Practicing Theory Building in a Many Modelers Hackathon

Scientific theories reflect some of humanity's greatest epistemic achievements. The best theories motivate us to search for discoveries, guide us towards successful interventions, and help us to explain and organize knowledge. Such theories require a high degree of specificity, which in turn requires formal modeling. Yet, in psychological science, many theories are not precise and psychological scientists often lack the technical skills to formally specify existing theories. This problem raises the question: How can we promote formal theory development in psychology, where there are many content experts but few modelers? In this paper, we discuss one strategy for addressing this issue: a Many Modelers approach. Many Modelers consists of mixed teams of modelers and non-modelers that collaborate to create a formal theory of a phenomenon. Here, we report a proof of concept of this approach, which we piloted as a three-hour hackathon at the Society for the Improvement of Psychological Science conference in 2021. After surveying the participants, results suggest that (a) psychologists who have never developed a formal model can become (more) excited about formal modeling + and theorizing; (b) a division of labor in formal theorizing is possible where only one or a few team members possess the prerequisite modeling expertise; and (c) first working prototypes of a theoretical model can be created in a short period of time. These results show some promise for the many modelers approach as a team science tool for theory development.

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Publication Details

Journal
Meta-Psychology
Published
2025-02-07
DOI
https://doi.org/10.15626/mp.2023.3688
Primary Topic
Biomedical and Engineering Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Practicing Theory Building in a Many Modelers Hackathon

Leonid Tiokhin, Jens Fuenderich, Marlene Werner, Li-Ching Chuang et al.
Meta-Psychology
Biomedical and Engineering Education
article

Practicing Theory Building in a Many Modelers Hackathon

Leonid Tiokhin, Jens Fuenderich, Marlene Werner, Li-Ching Chuang, Anton Kunnari, Elena C. Altmann, Sandra J. Geiger, Jill de Ron, Johannes Algermissen, Anna Szabelska, Aidai Golan, Felix D. Schönbrodt, Julia M. Rohrer, Denny Borsboom, Andrei Dumbravă, Hannah Katharina Peetz, Štěpán Bahník, Shirley Wang, Judith Herbers, Adrian Rothers, Marc Jekel, Yih-Shiuan Lin, Noah van Dongen, Yvonne Oberholzer, David Moreau, Natasha Tonge, Nicole Walasek, Adam Finnemann, Daria Gerasimova, Yashvin Seetahul
article en

Abstract

Scientific theories reflect some of humanity's greatest epistemic achievements. The best theories motivate us to search for discoveries, guide us towards successful interventions, and help us to explain and organize knowledge. Such theories require a high degree of specificity, which in turn requires formal modeling. Yet, in psychological science, many theories are not precise and psychological scientists often lack the technical skills to formally specify existing theories. This problem raises the question: How can we promote formal theory development in psychology, where there are many content experts but few modelers? In this paper, we discuss one strategy for addressing this issue: a Many Modelers approach. Many Modelers consists of mixed teams of modelers and non-modelers that collaborate to create a formal theory of a phenomenon. Here, we report a proof of concept of this approach, which we piloted as a three-hour hackathon at the Society for the Improvement of Psychological Science conference in 2021. After surveying the participants, results suggest that (a) psychologists who have never developed a formal model can become (more) excited about formal modeling + and theorizing; (b) a division of labor in formal theorizing is possible where only one or a few team members possess the prerequisite modeling expertise; and (c) first working prototypes of a theoretical model can be created in a short period of time. These results show some promise for the many modelers approach as a team science tool for theory development.

Meta-PsychologyVol. 9
Karlsruhe Institute of Technology (DE), Queen's University Belfast (GB), University of Vienna (AT), University of Helsinki (FI), Harvard University (US), Radboud University Nijmegen (NL), University of Auckland (NZ), Notre Dame of Maryland University (US), Philipps University of Marburg (DE), Tel Aviv University (IL), University of Cologne (DE), Universität Innsbruck (AT), University of Erfurt (DE), Harvard University Press (US), Association of University Centers on Disabilities (US), University Medical Center (US), University of Economics and Management (CZ), Institute of Psychology, Chinese Academy of Sciences (CN), George Enescu University of Arts of Iași (RO), University of Regensburg (DE), Lancaster University (GB), Technische Universität Dresden (DE), Ludwig-Maximilians-Universität München (DE), Eindhoven University of Technology (NL), University of Amsterdam (NL), Leipzig University (DE)
Openalex Percentile: Top 96%
Biomedical and Engineering Education
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