Abstract
A scientific problem solving environment should be built in such a way that users (scientists) might exploit underlying technologies without a specialised knowledge about available tools and resources. An adaptive user interface can be considered as an opportunity in addressing this challenge. This paper explores the importance of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments. In total, seven human factors (gender, learning abilities, locus of control, attention focus, cognitive strategy and verbal and nonverbal IQs) have been evaluated regarding their impact on interface adjustments done manually by users. People’s preferences for different interface configurations have been investigated. The experimental study suggests criteria for the inclusion of human factors into the user model guiding and controlling the adaptation process. To provide automatic means of adaptation, the Intelligent System for User Modelling has been developed.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
ACM (2002) The adaptive Web [special issue]. Commun ACM 45(5):1–120
Benyon D (1993) Adaptive system: a solution to usability problems. User Model User-Adapt Interact 3(1):65–86
Billingsley P (1986) Probability and measure, 2nd edn. Wiley, New York
Bishop YM, Feinberg SE, Holland PW (1975) Discrete multivariate analysis: theory and practice. MIT Press, Cambridge, MA
Brusilovsky P, Su H-D (2002) Adaptive visualization component of a distributed Web-based adaptive educational system. In: Cerri SA, Gouardères G, Paraguaçu F (eds) Intelligent tutoring systems, Proceedings of the 6th international conference, ITS 2002, Biarritz, France and San Sebastian, Spain, LNCS 2363, Springer, Berlin Heidelberg New York, pp 229–238
Cattell RB (1990) Advances in cattellian personality theory. In: Pervin LA (ed) Handbook of personality: theory and research. Guildford, New York, pp 101–110
Chek D, Ngo L, Seng Teo L, Byrne JG (2002) Evaluating interface esthetics. Knowl Inf Syst 4(1):46–79
Chen S, Magoulas G (2004) Adaptable and adaptive hypermedia systems. IRM, Hershey, PA, USA
Chin DN (2000) Strategies for expressing concise, helpful answers. Artif Intell 14(4–5):333–350
Chonacky N, Winch D (2005) Maple, mathematica, and Matlab: the 3M's without the tape. Comput Sci Eng 5:8–16
Coats R, Vlaeminke I (1990) Man–Computer interfaces. Blackwell Scientific, Oxford
Gavrilova T, Zudilova E, Voinov A (1995) User modeling technology in intelligent system design and interaction. In: Brusilovsky P (ed) Proceedings of the East–West international conference on human–computer interaction, EWHCI'95, Moscow, Russia, vol. 2, pp 115–128
Fine SS, Coats CJ, Hanna JA, Loughlin DH, McHenry JN, Mathur R, Smith WT, Wheeler NJM (1998) The environmental decision support system: a capable and versatile contribution to a community modeling and analysis system for air quality. In: Pepper DW, Brebbia CA, Zannetti P (eds) Development and application of computer techniques to environmental studies. WIT, Boston, pp 317–326
Foster I, Kesselman C (eds) (2003) The grid: blueprint for a new computing infrastructure, 2nd edn. Morgan Kaufmann, San Mateo, CA
Francisco-Revilla L, Shipman FM (2000) Adaptive medical information delivery combining user, task, and situation model. In: Proceedings of the international conference on intelligent user interface, New Orleans, LA, USA, pp 94–97
Hettinger LJ, Cress JD, Brickman BJ, Haas MW (1996) Adaptive interfaces for advanced airborne crew stations. In: Proceedings of the 3rd annual symposium on human interaction with complex systems IEEE Computer Society, Dayton, Ohio, USA, pp 188–192
Hitt J, Deaton J (1999) Design ergonomics: a Review. Ergon Des 7(2):35–36
Houstis E, Gallopolous S, Rice JR, Bramley R (2000) Enabling technologies for Computational science: frameworks, middleware, and environments. Kluwer, Boston
Kobsa A (2004) Adaptive interfaces. In: Bainbridge WS (ed) Encyclopedia of human–computer interaction. Berkshire, Great Barrington, MA
Kim H-J, Lee S-G (2004) An intelligent information system for organising online text documents. Knowl Inf Syst 4(1):125–149
Kim Y, Ra I, Kim B, Hariri S, Woo Park H (2004) A grid-enabled adaptive problem solving environment. In: Proceedings of the second European acrossgrids conference (AxGrids 2004), Nicosia, Cyprus, LNCS 3165, pp 119–128
Mandel T (1997) The elements of user interface design. Wiley, New York
McGraw K, Harbison K (1997) User-centered requirements: the scenario-based engineering process. Laurence Erlbaum, Mahwah, NY, USA
Meister D (1994) Psychology of system design. Adv Hum Factors/Ergon 17:719–722
Minsky M (1975) A framework for representing knowledge. In: Winston PH (ed) The psychology of computer vision. McGraw-Hill, New York
Montoy-Berthome M (1993) Generating self-adaptive human–computer interface. In: Brusilovsky P (ed) Proceedings of East–West international conference on human–computer interaction (EWHCI'93), Moscow, Russia, vol 2, pp 193–203
Murray D, Bevan N (1985) The social psychology of computer conversations. In: Shackel B (ed) Human–computer interaction (INTERACT'84). Elsevier, New York
Parmee IC (2001) Evolutionary and adaptive computing in engineering design. Springer-Verlag, London
Raskin J (2000) The humane interface: new directions for designing interactive systems. Addison-Wesley, Reading, MA
Rasmussen NJ, Hurecon S (2000) Designing to support adaptation. In: Proceedings of the IEA 2000/HFES 2000 Congress, San-Diego, USA, pp 25–30
Raven JC (1960) Standard progressive matrices. Lewis, Boca Raton, FL, USA
Rich E (1983) Users as individuals: individualizing user models. Int J Man-Mach Stud 18:199–214
Rothrock L, Koubek R, Fuch F, Haas M, Salvendy G (2002) Review and reappraisal of adaptive interfaces: toward biologically inspired paradigms. Theor Iss Ergon Sci 3(1):47–84
Rotter JB (1978) Generalized expectancies for problem solving and psychotherapy. Cogn Ther Res 2:1–10
Rouse WB, Geddes ND, Curry RE (1988) Architecture for intelligent interfaces: outline of an approach to supporting operators of complex systems. Hum-Comput Interact 3:87–122
Siegmund D (1985) Sequential analysis: tests and confidence intervals. Springer Series in Statistics. Springer, New York
Stephanidis C (2001) User interfaces for all: concepts, methods, and tools. Human Factors and Ergonomics Series. Laurence Erlbaum, Mahwah, NY, USA
Su Z, Yang Q, Zhang H, Xu X, Hu Y-H, Ma S (2002) Correlation-based web document clustering for adaptive Web interface design. Knowl Inf Syst 4(2):151–167
Vasilyeva E, Pechenizkiy M, Puuronen S (2005) Towards the framework of adaptive user interfaces for ehealth. In: Proceedings of the 18th IEEE symposium on computer-based medical systems (CBMS'05), Trinity College, Dublin, Ireland, pp 139–144
Vredenburg K, Isensee S, Righi C (2001) User-centered design: an integrated approach. Prentice-Hall, Englewood Cliffs, NJ
Wagner E (1992) A system ergonomics design methodology for HCI development. In: Brusilovsky (ed) Proceedings of the East–West international conference on human–computer interaction (EWHCI'92), St. Petersburg, Russia, pp 388–407
Weld DS et al (2003) Automatically personalizing user interfaces. In: Proceedings of the international joint conference on artificial intelligence (IJCAI 03), Acapulco, Mexico, pp 1613–1619
Wickens CD (1992) Engineering psychology and human performance, 2nd edn. HarperCollins, New York
Zudilova EV, Sloot PMA (2005) Bringing combined interaction to a problem solving environment for vascular reconstruction. Future Gener Comput Syst 21(7):1167–1176
Zudilova EV, Sloot PMA (2002) A first step to a user-centered approach to a development of adaptive simulation–visualization complexes. In: Proceedings of the international conference of the systemics, cybernetics and informatics, Orlando, FL, July, vol V, pp 104–110
Zudilova EV (1996) Some aspects of user computerized testing. In: Brusilovsky P (ed) Proceedings of the East–West international conference on human–computer interaction–-human aspects of business computing (EWHCI'96), Moscow, Russian Federation, pp 146–156
Zudilova EV (1998) Design and development of adaptive interfaces based on a user model. PhD Thesis, St. Petersburg State Technical University, Russian Federation, April.
Author information
Authors and Affiliations
Corresponding author
Additional information
Elena Zudilova-Seinstra is a Senior Researcher at the Scientific Visualisation and Virtual Reality Group of the University of Amsterdam. Previously, she worked for the Corning Scientific Centre. Apart from being a researcher, in 1999–2002 she was a part-time Assistant Professor at the St. Petersburg Academy of Management Methods and Techniques. She received her M.S. degree in technical engineering in 1993 and Ph.D. in computer science in 1998 from the St. Petersburg State Technical University. In 1996, she received an award for R&D from the Welles-Johnson Foundation of Maryland. She is a Program Committee Member of several International Conferences and Workshops. Her current research interests include multi-modal and adaptive interaction, scientific visualisation, virtual and augmented reality, ambient intelligence and usability studies. She has more than 40 research publications and three editorials in these areas. Also, she has been an INTAS evaluator since February 2005.
Rights and permissions
Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License ( https://creativecommons.org/licenses/by-nc/2.0 ), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
About this article
Cite this article
Zudilova-Seinstra, E. On the role of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments. Knowl Inf Syst 13, 243–270 (2007). https://doi.org/10.1007/s10115-006-0061-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10115-006-0061-3