How to model behavioural and cognitive complexity in human-computer interaction with Petri nets

Rauterberg, Matthias; Schluep, S Samuel; Fjeld, Morten

doi:10.1109/roman.1997.647003

Cited by 12 publications

(17 citation statements)

References 9 publications

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“…In terms of cognition, complexity relates to how we differentiate and integrate perceptual input to enable us to build analogies so that we can deal with a persistently changing world [Rauterberg 1996]. The more complex our comprehension of the context, the more data we can parse at a time; this is also defined as chunking [Miller 1956].…”

Section: Player Interaction As An Information Systemmentioning

confidence: 99%

Toward an understanding of flow in video games

et al. 2008

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________________________________________________________________________In the domain of computer games, research into the interaction between player and game has centred on 'enjoyment', often drawing in particular on optimal experience research and Csikszentmihalyi's 'Flow theory'. Flow is a well-established construct for examining experience in any setting and its application to game-play is intuitive. Nevertheless, it's not immediately obvious how to translate between the flow construct and an operative description of game-play. Previous research has attempted this translation through analogy. In this article we propose a practical, integrated approach for analysis of the mechanics and aesthetics of game-play, which helps develop deeper insights into the capacity for flow within games.The relationship between player and game, characterized by learning and enjoyment, is central to our analysis. We begin by framing that relationship within Cowley's user-system-experience (USE) model, and expand this into an information systems framework, which enables a practical mapping of flow onto game-play. We believe this approach enhances our understanding of a player's interaction with a game and provides useful insights for games' researchers seeking to devise mechanisms to adapt game-play to individual players.

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Section: Player Interaction As An Information Systemmentioning

confidence: 99%

Toward an understanding of flow in video games

et al. 2008

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“…The following concept is based on psychological work on the issue of "cognitive complexity" [Rauterberg, 1992[Rauterberg, , 1995[Rauterberg, , 1996[Rauterberg, , 1997 which originally has been developed for the evaluation of interaction complexity of computer programs. It uses a complexity measure ftrst introduced by McCabe [1976] based on the states and transitions of a computer program.…”

Section: Methodsmentioning

confidence: 99%

Objective Evaluation of the Complexity of Usage for Car Infotainment Systems

Jung

Willumeit

2000

Advances in Networked Enterprises

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“…In the paper "How to measure cognitive complexity in HCI" Rauterberg (1996) transferred the broad definition of cognitive complexity into the context of HCI. Accordingly, "the complexity of the user's mental model of the dialog system is given by the number of known dialog contexts ("constructs") on one hand and by the number of known dialog operations ("relationships") on the other hand" [4].…”

Section: Related Workmentioning

confidence: 99%

“…Accordingly, "the complexity of the user's mental model of the dialog system is given by the number of known dialog contexts ("constructs") on one hand and by the number of known dialog operations ("relationships") on the other hand" [4]. A GUI with a defined level of complexity will be perceived differently by expert and novice users.…”

Section: Related Workmentioning

confidence: 99%

On Complexity Reduction of User Interfaces for Safety-Critical Systems

Holzinger

Popova

Peischl³

et al. 2012

Lecture Notes in Computer Science

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Abstract. Control and communication systems used at power plants or incineration facilities offer various graphical visualizations of the physical parts of the site; however, they rarely provide sufficient visualization of the signal data. There is the problem, that such facilities contain 10,000 or more data acquisition points; each of them continuously sending data updates to the control system (once in 20 ms or less). This huge load of data can be analyzed by a human expert only if appropriately visualized. Such a visualization tool is AutoDyn, developed by the company Technikgruppe, which allows processing and visualizing complex data and supports decision making. In order to configure this tool, a user interface is necessary, called TGtool. It was originally developed by following a system-centered approach, consequently it is difficult to use. Wrong configuration can lead to incorrect signal data visualization, which may lead to wrong decisions of the power plant personnel. An unintentional mistake could have dramatic consequences. The challenge was to re-design this tool, applying a user-centered approach. In this paper we describe the re-design of the configuration tool, following the hypothesis that a usercentered cognitive map structure helps to deal with the complexity without excessive training. The results of the evaluation support this hypothesis.

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How to model behavioural and cognitive complexity in human-computer interaction with Petri nets

Abstract: Abstract

Cited by 12 publications

References 9 publications

Toward an understanding of flow in video games

Toward an understanding of flow in video games

Objective Evaluation of the Complexity of Usage for Car Infotainment Systems

On Complexity Reduction of User Interfaces for Safety-Critical Systems

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