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[1]- © www.blende2komma2.de
Researcher/ Lecturer
Marchstr. 23
10587 Berlin
Room: MAR 3.070
sabine.prezenski(at)tu-berlin.de [2]
Tel: +49 30 315 29628
Projectleader: AVALANCHE [3]
Research interests
- Decision-Making in
High-Risk Settings
- Cognitive Systems
- Companion
Systems
- Cognitive modeling (ACT-R)
- Usability
- Mobile
Interaction
- Neuropsychological methods
(EEG)
Curriculum Vitae
Degree
- Dissertation: "Interactive
Learning of Dynamic Systems:
"A Cognitive Modeling Approach to
Mental Model Building and Updating." Defence on 29th of November
2018. Video of Defence Talk [4]
- Psychology (Diploma), Free University
Berlin Thesis: "Continuous exclusion during a game of Cyberball-
A single trial study"
Working
experience
- Visiting Associate Fellow with the Faculty
of Engineering and Information Sciences at the University Wollongong
in Australien (WS 2017/18)
- Research assistant/
lecturer, Cognitive Modelling in Dynamic Human-Machine-Systems, Berlin
Institute of Technoloy (since 04/2013)
- Student
assistant, Experimental Psychology and Neuropsychology, Free
University Berlin (02/2009 - 09/2011)
- Intern at
Daimler AG, Research & Advanced Engineering/Mindlab (02/2009 -
04/2009)
- Student assistant at Max Planck Institute
for Human Development, Berlin (Babylab) (07/2007 -
07/2008)
Teaching Experience
- Human Factors
Engineering (E-Learning), TU Berlin (WS 2018/2019, WS
2017/2018)
- Human Factors Engineering, TU
Berlin (WS 2016/17, WS 2015/16, WS
2013/14)
- Decision-Making in Real-World
Settings, TU Berlin (SS 2017)
- Tutorial
biological psychology, FU Berlin (SS
2011)
- Introduction to cognitive modelling, TU
Berlin (SS 2019 SS 2018 SS 2017 SS 2016, SS 2014, SS
2013)
- Cognitive Systems, TU Berlin (SS
2019)
Talks
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
[5]
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)
Models and Tools
1. cognitive models
Usability Prediction (Users Mental
Model) [6]
related
publication
- Implementing
Mental Model Updating in ACT-R [7]
- Towards a general model of
repeated app usage [8]
- Combining cognitive ACT-R models with
usability testing reveals users mental model while shopping with a
smartphone application [9]
- Interactive Learning of
Dynamic Systems: [10]A Cognitive Modeling
Approach to Mental Model Building and Updating [Dissertation]
[11]
Dynamic Decision Making in Category Learning (Mental Model
Building and Updating) [12]
related publication
- A Cognitive Modeling Approach
to Strategy Formation in Dynamic Decision Making
[13]
- Implementing Mental Model Updating in ACT-R [14]
-
Modeling Individual Strategies in Dynamic Decision-making with ACT-R:
A Task Toward Decision-making Assistance in HCI
[15]
- Interactive Learning of Dynamic
Systems: [16]A Cognitive Modeling Approach
to Mental Model Building and Updating [Dissertation]
[17]
2. Tools
Automated Usability Predictition:
- ACT-Droid:
- first
version :Lisa Doerr, Nele Rußwinkel & Sabine
Prezenski (2016). See paper: ACT-Droid: ACT-R
interacting with Android applications [18]
- Cawler (2017)
[20]:
Publications
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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
[23]. 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 to publication [24] Link
to original publication [25]
Prezenski, S. (2019). Interactive Learning of
Dynamic Systems: A Cognitive Modeling Approach to Mental Model
Building and Updating (Dissertation) [26]. doi:
http://dx.doi.org/10.14279/depositonce-7951.
Link to publication [27] Link to
original publication [28]
Prezenski, S., Brechmann, A., Wolff, S. and
Russwinkel, N. (2018). To what extent can ACT-R models address
complex problem solving? [29]. In 51. Kongress der Deutschen
Gesellschaft für Psychologie Supplement to Psychological Test and
Assessment Modeling, p. 276. Link to original
publication
Prezenski, S., Russwinkel, N. and Win, K.
(2018). Designing a wearable persuasive avalanche warning system [30].
In Proceedings of the International Snow Science Workshop, p.
835-836. Link to original publication [31]
Russwinkel, N., Prezenski, S., Doerr, L. and
Tamborello, F. (2018). ACT-Droid meets ACT-Touch: Modelling
differences in swiping behavior with real Apps [32]. In I. Juvins and
C. Myers (Eds.), Proceedings of the 16th International Conference
on Cognitive Modeling (ICCM 2018), p. 121-125. Link to publication [33] Link to original
publication
Zhang, Z., Russwinkel, N. and Prezenski, S.
(2018). Deciphering Dynamic Decision Making Using Cognitive Modeling
Including Subjective Asessment [34]. In Rothkopf, C. et al. (Eds.),
14th Biannual Conference of the German Society for Cognitive
Science, p. 79. Link to publication
[35] Link to original publication
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 [36].
ScienceDirect:Procedia Computer Science, 145, p.
668-674. Link to publication [37]
Prezenski, S., Brechmann, A., Wolff, S. and
Russwinkel, N. (2017). A Cognitive Modeling Approach to Strategy
Formation in Dynamic Decision Making [38]. Front. Psychol.,
8(1335), p. 1-18. doi: 10.3389/fpsyg.2017.01335 Link to
original publication [39]
Prezenski, S., Bruechner, D. and Russwinkel,
N. (2017). Predictive Cognitive Modelling of Applications [40]. In
Proceedings of the 12th International Joint Conference on Computer
Vision, Imaging and Computer Graphics, p. 165-171. Link to publication [41] Link to original
publication [42]
Ehrenbrink, P. and Prezenski, S. (2017).
Causes of Psychological Reactance in Human-Computer Interaction - A
Literature Review and Survey [43]. In Proceedings of the 35th
European Conference on Cognitive Ergonomics (ECCE 2017).
(electronic) Link to publication
[44]
Prezenski, S. (2017). Implementing Mental
Model Updating in ACT-R [45]. In M. van Vugt, A. Banks & W.
Kennedy (Eds.), Proceedings of the 15th International Conference on
Cognitive Modeling, p. 121-127. Link
to publication [46] Link to original publication [47]
Dörr, L.-M., Russwinkel, N. and Prezenski,
S. (2016). ACT-Droid: ACT-R interacting with Android applications
[48]. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the
14th International Conference on Cognitive Modeling, p. 225-227.
Link to publication [49] Link to original
publication [50]
Prezenski, S. and Russwinkel, N. (2016).
Towards a general model of repeated app usage [51]. In D. Reitter
& F. E. Ritter (Eds.), Proceedings of the 14th International
Conference on Cognitive Modeling, p. 201-207. Link to publication [52] Link to original
publication [53]
Prezenski, S. and Russwinkel, N. (2016). A
proposed method of matching ACT-R and EEG-Data [54]. In D. Reitter
& F. E. Ritter (Eds.), Proceedings of the 14th International
Conference on Cognitive Modeling, p. 249-251. Link to publication [55] Link to original
publication [56]
Russwinkel, N., Prezenski, S., Halbrügge,
M. and Lindner, S. (2016). Introduction to Cognitive Modelling with
ACT-R [57]. In Proceedings of the 13th Biannual Conference of the
German Cognitive Science Society (KogWis 2016). (Tutorial im
Rahmen der KogWis 2016) Link to publication
[58]
Prezenski, S. and Russwinkel, N. (2014).
Combining cognitive ACT-R models with usability testing reveals users
mental model while shopping with a smartphone application [59].
International Journal On Advances in Intelligent Systems,
7(3-4), p. 700-715. Link to
publication [60] Link to original publication [61]
Prezenski, S. and Russwinkel, N. (2014).
Cognitive modeling offers explanations for effects found in usability
studies [62]. Poster präsentiert auf der 32. European Conference on
Cognitive Ergonomics ECCE 2014. Link to
publication [63]
Russwinkel, N. and Prezenski, S. (2014).
ACT-R Meets Usability [64]. In Proceedings of the Sixth
International Conference on Advanced Cognitive Technologies and
Applications COGNITIVE, 2014. (Best Paper Award) Link to publication [65] Link to original
publication [66]
Russwinkel, N., Prezenski, S., Joeres, F.,
Lindner, S. and Halbrügge, M. (2014). Introduction to cognitive
modelling with ACT-R [67]. Cognitive Processing,
15(Suppl. 1), p. S25. (Tutorial im Rahmen der KogWis 2014) Link to publication [68]
Russwinkel, N., Prezenski, S., Lindner, S.,
Halbrügge, M., Schulz, M. and Wirzberger, M. (2014). Modeling of
cognitive aspects of mobile interaction [69]. Cognitive
Processing, 15(Suppl. 1), p. S22-S24. doi:
10.1007/s10339-014-0632-2 (Symposium im Rahmen der KogWis 2014) Link to publication [70]
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[1]
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er/2012_09_21_Sabine-23.jpg
[2]
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parameter/en/font1/minhilfe/id/147148/?no_cache=1&a
sk_mail=YA1uZgALfF06qUiosmVVo4gqUN74c83kSy713XL1cJazLh9
AybzY2w%3D%3D&ask_name=SABINE%20PREZENSKI
[3]
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[4]
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[6]
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[9]
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