Design and evaluation of an adaptive icon toolbar

As information systems become increasingly important in many different domains, the potential to adapt them to individual users and their needs also becomes more important. Adaptive user interfaces offer many possible ways to adjust displays and improve procedures for a user's individual patterns of work. This paper describes an attempt to design an adaptive user interface in a computer environment familiar to many users. According to one classification of adaptive user interfaces, the adaptive bar described in this paper would be classified as a user-controlled self-adaptation system.At the user's convenience, the adaptive bar offers suggestions for adding or removing command icons, based on the frequency and probability of specific commands. It also implements these changes once the user has agreed to them. Beyond the adaptive bar, the general behavior of the whole user interface does not change, thereby allowing the user to maintain a clear general model of the system. This paper describes the decision-making algorithm implemented in the bar. It also describes the bar's self-adaptive behavior of displaying the frequency of each icon's use through the icon's size. Finally, we present some encouraging preliminary results of evaluations by users.     

Adaptive systems: from intelligent tutoring to autonomous agents

Computer systems which can automatically alter aspects of their functionality or interface to suit the needs of individuals or groups of users have appeared over the years in a variety of guises. Most recently, attention has focused on intelligent interface agents, which are seen as specialised, knowledge-based systems acting on behalf of the user in some aspect of the interaction. Similar requirements for automatic adaptation have been noted in intelligent tutoring systems, natural-language systems and intelligent interfaces. The paper brings together the research which has emanated from a number of backgrounds, and provides a unifying perspective on adaptive systems in general. An architecture for adaptive systems and a methodology for their development are presented. The paper also describes software support for producing adaptive systems, and offers some experimental evidence to justify both the desirability and feasibility of exploiting an adaptive system approach to human-computer interaction     

Applying user modeling to human-computer interaction design

Since the early 1980's, intelligent and adaptive systems have appeared and have been written about in a variety of guises. Although there are many differences between such systems as adaptive user interfaces, intelligent help systems and explanation systems, there are many similarities as well. The most notable of these is that they all require user models to be maintained and exploited as part of their designs. Furthermore, they share the same high level architecture. This paper discusses the use of models in human-computer interaction design and offers a common architecture for these adaptive systems. A methodology for the development of these systems is presented.This is based on our experimental work which is reported fully in Jennings, Benyon and Murray, 1991 and Jennings and Benyon, in press)     

User modelling for adaptive computer systems: a survey of recent developments

User modelling is becoming an important sub-area of Artificial Intelligence with both theoretical and practical consequences. The theoretical foundations of user modelling are to be found in key areas of AI, such as knowledge representation and plan recognition, while its practical applications impinge on the construction of intelligent user interfaces and adaptive systems. This paper provides a survey of current work in user modelling. The paper begins by distinguishing between AI approaches, which are the subject of this survey, and those of HCI (Human-Computer Interaction) and then considers the major issues in user modelling such as: types of user modelling system, the sorts of information modelled, how the information is acquired, represented and used. The paper concludes by examining some of the more problematic aspects of user modelling as well as indicating areas for future research.     

From user interface design to the support of intelligent and adaptive interfaces: an overhaul of user interface software infrastracture

Research on adaptive interfaces in the past has lacked support from user interface tools which allow interfaces to be easily created and modified. Also, current user interface tools provide no support for user models which can collect task-oriented information about users. Developing an adaptive interface requires a user model and an adaptation strategy. It also, however, requires a user interface which can be adapted. The latter task is often time-consuming, especially in relation to more sophisticated user interfaces.

The paper presents a user interface design environment, UIDE, which has a different software infrastracture. Designers use high-level specifications to create a model of an application and links from the application to various interface components. The model is the heart of all the design and run-time support in UIDE, including automatic dialog sequencing and help generation. UIDE provides automatic support for collecting task-oriented information about users, by the use of its high-level specifications in its application model as a basic construct for a user model. Some examples of adaptive interfaces and adaptive help are presented that use the information that is collectable in UIDE.     

A glass box approach to adaptive hypermedia

Utilising adaptive interface techniques in the design of systems introduces certain risks. An adaptive interface is not static, but will actively adapt to the perceived needs of the user. Unless carefully designed, these changes may lead to an unpredictable, obscure and uncontrollable interface. Therefore the design of adaptive interfaces must ensure that users can inspect the adaptivity mechanisms, and control their results. One way to do this is to rely on the user's understanding of the application and the domain, and relate the adaptivity mechanisms to domain-specific concepts. We present an example of an adaptive hypertext help system POP, which is being built according to these principles, and discuss the design considerations and empirical findings that lead to this design.     

Adaptive hypertext navigation based on user goals and context

Hypertext systems allow flexible access to topics of information, but this flexibility has disadvantages. Users often become lost or overwhelmed by choices. An adaptive hypertext system can overcome these disadvantages by recommending information to users based on their specific information needs and preferences. Simple associative matrices provide an effective way of capturing these user preferences. Because the matrices are easily updated, they support the kind of dynamic learning required in an adaptive system.HYPERFLEX, a prototype of an adaptive hypertext system that learns, is described. Informal studies with HYPERFLEX clarify the circumstances under which adaptive systems are likely to be useful, and suggest that HYPERFLEX can reduce time spent searching for information by up to 40%. Moreover, these benefits can be obtained with relatively little effort on the part of hypertext authors or users.The simple models underlying HYPERFLEX's performance may offer a general and useful alternative to more sophisticated modelling techniques. Conditions under which these models, and similar adaptation techniques, might be most useful are discussed.     

Methods and techniques of adaptive hypermedia

Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. Adaptive hypermedia (AH) systems build a model of the individual user and apply it for adaptation to that user, for example, to adapt the content of a hypermedia page to the user's knowledge and goals, or to suggest the most relevant links to follow. AH systems are used now in several application areas where the hyperspace is reasonably large and where a hypermedia application is expected to be used by individuals with different goals, knowledge and backgrounds. This paper is a review of existing work on adaptive hypermedia. The paper is centered around a set of identified methods and techniques of AH. It introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.     

Toward the adaptation of component‐based architectures by model transformation: behind smart user interfaces

Graphical user interfaces are not always developed for remaining static. There are GUIs with the need of implementing some variability mechanisms. Component‐based GUIs are an ideal target for incorporating this kind of operations, because they can adapt their functionality at run‐time when their structure is updated by adding or removing components or by modifying the relationships between them. Mashup user interfaces are a good example of this type of GUI, and they allow to combine services through the assembly of graphical components. We intend to adapt component‐based user interfaces for obtaining smart user interfaces. With this goal, our proposal attempts to adapt abstract component‐based architectures by using model transformation. Our aim is to generate at run‐time a dynamic model transformation, because the rules describing their behavior are not pre‐set but are selected from a repository depending on the context. The proposal describes an adaptation schema based on model transformation providing a solution to this dynamic transformation. Context information is processed to select at run‐time a rule subset from a repository. Selected rules are used to generate, through a higher‐order transformation, the dynamic model transformation. This approach has been tested through a case study which applies different repositories to the same architecture and context. Moreover, a web tool has been developed for validation and demonstration of its applicability. The novelty of our proposal arises from the adaptation schema that creates a non pre‐set transformation, which enables the dynamic adaptation of component‐based architectures. Copyright © 2014 Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive personalized interfaces—A question of viability

It is widely accepted that interfaces between computers and users should differ to accommodate individual, or group, needs. One method of 'personalizing' an interface is to have the system form a limited model of the user and employ it to fashion the dialogue to his needs. Unfortunately, little is known about the effect of adaptation on the man-machine interface. Although obvious advantages accrue from 'personalized' interfaces, there are also obvious disadvantages to presenting users with a changing, adapting and perhaps apparently inconsistent interface. The goal of this work is to determine the viability of an adaptive interface through a human-factor pilot study of a simple, specially designed, interactive computer system. The system uses menu-driven selection to retrieve entries from a large ordered telephone directory. This simple task has several advantages: it is a realistic application area for interactive computers; plausible adaptive modelling methods exist and have been studied theoretically; and previous work has determined the best way to display the menus to users. The results of this empirical study support the use of adaptive user modelling. In the (admittedly highly constrained) example system, a computer interface can indeed adapt successfully to every user. Although it does not necessarily generalize to other user interfaces, the result supplies evidence to refute published objections to adaptive user modelling in general.