| Autor: |
Noah N'Djaye Nikolai van Dongen, Adam Finnemann, Jill de Ron, Leonid Tiokhin, Shirley B Wang, Johannes Algermissen, Elena C. Altmann, Li-Ching Chuang, Andrei Dumbravă, Štěpán Bahník, Jens Fuenderich, Sandra Jeanette Geiger, Daria Gerasimova, Aidai Golan, Judith Herbers, Marc Jekel, Yih-Shiuan Lin, David Moreau, Yvonne Oberholzer, Hannah Katharina Peetz, Julia M. Rohrer, Adrian Rothers, Felix D. Schönbrodt, Yashvin Seetahul, Anna Szabelska, Natasha April Tonge, Nicole Walasek, Marlene Werner, Denny Borsboom |
| Rok vydání: |
2022 |
| DOI: |
10.31234/osf.io/r5yfz |
| Popis: |
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, and specifying them requires modeling skills. Unfortunately, in psychological science, theories are often 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 consist of mixed teams of modelers and non-modelers that collaborate to create a formal theory of a phenomenon. We report a proof of concept of this approach, which we piloted as a three-hour hackathon at the SIPS 2021 conference. We find that (a) psychologists who have never developed a formal model can become excited about formal modeling and theorizing; (b) a division of labor in formal theorizing could be 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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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