The growth of cognitive modeling in human-computer interaction since GOMS

The purpose of this article is to review where we stand with regard to modeling the kind of cognition involved in human-computer interaction. Card, Moran, and Newell's pioneering work on cognitive engineering models and explicit analyses of the knowledge people need to perform a procedure was a significant advance from the kind of modeling cognitive psychology offered at the time. Since then, coordinated bodies of research have both confirmed the basic set of parameters and advanced the number of parameters that account for the time of certain component activities. Formal modeling in grammars and production systems has provided an account for error production in some cases, as well as a basis for calculating how long a system will take to learn and how much savings there is from previous learning. Recently, we were given a new tool for modeling nonsequential component processes, adapting the "critical path analysis" from engineering to the specification of interacting processes and their consequent durations. Though these advances have helped, there are still significant gaps in our understanding of the whole process of interacting with computers. The cumulative nature of this empirical body and its associated modeling framework has further highlighted important issues central to research in cognitive psychology: how people move smoothly between skilled performance and problem solving, how people learn, how to design for consistent user interfaces, how people produce and manage errors, how we interpret visual displays for meaning, and what processes run concurrently and which depend on the completion of prior processes. In the bigger picture, cognitive modeling is a method that is useful in both initial design (it can narrow the design space and provide early analyses of design alternatives), evaluation, and training. But it does not extend to broader aspects of the context in which people use computers, partly because there are significant gaps in contemporary cognitive theory to inform the modeling and partly because it is the wrong form of model for certain kinds of more global questions in human-computer interaction. Notably, it fails to capture the user's fatigue, individual differences, or mental workload. And it is not the type of model that will aid the designer in designating the set of functions the software ought to contain, to assess the user's judgment of the acceptability of the software, or the change that could be expected in work life and the organization in which this work and person fits. Clearly, these kinds of considerations require modeling and tools of a different granularity and form.

[1]  John M. Carroll,et al.  Softening Up Hard Science: Reply to Newell and Card , 1986, Hum. Comput. Interact..

[2]  Allen Newell,et al.  The Prospects for Psychological Science in Human-Computer Interaction , 1985, Hum. Comput. Interact..

[3]  W. E. Hick Quarterly Journal of Experimental Psychology , 1948, Nature.

[4]  David E. Kieras,et al.  The Acquisition of Procedures from Text: A Production-System Analysis of Transfer of Training. Technical Report No. 16. , 1985 .

[5]  Keith Duncan,et al.  Cognitive Engineering , 2017, Encyclopedia of GIS.

[6]  Jock D. Mackinlay Automatic design of graphical presentations , 1987 .

[7]  Allen Newell,et al.  Predicting the time to recall computer command abbreviations , 1986, CHI '87.

[8]  M. Markus Systems in Organizations: Bugs and Features , 1984 .

[9]  Phyllis Reisner,et al.  Formal Grammar and Human Factors Design of an Interactive Graphics System , 1981, IEEE Transactions on Software Engineering.

[10]  Peter G. Polson,et al.  A quantitative theory of human-computer interaction , 1987 .

[11]  Bonnie Elizabeth John Contributions to engineering models of human-computer interaction. (volumes i and ii) , 1988 .

[12]  Marilyn Tremaine,et al.  Skilled financial planning: the cost of translating ideas into action , 1989, CHI '89.

[13]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[14]  R Schweickert,et al.  Critical-path scheduling of mental processes in a dual task. , 1980, Science.

[15]  Richard Schweickert,et al.  A critical path generalization of the additive factor method: Analysis of a stroop task , 1978 .

[16]  John R. Anderson,et al.  A Keystroke Analysis of Learning and Transfer in Text Editing , 1987, Hum. Comput. Interact..

[17]  Lucy A. Suchman,et al.  Plans and Situated Actions: The Problem of Human-Machine Communication (Learning in Doing: Social, , 1987 .

[18]  Bonnie E. John,et al.  Toward an Engineering Model of Stimulus-Response Compatibility , 1990 .

[19]  P. Fitts,et al.  INFORMATION CAPACITY OF DISCRETE MOTOR RESPONSES. , 1964, Journal of experimental psychology.

[20]  John Karat,et al.  Software Evaluation Methodologies , 1988 .

[21]  Allen Newell,et al.  Cumulating the science of HCI: from s-R compatibility to transcription typing , 1989, CHI '89.

[22]  Lucy Suchman Plans and situated actions: the problem of human-machine communication , 1987 .

[23]  Thomas R. G. Green,et al.  The Structure of Command Languages: An Experiment on Task-Action Grammar , 1989, Int. J. Man Mach. Stud..

[24]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[25]  T S Tullis,et al.  The Formatting of Alphanumeric Displays: A Review and Analysis , 1983, Human factors.

[26]  David E. Kieras,et al.  The Acquisition and Performance of Text-Editing Skill: A Cognitive Complexity Analysis , 1990, Hum. Comput. Interact..

[27]  Clayton Lewis,et al.  Theory-based design for easily learned interfaces , 1990 .

[28]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[29]  David E. Kieras,et al.  A quantitative model of the learning and performance of text editing knowledge , 1985, CHI '85.

[30]  David E. Kieras,et al.  Towards a Practical GOMS Model Methodology for User Interface Design , 1988 .

[31]  Allen Newell,et al.  Straightening Out Softening Up: Response to Carroll and Campbell , 1987, SGCH.

[32]  R. M. Young,et al.  Choosing between methods: analysing the user's decision space in terms of schemas and linear models , 1988, CHI '88.

[33]  Stephen J. Payne,et al.  Task-Action Grammars: A Model of the Mental Representation of Task Languages , 1986, Hum. Comput. Interact..

[34]  Marilyn M. Mantei,et al.  Computerized financial planning: discovering cognitive difficulties in model building , 1988 .

[35]  Louis M. Gomez,et al.  Learning to Use a Text Editor: Some Learner Characteristics that Predict Success , 1987, SGCH.

[36]  J. B. Smelcer Understanding user errors in database query , 1990 .

[37]  Allen Newell,et al.  Computer text-editing: An information-processing analysis of a routine cognitive skill , 1980, Cognitive Psychology.

[38]  G. Engelbeck,et al.  A test of a common elements theory of transfer , 1986, CHI '86.

[39]  Allen Newell,et al.  A theory of stimulus-response compatibility applied to human-computer interaction , 1985, CHI '85.

[40]  Thomas B. Sheridan Task Allocation and Supervisory Control , 1988 .

[41]  William C. Sasso,et al.  The Practice of Office Analysis: Objectives, Obstacles, and Opportunities , 1986 .

[42]  Dennis E. Egan,et al.  Individual Differences In Human-Computer Interaction , 1988 .

[43]  Louis M. Gomez,et al.  How interface design determines Who has difficulty learning to use a text editor , 1983, CHI '83.

[44]  Allen Newell,et al.  The keystroke-level model for user performance time with interactive systems , 1980, CACM.