 citations
TL;DR: This paper empirically test and confirm the basic tenants of lead user theory, and provides a first empirical analysis of the independent effects of its two key component variables, and finds that adding measures of users' local resources can improve the ability of the lead user construct to identify commercially attractive innovations under some conditions.
Abstract: Firms and governments are increasingly interested in learning to exploit the value of lead user innovations for commercial advantage. Improvements to lead user theory are needed to inform and guide these efforts. In this paper we empirically test and confirm the basic tenants of lead user theory. We also discover some new refinements and related practical applications.Using a sample of users and user-innovators drawn from the extreme sport of kite surfing, we analyze the relationship between the commercial attractiveness of innovations developed by users and the intensity of the lead user characteristics those users display. We provide a first empirical analysis of the independent effects of its two key component variables. In our empirical study of user modifications to kite surfing equipment, we find that both components independently contribute to identifying commercially attractive user innovations. Component 1 (the "high expected benefits" dimension) predicts innovation likelihood, and component 2 (the "ahead of the trend" dimension) predicts both the commercial attractiveness of a given set of user-developed innovations and innovation likelihood due to a newly-proposed innovation supply side effect. We conclude that the component variables in the lead user definition are indeed independent dimensions and so neither can be dropped without loss of information - an important matter for lead user theory. We also find that adding measures of users' local resources can improve the ability of the lead user construct to identify commercially-attractive innovations under some conditions.The findings we report have practical as well as theoretical import. Product modification and development has been found to be a relatively common user behavior in many fields. Thus, from 10% to nearly 40% of users report having modified or developed a product for in-house use in the case of industrial products, or for personal use in the case of consumer products, in fields sampled to date. As a practical matter, therefore, it is important to find ways to selectively identify the user innovations that manufacturers will find to be the basis for commercially attractive products in the collectivity of user-developed innovations. We discuss the implications of these findings for theory and also for practical applications of the lead user construct, i.e. how variables used in lead user studies can profitably be adapted to fit specific study contexts and purposes.
742 citations