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16th International Conference on cognitive modeling, ICCM 2018

作者： Russwinkel, Nele Prezenski, Sabine Dörr, Lisa Tamborello, Frank Department of Cognitive Modeling in Dynamic Human-Machine Systems TU Berlin Marchstr. 23 Berlin10587 Germany Cogscent LLC HoustonTX United States

ISBN: (纸本)9780998508221

This paper presents a tool (ACT-Droid) that integrates user models with mobile devices and enables modelling time-sensitive touch interactions via ACT-Touch. It demonstrates that using ACT-Droid in combination with ACT-Touch is a step towards model-based user studies of real smartphone apps. Aspecial focus is set on modeling swipe interactions. Hereby, different interaction strategies depending on preknowledge of the interface type (e.g. sorted or unsorted lists) are modeled. Results of an empirical study conducted with a real smartphone app indicate that searching through lists results in different kinds of swipe behavior for sorted vs. unsorted lists. Sorted list interfaces elicited fewer and quicker swipes than unsorted lists. This paper introduces ACT-R model approaches capable of capturing such behavior. Finally, the importance of understanding top-down strategies involved in such regular tasks is discussed. © 2020 The Authors. Published by Elsevier Ltd.

关键词： Smartphones

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modeling Individual Strategies in dynamic Decision-making with ACT-R: A Task Toward Decision-making Assistance in HCI

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Procedia Computer Science 2018年 145卷 668-674页

作者： Ziying Zhang Nele Russwinkel Sabine Prezenski Cognitive Modeling in Dynamic Human-Machine Systems Department of Psychology and Ergonomics Technische Universität Berlin 10587 Berlin Germany

New findings from cognitive science, computer science, and psychology should be used to develop better artificial intelligence (AI). One of the important goals in AI development is the accurate understanding and prediction of the behaviors and decision-making processes of humans. It is especially demanding to achieve this for real dynamic settings, characterized by constant changes. Individual differences in decision-making and behavior make this even more challenging. The area of human-computer interaction looks at a series of decisions and multifactor situations which are influenced by corresponding feedback. cognitive modeling provides us with a method to understand and explain how such dynamic decisions are made. This work is a demonstration of how cognitive modeling allows to flexible simulate decision-making in dynamic environments for different individual strategies. In this work an empirical study of an improved complex category learning task is presented, the study is based on previous work [8]. The task requires participants to categorize tones (consisting of different features) by applying acoustic strategies to define a target category and adapt to a reversal of feedback. Thus, a model based on the cognitive architecture ACT-R is developed. This model firstly tries out one-feature strategies (e.g. frequency) and then switches to two-feature strategies (e.g. frequency + volume) as a result of negative feedback. However, after comparing the model fit data and analyzing each individual’s data and answers, there is a great variance among some individuals and the first model which only considers acoustic feature strategies and cannot predict individuals who consider the uncertain correct button representing target tones. The upgraded second model contains two independent threshold count mechanisms for these two factors’ learning process. The result of the second model provides a better approximation of the values with the empirical data of those subjects who

关键词： dynamic decision making Category learning ACT-R cognitive modeling Auditory cognition Artificial intelligence

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Implementing mental model updating in ACT-R 15

Implementing mental model updating in ACT-R

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15th International Conference on cognitive modeling, ICCM 2017

作者： Prezenski, Sabine Cognitive Modeling in Dynamic Human-Machine Systems Department of Psychology and Ergonomics Technical University Berlin Berlin Germany

This paper demonstrates how mental models and updates of mental models due to system changes can be modeled with the cognitive architecture ACT-R using explicit mechanisms. The mental model building and updating is modeled with a representation chunk and a control chunk. The representation chunk holds the strategy, the expected outcome and an evaluation mechanism of the strategy. The control chunk holds information over environmental conditions and the learning history. This modeling approach was developed and tested for smartphone application tasks and then implemented in a dynamic decision-making task investigating strategy development with complex stimuli. The later task used different multi-feature auditory stimuli material. The modeling approach explained data of participants in the smartphone studies very well and met the trends found in the dynamic decision-making task. © Copyright 2017 retained by the authors.

关键词： Smartphones

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modeling of visual search and influence of item similarity 15

Modeling of visual search and influence of item similarity

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15th International Conference on cognitive modeling, ICCM 2017

作者： Lindner, Stefan Russwinkel, Nele Arlt, Lennart Neufeld, Max Schattenhofer, Lukas Department of Cognitive Modeling in Dynamic Human-Machine Systems TU Berlin Marchstr. 23 Berlin10587 Germany

A modeling approach addressing visual search in an array of items of differing similarity is introduced. The model is able to capture the effects found in a study that varies target-distractor similarity (low vs. high), distractor-distractor similarity (low vs. high) of icons, target presence (present vs. absent) and the set size (8, 16 or 24 icons). To be able to simulate human visual search in such a task with original ACT-R mechanisms we implemented a hybrid search strategy that combines parallel and serial search. The presented model can provide useful insight for researchers interested in modeling tasks containing visual icon search. © Copyright 2017 retained by the authors.

关键词： ACT-R cognitive modeling Similarity Visual search

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Causes of psychological reactance in human-computer interaction: A literature review and survey 17

Causes of psychological reactance in human-computer interact...

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35th Annual Conference of the European Association of cognitive Ergonomics, ECCE 2017

作者： Ehrenbrink, Patrick Prezenski, Sabine Institute of Software Engineering and Theoretical Computer Science Quality and Usability Lab Technische Universitt Berlin Ernst-Reuter-Platz 7 Berlin10587 Germany Mechanical Engineering and Transport Systems Cognitive Modeling in Dynamic Human-Machine Systems Technische Universitt Berlin Marchstr. 23 Berlin10587 Germany

ISBN: (纸本)9781450352567

Psychological reactance is a psychological effect that can reduce the acceptance of devices and services. So far, there has not been a collection of potential causes for reactance in the context of human-computer interaction in literature. A literature review and a qualitative study to compile a list of possible causes of reactance in human-computer interaction were conducted. The final list includes twelve causes of reactance that have been shown to appear in the field of human-computer interaction. The individual causes are discussed and examples provided. Finally, strategies for avoiding reactance in human-computer interaction are proposed and possible future directions for reactance research in this field are recommended.

关键词： human computer interaction

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modeling of proximity-Based expectatons 14

Modeling of proximity-Based expectatons

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14th International Conference on cognitive modeling, ICCM 2016

作者： Lindner, Stefan Russwinkel, Nele Department of Cognitive Modeling in Dynamic Human-Machine Systems TU Berlin Berlin Germany

ISBN: (纸本)9780998508207

Expectations play a crucial role in many domains, including HMI. In this paper we examine a specific type of expectations resulting from the proximity of interface control elements. We briefly present the results of an experimental smart phone task that manipulated the relationship between control element proximity and the closeness of the corresponding goals. We present a modeling approach for proximity-based expectations and compare model predictions from an ACT-R model and experimental results. Copyright © TRECVID *** rights reserved.

关键词： Smartphones

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Act-droid: ACT-R interacting with android applications 14

Act-droid: ACT-R interacting with android applications

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14th International Conference on cognitive modeling, ICCM 2016

作者： Dörr, Lisa-Madeleine Russwinkel, Nele Prezenski, Sabine Department of Cognitive Modeling in Dynamic Human-Machine Systems Technische Universität Berlin Germany

ISBN: (纸本)9780998508207

A tool for directly connecting ACT-R with Android applications on smartphones or tablets is introduced. The advantage of this tool is that no prototyping of the application is needed. This tool is especially useful to evaluate applications according to usability by using general modeling approaches. Copyright © TRECVID *** rights reserved.

关键词： Android (operating system)

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A proposed method of matching ACT-R and EEG-data 14

A proposed method of matching ACT-R and EEG-data

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14th International Conference on cognitive modeling, ICCM 2016

作者： Prezenski, Sabine Russwinkel, Nele Department of Cognitive Modeling in Dynamic Human-Machine Systems Technische Universität Berlin Berlin10587 Germany

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Towards a general model of repeated app usage 14

Towards a general model of repeated app usage

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14th International Conference on cognitive modeling, ICCM 2016

作者： Prezenski, Sabine Russwinkel, Nele Department of Cognitive Modeling in Dynamic Human-Machine Systems Technische Universität Berlin Berlin10587 Germany

ISBN: (纸本)9780998508207

The main challenge of implementing cognitive models for usability testing lies in reducing the modeling effort, while including all relevant cognitive mechanisms, such as learning and relearning, in the model. In this paper we introduce a general cognitive modeling approach with ACT-R for hierarchical, list-based smartphone apps. These apps support the task of selecting a target, via navigating through subtargets positioned on different layers. Mean target selection time for repeated app interaction, learning and relearning behavior was collected in four studies conducted with either a shopping app or a real-estate app. The predictions of the general modeling approach match the empirical data very well, both in terms of trends and absolute values. We also explain how such a general modeling approach can be followed. The presented general model approach requires little modeling effort to be used for predicting overall efficiency of other apps. It supports more complex interface, as well. Copyright © TRECVID *** rights reserved.

关键词： Learning systems

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The sum of two models: How a composite model explains unexpected user behavior in a dual-task scenario 14

The sum of two models: How a composite model explains unexpe...

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14th International Conference on cognitive modeling, ICCM 2016

作者： Halbrügge, Marc Russwinkel, Nele Quality and Usability Lab Telekom Innovation Laboratories Technische Universität Berlin Ernst-Reuter-Platz 7 Berlin10587 Germany Department of Cognitive Modeling in Dynamic Human-Machine Systems Technische Universität Berlin Marchstraße 23 Berlin10587 Germany

ISBN: (纸本)9780998508207

Maintaining cognitive control while pursuing several tasks at the same time is hard, especially when the current problem states of these tasks need to be represented in memory. We are investigating the mutual influence of a self-paced and a reactive task with regard to completion time and error rates. Against initial expectations, the interruptions from the reactive task did not lead to more errors in the self-paced task, but only prolonged the completion time. Our understanding of this result is guided by a combined version of two previously published cognitive models of the individual tasks. The combined model reproduces the empirical findings concerning error rates and task completion times, but not an unexpected change in the error pattern. These results feed back into our theoretical understanding of cognitive control during sequential action. Copyright © TRECVID *** rights reserved.

关键词： Errors

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