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Cognitive Ergonomics (CE)

What is AMME? In an overview Ivory and Hearst (2001) compared 132 usability evaluation and modeling methods worldwide; 19 different modeling methods are based on logfile analysis: “AMME is the only surveyed approach that constructs a WIMP simulation model (Petri net) directly from usage data” (Ivory and Hearst 2001, p. 499). Therefore they conclude, “AMME appears to be the most effective method, since it is based on actual usage” (2001, p. 502). Ivory and Hearst (2001): The State of the Art in Automating Usability Evaluation of User Interfaces. In ACM Computing Surveys, Vol. 33, No. 4, December 2001.

Tasks solving processes produced by computer users (observed process) contain much information about their mental models, individual problem solving strategy and underlying decision structure for a given task. Our tool AMME analyses observed processes and automatically extracts a Petri net description of the task dependent decision structure (logical structure). This net is extended by goal setting structures (modelling) and can be executed (simulated process). The aim is of simulation is functional equivalence between observed and simulated processes. Based on Activity Theory, three modelling strategies, event-driven, parallel goal setting, and regulation-driven goal setting are presented [1]. Based on all observed actions, the latter strategy leads to full functional equivalence [2]. To reduce the complexity of such models, it became necessary to find out which actions are more relevant for successful task solving.

Since the number of actions are high, automatic detection of strategies becomes of interest. Given that the number of users exceeds that of strategies, multiple users will have a strategy in common. Based on a state-transition representation [3], our aim is to find groups of users sharing the same strategy. Following each of three methods (correlation, intersection and exclusion) we define a comparative metric among task solving behaviour. For multiple users, we represent these measures by a matrix system, to find groups of users with common strategies. Multidimensional scaling (MDS) or analytic interpretation indicates distinct user groups [4].

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Selected CE publications

[1] M. Rauterberg, S. Schluep & M. Fjeld (1998): Modelling of cognitive complexity with Petri nets: an action theoretical approach. In R. Trappl (ed.) Cybernetics and Systems'98 (EMCSR'98), Vol. 2, pp. 842-847. Wien: Austrian Society for Cybernetic Studies. (order proceedings)

[2] M. Rauterberg, M. Fjeld & S. Schluep (1997): Parallel or event-driven goal setting mechanism in Petri net based models of expert decision behaviour. In S. Bagnara, E. Hollnagel, M. Mariani & L. Norros (eds.) Time and Space in Process Control (CSAPC'97) (Sixth European Conference on Cognitive Science Approaches to Process Control), pp. 98-102. Roma: CNR. (HTML online abstract / order proceedings)

[3] M. Fjeld, S. Schluep & M. Rauterberg (1999): Action-driven quantification of task-solving behaviour. In D. Harris (ed.) Engineering Psychology and Cognitive Ergonomics (EPCE), Vol. 4. Hampshire: Ashgate, pp. 253-261.

[4] M.  Fjeld, S. Schluep & M. Rauterberg (1998): Quantification of task related activity by statistical and analytical methods. In Proceedings 7th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design and Evaluation of Man-Machine Systems (IFAC-MMS98), pp.591-596. Oxford: Elsevier Science, Ltd.


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