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TU Berlin

Inhalt des Dokuments

Dr. rer. nat. Sabine Prezenski (Dipl.-Psych.)

Lupe [1]
© www.blende2komma2.de

Wissenschaftliche Mitarbeiterin

 

Marchstr. 23
10587 Berlin
Raum: MAR 3.070

 

sabine.prezenski(at)tu-berlin.de [2]

Tel: +49 30 314 29628

 

Projektleitung: AVALANCHE [3]

 

Forschungsinteressen

  • Kognitive Systeme
  • Dynamisches Entscheiden in Risikobereichen
  • Companion Systeme
  • Kognitive Modellierung (ACT-R)
  • Usability (Mobile Interaktion)
  • Aufbau und anpassen von mentalen Modell von Nutzern in dynamischen Situationen
  • Neuropsychologische Methoden (EEG)

 

Curriculum Vitae

Abschluss

  • Dissertation: "Interactive Learning of Dynamic Systems: [4]A Cognitive Modeling Approach to Mental Model Building and Updating. [5]" (Tag der Wissenschaftliche Aussprache: 29. November 2018). Video der Verteidigung [6]
  • Psychologie (Diplom), FU Berlin  Diplomarbeit: “Continuous exclusion during a game of Cyberball- A single trial study”

Berufserfahrung

  • 04/2013 – aktuell Kognitive Modellierung in dynamischen Mensch-Maschine Systemen, Nele Rußwinkel, Technische Universität Berlin, Wissenschaftliche Mitarbeiterin (10 Monate Elternzeit 10/2014- 08/2015)
  • 10/2017 – 03/2018 Center for Persuasive Technology and Society, Khin Tan Win, University of Wollongong Australien, Gastwissenschaftlerin
  • 02/2009-09/2011 Experimentelle Psychologie und Neuropsychologie, Michael Niedeggen, Freie Universität Berlin, Studentische Hilfskraft und Tutorin
  • 02/2009-04/2009 Research & Advanced Engineering, Michael Schrauff, Daimler AG Sindelfingen, Praktikantin
  • 04/2007-08/2008 Babylabor, Franziska Kopp, Max-Planck-Institut für Bildungsforschung Berlin, Studentische Hilfskraft

 

Lehrveranstaltungen

Master

  • Kognitive Systeme (Seminar, 2 ECTS, TU Berlin, 2019)
  • Decision Making in Real-Word Settings (Seminar, 2 ECTS), TU Berlin, 2017
  • Introduction to Cognitive Modeling (Vorlesung und Übung, 6 ECTS), TU Berlin, 2013, 2014, 2016, 2017, 2018

Bachelor

  • Human Factors Engineering E-Learning (Online Kurs, 6 ECTS), TU Berlin, 2017/2018; 2018/19
  • Human Factors Engineering (Vorlesung und Übung, 6 ECTS), TU Berlin, 2013/14, 2015/16, 2016/17
  • Tutorium Biopsychologie (Tutorium, 2 ECTS), FU Berlin, 2011.

 

Auszeichnungen und Wettbewerbe

  • Gewinn des Ideenwettbewerbs „Research to Market Challenge“ der Gründungsförderung der Berliner Universtäten (PROFUND 2018). Erster Platz in der Kategorie „Digital“ mit der Idee „Navalanche“. (06/2018)
  • Best-Paper Award im Rahmen der Konferenz: “Sixth International Conference on Advanced Cognitive Technologies and Applications” für “ACT-R Meets Usability” (04/2014)

 

Vorträge

  • ISSW 2018, Innsbruck, Austria "Designing a wearable persuasive avalanche warning system"(10/2018)
  • DGPS 2018, Frankfurt, Germany- Symposium zu Ehren von Dietriech Dörner: “To what extent can ACT-R models address Complex Problem Solving?” (09/2018)
  • HLAI/BICA 2018, Prag, Czech Republic: “Modeling Individual Strategies in Dynamic Decision-making with ACT-R: A Task Toward Decision-making Assistance in HCI” (08/2018). Video of presentation [7]
  • Second Workshop on Persuasive Technology and Society, Wollongong, Australia:“Developing a Personalized Persuasive Avalanche Warning System” (11/2017)
  • ICCM 2017, London, UK: “Implementing Mental Model Updating in ACT-R“ (07/2017)
  • VISIGRAPP/HUCAPP 2017, Porto, Portugal: "Predictive Cognitive Modelling of Applications" (02/2017)
  • KOGWIS 2016, Bremen, Germany: “ACT-R Workshop” (10/2016)
  • KOGWIS 2014, Tübingen, Germany: “Introduction to Cognitive Modelling with ACT-R” (10/2014)
  • COGNITIVE 2014, Venice, Italy: “Combining Formalized Cognitive Theory (ACT-R) And EEG-Data Is A
    Milestone Towards A Comprehensive Understanding of Human Information Processing.” (05/2014)
  • COGNITIVE 2014, Venice, Italy: “ACT-R Meets Usability” (05/2014)

 

Modelle und Tools

1. kognitive Modelle

Usability Prediction (Users Mental Model) [8]

      assozierte Publikationen

  • Implementing Mental Model Updating in ACT-R [9]
  • Towards a general model of repeated app usage [10]
  • Combining cognitive ACT-R models with usability testing reveals users mental model while shopping with a smartphone application [11]
  • Interactive Learning of Dynamic Systems: [12]A Cognitive Modeling Approach to Mental Model Building and Updating [Dissertation] [13]

Dynamic Decision Making in Category Learning (Mental Model Building and Updating) [14]

      assoziierte Publikationen

  • A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making [15]
  • Implementing Mental Model Updating in ACT-R [16]
  • Modeling Individual Strategies in Dynamic Decision-making with ACT-R: A Task Toward Decision-making Assistance in HCI [17]
  • Interactive Learning of Dynamic Systems: [18]A Cognitive Modeling Approach to Mental Model Building and Updating [Dissertation] [19]

2. Tools

Automated Usability Predictition:

  • ACT-Droid:

    • erste Version :Lisa Doerr, Nele Rußwinkel & Sabine Prezenski (2016). Siehe Paper: ACT-Droid: ACT-R interacting with Android applications [20]

    • zweite Version: Lisa Doerr, Nele Rußwinkel, Sabine Prezenski & Frank Tamborello (2018). Siehe Paper: ACT-Droid meets ACT-Touch: Modelling differences in swiping behavior with real Apps [21]

  • Cawler (2017) [22]:

    • Dominik Brüchner & Sabine Prezenski (2017).

 

 

Publikationen

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Lommerzheim, M., Prezenski, S., Russwinkel, N. and Brechmann, A. (2020). Category Learning as a Use Case for Anticipating Individual Human Decision Making by Intelligent Systems [25]. In Ahram, T. and Karwowski, W. and Vergnano, A. and Leali, F. and Taiar, R. (Eds.), Proceedings of the Intelligent Human Systems Integration 2020. Advances in Intelligent Systems and Computing, p. 159-164. Link zur Publikation [26] Link zur Originalpublikation [27]

Prezenski, S. (2019). Interactive Learning of Dynamic Systems: A Cognitive Modeling Approach to Mental Model Building and Updating (Dissertation) [28]. doi: http://dx.doi.org/10.14279/depositonce-7951.

Link zur Publikation [29] Link zur Originalpublikation [30]

Prezenski, S., Brechmann, A., Wolff, S. and Russwinkel, N. (2018). To what extent can ACT-R models address complex problem solving? [31]. In 51. Kongress der Deutschen Gesellschaft für Psychologie Supplement to Psychological Test and Assessment Modeling, p. 276. Link zur Originalpublikation

Prezenski, S., Russwinkel, N. and Win, K. (2018). Designing a wearable persuasive avalanche warning system [32]. In Proceedings of the International Snow Science Workshop, p. 835-836. Link zur Originalpublikation [33]

Russwinkel, N., Prezenski, S., Doerr, L. and Tamborello, F. (2018). ACT-Droid meets ACT-Touch: Modelling differences in swiping behavior with real Apps [34]. In I. Juvins and C. Myers (Eds.), Proceedings of the 16th International Conference on Cognitive Modeling (ICCM 2018), p. 121-125. Link zur Publikation [35] Link zur Originalpublikation

Zhang, Z., Russwinkel, N. and Prezenski, S. (2018). Deciphering Dynamic Decision Making Using Cognitive Modeling Including Subjective Asessment [36]. In Rothkopf, C. et al. (Eds.), 14th Biannual Conference of the German Society for Cognitive Science, p. 79. Link zur Publikation [37] Link zur Originalpublikation

Zhang, Z., Russwinkel, N. and Prezenski, S. (2018). Modeling Individual Strategies in Dynamic Decision-making with ACT-R: A Task Toward Decision-making Assistance in HCI [38]. ScienceDirect:Procedia Computer Science, 145, p. 668-674. Link zur Publikation [39]

Prezenski, S., Brechmann, A., Wolff, S. and Russwinkel, N. (2017). A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making [40]. Front. Psychol., 8(1335), p. 1-18. doi: 10.3389/fpsyg.2017.01335 Link zur Originalpublikation [41]

Prezenski, S., Bruechner, D. and Russwinkel, N. (2017). Predictive Cognitive Modelling of Applications [42]. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics, p. 165-171. Link zur Publikation [43] Link zur Originalpublikation [44]

Ehrenbrink, P. and Prezenski, S. (2017). Causes of Psychological Reactance in Human-Computer Interaction - A Literature Review and Survey [45]. In Proceedings of the 35th European Conference on Cognitive Ergonomics (ECCE 2017). (electronic) Link zur Publikation [46]

Prezenski, S. (2017). Implementing Mental Model Updating in ACT-R [47]. In M. van Vugt, A. Banks & W. Kennedy (Eds.), Proceedings of the 15th International Conference on Cognitive Modeling, p. 121-127. Link zur Publikation [48] Link zur Originalpublikation [49]

Dörr, L.-M., Russwinkel, N. and Prezenski, S. (2016). ACT-Droid: ACT-R interacting with Android applications [50]. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling, p. 225-227. Link zur Publikation [51] Link zur Originalpublikation [52]

Prezenski, S. and Russwinkel, N. (2016). Towards a general model of repeated app usage [53]. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling, p. 201-207. Link zur Publikation [54] Link zur Originalpublikation [55]

Prezenski, S. and Russwinkel, N. (2016). A proposed method of matching ACT-R and EEG-Data [56]. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling, p. 249-251. Link zur Publikation [57] Link zur Originalpublikation [58]

Russwinkel, N., Prezenski, S., Halbrügge, M. and Lindner, S. (2016). Introduction to Cognitive Modelling with ACT-R [59]. In Proceedings of the 13th Biannual Conference of the German Cognitive Science Society (KogWis 2016). (Tutorial im Rahmen der KogWis 2016) Link zur Publikation [60]

Prezenski, S. and Russwinkel, N. (2014). Combining cognitive ACT-R models with usability testing reveals users mental model while shopping with a smartphone application [61]. International Journal On Advances in Intelligent Systems, 7(3-4), p. 700-715. Link zur Publikation [62] Link zur Originalpublikation [63]

Prezenski, S. and Russwinkel, N. (2014). Cognitive modeling offers explanations for effects found in usability studies [64]. Poster präsentiert auf der 32. European Conference on Cognitive Ergonomics ECCE 2014. Link zur Publikation [65]

Russwinkel, N. and Prezenski, S. (2014). ACT-R Meets Usability [66]. In Proceedings of the Sixth International Conference on Advanced Cognitive Technologies and Applications COGNITIVE, 2014. (Best Paper Award) Link zur Publikation [67] Link zur Originalpublikation [68]

Russwinkel, N., Prezenski, S., Joeres, F., Lindner, S. and Halbrügge, M. (2014). Introduction to cognitive modelling with ACT-R [69]. Cognitive Processing, 15(Suppl. 1), p. S25. (Tutorial im Rahmen der KogWis 2014) Link zur Publikation [70]

Russwinkel, N., Prezenski, S., Lindner, S., Halbrügge, M., Schulz, M. and Wirzberger, M. (2014). Modeling of cognitive aspects of mobile interaction [71]. Cognitive Processing, 15(Suppl. 1), p. S22-S24. doi: 10.1007/s10339-014-0632-2 (Symposium im Rahmen der KogWis 2014) Link zur Publikation [72]

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