Skip to main content
Log in

The Role of Cognitive Modeling for User Interface Design Representations: An Epistemological Analysis of Knowledge Engineering in the Context of Human-Computer Interaction

  • Published:
Minds and Machines Aims and scope Submit manuscript

Abstract

In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer.

We show that in a first step it is necessary to study and investigate the different levels and forms of representation that are involved in the interaction processes between computers and human cognitive systems. Only if designers have achieved some understanding about these representational mechanisms, user interfaces enabling individual experiences and skill development can be designed. In this paper we review mechanisms and processes for knowledge representation on a conceptual, epistemological, and methodologieal level, and sketch some ways out of the identified dilemmas for cognitive modeling in the domain of human-computer interaction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Anderson J.R. (1983), The Architecture of Cognition, Cambridge, Massachusetts, Harvard University Press.

    Google Scholar 

  • Anderson J.R. (1990), Cognitive Psychology and its Implications, 3rd edition, New York: W.H. Freeman

    Google Scholar 

  • Anderson J.A, Pellionisz A. and Rosenfeld E. (1991), Neurocomputing 2. Directions of Research Cambridge, MA, (eds.) MIT Press.

  • Bainbridge L. (1991) Mental Models in Cognitive Skills, in: (eds.): A. Rutherford and Y. Rogers, Models in the Mind, New York, Academic Press.

    Google Scholar 

  • Becker A.L. (1991), ‘A Short Essay on Languaging’, in F. Steier, (ed), Research and Reflexivity, London; Newbury Park, CA, SAGE Publishers. pp. 226–234.

    Google Scholar 

  • Benett J.L., Lorch D.J., Kieras D.E., and Polson P.G. (1987), ‘Developing a User Interface Technology for use in Industry, Proceedings INTERACT’87, IFIP, pp. 21–26, Elsevier (North Holland), 1987.

    Google Scholar 

  • Berry, D.C. (1987), ‘The Problem of Implicit Knowledge’, in Experts Systems, 4,(3).

  • Boden M.A. (ed.) (1990), The Philosophy of Artificial Intelligence, New York, Oxford University Press.

    Google Scholar 

  • Böhle, F. and Milkau, B. (1988), ‘Computerized Manufacturing and Empirical Knowledge’, in AI & Society; 2,(3), pp. 235–243.

    Google Scholar 

  • Brown T.H., Ganong A.H., Kariss E.W. and Keenan C.L. (1990), Hebbian Synapses: Biophysical Mechanisms and Algorithms Annual Review of Neuroscience, 13, 475–511.

    Google Scholar 

  • Caroll J.M. and Olson J.R. (1988), ‘Mental Models in Human-Computer Interaction’ in: Handbook of Human-Computer Interaction, M. Helander (ed), Elsevier, pp. 45–65.

  • Cherniak, Ch. (1988), ‘Undebuggability and Cognitive Science’, Communication of the ACM, 31,(4), pp. 402–412.

    Google Scholar 

  • Churchland P.M. (1991), ‘A Deeper Unity: Some Feyerabendian Themes in Neuro-Computational Form’, in G. Munevar (ed.), Beyond reason: Essays on the Philosoplay of Paul Feyerabend, Kluwer Academic Publishers, Dordrecht, Boston, pp. 1–23. (reprinted in R.N.Giere (ed.), Cognitive models of science, Minnesota Studies in the Philosophy of Science XV.

    Google Scholar 

  • Churchland P.S., Koch C. and Sejnowski T.J. (1990), ‘What is computational neuroscience?’ in E.L. Schwartz, (ed), Computationnl Neuroscience. Cambridge, MA, MIT Press.

    Google Scholar 

  • Churchland P.S. and Sejnowski T.J. (1992), The computational Brain. Cambridge, MA, MIT Press.

    Google Scholar 

  • Devitt M. and Sterelny, K. (1987), Language and Reality. An Introduction to the Philosophy of Language, Cambridge, MA, MIT Press.

    Google Scholar 

  • Dix A., Finlay J., Abowd G. and Beale R. (1993), Human-Computer Interaction, New York, Prentice Hall.

    Google Scholar 

  • Downs T. (1987), Reliability ProbIems in Software Engineering — A Review, in Computer Systems, Science and Engineering, 2,(3), pp. 131–147.

    Google Scholar 

  • Dreyfus H.L. and Dreyfus St.E. (1986), Competent Systems: The Only Future for Inference-Making Computers, in Future Generations Computer Systems, 2, pp. 233–244.

    Google Scholar 

  • Duda R.O. and Gaschnig J.G. (1981), Knowledge-Based Expert Systems Coming of Age, in: Byte, 6,(9), pp. 238–278.

    Google Scholar 

  • Eckardt B.v., (1993), What is cognitive science? Cambridge, MA, MIT Press.

    Google Scholar 

  • Eco U., (1976), A Theory of Semiotics. Bloomington, Indiana University Press.

    Google Scholar 

  • Eco U., (1994), Semiotics and the Philosophy of Language. Bloomington, Indiana University Press.

    Google Scholar 

  • Edwards, P.N. (1988), The Closed World: Systems Discourse, Military Strategy, and Post WWII American Histrical Consciousness, in AI & Society, 2,(3), pp. 245–256.

    Google Scholar 

  • Ernst M.L. and Ojha H., (1986), Business Applications of Artificial Intelligence KBs, in Future Generations Computer Systems, 2, pp. 75–116.

    Google Scholar 

  • Feyerabend P.K., (1975), Against Method. London; New York, Verso.

    Google Scholar 

  • Feyerabend P.K., (1975), Realism, Rationalism, and Scientific Method. Philosophical papers I, Vol. I, Cambridge; New York, Cambridge University Press.

    Google Scholar 

  • Feyerabend P.K., (1981), Problems of Empiricism. Philosophical Papers II, Vol. II. Cambridge; New York, Cambridge University Press.

    Google Scholar 

  • Fischer G. (1993), ‘Beyond Human-Computer Interaction: Designing Useful and Usable Commucational Environments’, in Proceedings HCI '93‘, Cambridge University Press, pp. 17–31.

  • Fodor J.A., (1988), Psychosemantics: The Problem of Meaning in the Philosophy of Mind, Cambridge, MA, MIT Press.

    Google Scholar 

  • Gazzaniga M.S., (ed.) (1995), The Cognitive Neurosciences. Cambridge, MA, MIT Press.

    Google Scholar 

  • Gelder T.v. and Port R., (1995), It's About Time: An Overview of the Dynamical Approach to Cognition, in R. Port and T.v. Gelder, (eds), Mind as Motion. Cambridge, MA, MIT Press.

    Google Scholar 

  • Gentner D. and Stevens A.L. (eds). (1983), Mental Models. Hillsdale, NJ, Lawrence Erlbaum.

    Google Scholar 

  • Glasersfeld E.v., (1983), On the Concept of Interpretation. Poetics, 12: 254–274.

    Google Scholar 

  • Glasersfeld E.v., (1984), An introduction to radical constructivism, in P. Watzlawick, (ed.), pp. 17–40. The Invented Reality, New York, Norton.

    Google Scholar 

  • Glasersfeld E.v., (1995), Radical Constructivism: A Way of Knowing and Learning. London, Falmer Press.

    Google Scholar 

  • Goldberg D.E., (1989), Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA, Addison-Wesley.

    Google Scholar 

  • Hanson S.J. and Olson C.R., (1990), Connectionist Modeling and Brain Function: the Developing Interface. Cambridge, MA, MIT Press.

    Google Scholar 

  • Hebb D.O., (1949), The Organization of Behavior; A Neuropsychological Theory, New York, Wiley.

    Google Scholar 

  • Hertz J., Krogh A. and Palmer R.G., (1991), Introduction to the theory of neural computation, volume 1 of Santa Fe Institute studies in the sciences of complexity. Lecture notes. Addison-Wesley, Redwood City, CA, 1991.

    Google Scholar 

  • Holland J.H., (1975), Adaptation in natural and artificial systems: an analysis with applications to biology, control, and artificial intelligence. Ann Arbor, University of Michigan Press.

    Google Scholar 

  • Hutchins E. and Hazelhurst B. (1992), Learning in the Cultural Process, in C.G. Langton, C. Taylor, J.D. Farmer, and S. Rasmussen, (eds.) Artificial Life II, Redwood City, CA, Addison-Wesley, pp. 689–706.

    Google Scholar 

  • Johnson P. (1992), Human-Computer Interaction. Psychology, Task Analysis and Software Engineering, London, McGraw Hill.

    Google Scholar 

  • Johnson-Laird P.N. (1983), Mental Models, Cambridge, MA, Harvard University Press.

    Google Scholar 

  • Johnson-Laird P. (1993), The Computer and the Mind. An Introduction of Cognitive Science, London, Fontana.

    Google Scholar 

  • Kobsa A. and Wahlster W., (eds) (1989), User Models in Dialog Systems. Heidelberg, Springer.

    Google Scholar 

  • Ktandel E.R., Schwartz J.H. and Jessel T.M. (eds.) (1991), Principles of Neural Science. New York, 3rd edn. Elsevier.

    Google Scholar 

  • Kuhn T.S. (1970), The Structure of Scientific Revolutions, Chicago, University of Chicago Press, 2nd edn.

    Google Scholar 

  • Lenat D.B. (1988), When Will Machines Learn?, in Proceedings ‘Int. Conf. on 5th Generation Computer Systems’, ICOT, pp. 1213–1245.

  • Maturana H.R. (1978), Biologie der sprache: die epistemologie der realität, in H.R. Maturana, (ed.), Erkennen: die Organisation und Verkörperung von Wirklichkeit, Vieweg (1982), Braunschweig, pps. 236–271.

  • Maturana H.R. and Varela F.J. (eds.) (1980), Autopoiesis and cognition: the realization of the living, volume 42 of Boston studies in the philosophy of science. Dordrecht, Boston, D. Reiclel Pub. Co.

    Google Scholar 

  • McClelland J.L. and Rumelhart D.E. (eds.) (1986), Parallel Distributed Processing: explorations in the microstructure of cognition. Psychological and biological models, vol II. Cambridge, MA, MIT Press.

    Google Scholar 

  • Mitchell M. and Forrest S. (1994), ‘Genetic Algorithms and Artificial Life,’ Artficial Life, 1(3): 267–291.

    Google Scholar 

  • Moray N. (1993), ‘Formalisms for Cognitive Modeling’, in: Human-Computer Interaction. Applications and Case Studies, Smith, M.J.; Salvendy, G. (eds.), Elsevier, Amsterdam, pp. 581–586.

    Google Scholar 

  • Myers B.A. (1989), ‘Demonstrational Interfaces. A Step Beyond Direct Manipulation’, IEEE Computer, 25(8) pp. 61–73.

    Google Scholar 

  • Newell A. (1980), ‘Physical Symbol Systems’, Cognitive Science, 4: 135–183.

    Google Scholar 

  • Newell A. (1982), The Knowledge Level, in Artificial Intelligence, 18, pp. 87–127.

    Google Scholar 

  • Newell A. (1989), Unified Theories of Cognition, Harvard, University Press.

  • Newell A., Rosenbloom P.S. and Laird J.E. (1989), Symbolic architectures for Cognition. in M.I. Posner (ed.) Foundations of Cognitive Science, Cambridge, MA, MIT Press, pp 93–131.

    Google Scholar 

  • Nicoll R.A., Kauer J.A. and Malenka R.C. (1988), The Current Excitement in Long-Term Potentiation Neuron, 1(2) pp. 97–103.

    Google Scholar 

  • Norman D.A. (1983), Some Observations on Mental Models, in Mental Models, Lawrence Erlbaum, Stevens, A.L. and Gentner, D. (eds.), Hillsdale, New Jersey, pp. 7–14.

  • Olson J.R. and Olson, G.M. (1990), ‘The Growth of Cognitive Modeling in Human-Computer Interaction Since GOMS’, in Human-Computer Interaction, 5,(2 and 3) pp. 221–266.

    Google Scholar 

  • Osherson D.N. and Lasnik H. (eds.) (1990), An Invitation to Cognitive Science, vol 1–-3, Cambridge, MA, MIT Press.

    Google Scholar 

  • Perner J. and Garnham A. (1988), Conditions for Mutuality, in: Journal of Semantics, Vol. 6, pp. 369–385.

    Google Scholar 

  • Peschl M.F. (1990), Cognitive Modelling, Deutscher Universitätsverlag/Vieweg, Wiesbaden.

    Google Scholar 

  • Peschl M.F. (1994), ‘Autonomy vs. Environmental Dependency in Neural Knowledge Representation’, in R. Brooks and P. Maes, (eds.), Artificial Life IV, Cambridge, MA, MIT Press, pp 417–423.

    Google Scholar 

  • Peschl M.F. (1994), ‘Embodiment of Knowledge in the Sensory System and its Contribution to Sensormotor Integration. The Role of Sensors in Representational and Epistemological Issues’, in P. Gaussier and J.D. Nicoud, (eds.), From Perception to Action Conference, Los Alamitos, CA, IEEE Society Press, pps. 444–447.

    Google Scholar 

  • Peschl M.F. (1994), Repräsentation und Konstruktion. Kognitions-und neuroin-formtische Konzepte als Grundlage einer naturalisierten Epistemologie und Wissenschaftstheorie. Vieweg, Braunschweig/Wiesbaden.

    Google Scholar 

  • Peschl M.F. and Stary Ch. (1990), ‘IKARUS-Interdisciplinary Knowledge Reconstruction Based on Rules and Science Theory’, in Proc. of 8th Int. Conference on Systems and Cybernetics, Vol. 2, New York.

  • Polanyi M. (1966), The Tacit Dimension. Garden City, NY, Doubleday.

    Google Scholar 

  • Port R. and Gelder T.v. (eds.) (1995), Mind as Motion: Explorations in the Dynamics of Cognition. Cambridge, MA, MIT Press.

    Google Scholar 

  • Posner M.I. (ed.) (1989), Foundations of Cognitive Science. Cambridge, MA, MIT Press.

    Google Scholar 

  • Preece J (ed.) (1994), Human-Computer Interaction, Wokingham, Addison-Wesley.

    Google Scholar 

  • Ravden S. and Johnson G. (1989), Evaluating Usability of Human-Computer Interaction. A Practical Method. Chicester, Ellis Horwoor.

    Google Scholar 

  • Roth G. (1991), ‘Die Konstitution von Bedeutung im Gehirn’, in S.J. Schmicit, (ed.), Gedächtnis, Suhrkamp, Frankfurt/M., pps 360–370.

  • Roth G. (1994), Das Gehirn und seine Wirklichkeit. Kognitive Neurobiologie und ihre philosophischen Konsequenzen, Suhrkamp, Frankfurt/M., 1994.

  • Rumelhart D.E. and McClelland J.L. (ed.) (1986), Parallel Distributed Processing: explorations in the microstructure of cognition. Foundations, vol 1. Cambridge, MA, MIT Press.

  • Sejnowski T.J. Koch C. and Churchland P.S. (1990), Computational Neuroscience, in S.J. Hanson and C.R. Olson, (eds.), Connectionist Modeling and Brain Function: The Developing Interface, Cambridge, MA, MIT Press, pps 5–35.

    Google Scholar 

  • Shepherd G.M. (ed.) (1990), The Synaptic Organizntion of the Brain. New York, Oxford University Press, 3rd ed.

    Google Scholar 

  • Stacy W. (1995), Cognition and Software Development, in Communications of the ACM, Vol. 38,(6), p. 31.

    Google Scholar 

  • Stary Ch. and Peschl M. (1995), ‘Towards Constructivist Unification of Machine Learning and Parallel Distributed Processing’, in Ford, K., Hayes, P. eds, Android Epistemology, MIT Press.

  • Stary Ch. (1996), Interactive Systems. Software Ergonomics and Software Engineering (2nd edition), in German, Vieweg, Wiesbaden.

    Google Scholar 

  • Sterling P. (1990), Retina, in G.M. Shepherd, (ed), The Synaptic organization of the Brain, New York, Oxford University Press, 3rd ed, pps 170–213.

    Google Scholar 

  • Sticklen J. (1990), ‘Problem Solving Architectures at the Knowledge Level’, in Journal of Experimental and Artificial Intelligence, 1,(1), pp. 1–52.

    Google Scholar 

  • Tauber M.J. (1991), ‘ETAG-Extended Task Action Grammar’, Proceedings INTERACT '91, IFIP, Elsevier.

  • Tessier-Lavigne M. (1991), Phototransduction and Information Processing in the Retina, in E.R. Kandel, J.H. Schwartz, and T.M. Jessel, (eds.), Principles of Neural Science, Elsevier, New York, 3rd edition, pps 400–419.

    Google Scholar 

  • Thorndyke P.W. and Stasz C. (1985), ‘Individual Differences in Procedures for Knowledge Acquisition from Maps’, in Cognitive Psychology 12, pp. 137–175.

    Google Scholar 

  • Turkle Sh. (1984), The Second Shelf: Computers and the Human Spirit, New York, Simon and Schuster.

    Google Scholar 

  • Van de Riet R. (1987), Problems with Expert Systems, in Future Generations Computer Systems, Vol. 3, pp. 11–16.

    Google Scholar 

  • Varela F.J., Thompson E. and Rosch E. (1991), The Embodied Mind: Cognitive Science and Human Experience. MIT Press, Cambridge, MA.

    Google Scholar 

  • Watzlawick P. (ed.) (1984), The Invented Reality, Norton, New York.

    Google Scholar 

  • Weitzel J.R. and Kerschberg L. (1989), ‘Developing Knowledge-Based Systems: Reorganizing the System Development Life Cycle’, in Communications of the ACM, Vol. 32,(4), pp. 482–488.

    Google Scholar 

  • Whitaker R. and Östberg O. (1988), ‘Channeling Knowledge: Expert Systems as Communication Media’, in AI & Society, Vol. 2,(3), pp. 197–208.

    Google Scholar 

  • Winograd T. and Flores F. (1986), Understanding Computers and Cognition, A New Foundation for Design, Ablex, Norwood.

    Google Scholar 

  • Winograd T. (1995), From Programming Environments to Environments for Designing, in Communications of the ACM, Vol. 38,(6), pp. 65–74.

    Google Scholar 

  • Wood S. (1986), New Technologies, Organization of Work, and Qualifications: The British-Labour-Process Debate (in German), in Prokla 2, Rotbuch, Berlin.

    Google Scholar 

  • Young R.M., Green T.R.G. and Simon T. (1989), ‘Programmable User Models for Predictive Evaluation of Interface Designs’, in Proceedings CHI'89, ACM, p. 1.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Peschl, M.F., Stary, C. The Role of Cognitive Modeling for User Interface Design Representations: An Epistemological Analysis of Knowledge Engineering in the Context of Human-Computer Interaction. Minds and Machines 8, 203–236 (1998). https://doi.org/10.1023/A:1008223113903

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008223113903

Navigation