Adaptivity in graphical user interfaces: an experimental framework

Abstract Several user and task modeling approaches evolved during the past years and were applied to certain problem areas showing different strengths and weaknesses. A qualitative comparison of these approaches and techniques is difficult since the application and experimentation environments vary. On the other hand, the integration of approved user modeling techniques with different application environments is usually difficult if not impossible. We propose a framework that, in a first step, allows the direct comparison of results of different user and task modeling approaches in graphical user interfaces. The objective is the development of appropriate adaptive help systems for new and existing applications. The system is therefore designed as a client-server architecture to support multi-user operation. The implementation can be easily adapted to different application systems. Applications can be upgraded in a well-defined way, and with a minimal amount of effort by using the approach and tools presented in this paper. A prototype-implementation is presented consisting of an interaction protocoling and managing kernel, a user evaluating module and a corresponding adaptive help system applied to sample medical and CAD experimentation environments.

[1]  Jirí Benes,et al.  On neural networks , 1990, Kybernetika.

[2]  Christoph G. Thomas,et al.  An adaptive environment for the user interface of Excel , 1993, IUI '93.

[3]  L. M. Encarnaçāo,et al.  Direct Graphic User Interaction with Modelers Based on Constructive Solid Geometry , 1992, Graphics Modeling and Visualization in Science and Technology.

[4]  Lotfi A. Zadeh,et al.  Knowledge Representation in Fuzzy Logic , 1996, IEEE Trans. Knowl. Data Eng..

[5]  Barbara Smith,et al.  The role of built-in knowledge in adaptive interface systems , 1993, IUI '93.

[6]  Martin Göbel,et al.  Graphics Modeling and Visualization in Science and Technology , 1993, Beiträge zur Graphischen Datenverarbeitung.

[7]  Pattie Maes,et al.  A learning interface agent for scheduling meetings , 1993, IUI '93.

[8]  Angel R. Puerta The study of models of intelligent interfaces , 1993, IUI '93.

[9]  Chaochang Chiu,et al.  An Adaptive Intelligent Help System , 1993, HCI.

[10]  Grady Booch,et al.  Object-Oriented Analysis and Design with Applications , 1990 .

[11]  H H Ehricke,et al.  Imaging and graphics in medicine: concept of an object-oriented platform for clinical research. , 1995, Computer methods and programs in biomedicine.

[12]  L. A. Zedeh Knowledge representation in fuzzy logic , 1989 .

[13]  Anthony F. Norcio,et al.  Modeling users with neural architectures , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[14]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[15]  David L. Waltz,et al.  Toward memory-based reasoning , 1986, CACM.

[16]  Frank Berger,et al.  Intelligent user support in graphical user interfaces , 1992 .

[17]  James A. Hendler,et al.  Readings in Planning , 1994 .

[18]  Klaus-Jürgen Quast Plan recognition for context sensitive help , 1993, IUI '93.

[19]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[20]  Thomas Kuehme Adaptive Action Prompting: A Complementary Aid to Support Task-Oriented Interaction in Explorative User Interfaces , 1993 .

[21]  Hogler Kirschner,et al.  Reasoning on domain knowledge level in human-computer interaction , 1994 .