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Beyond playing 20 questions with nature: Integrative experiment design in the social and behavioral sciences

Published online by Cambridge University Press:  21 December 2022

Abdullah Almaatouq*
Affiliation:
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA amaatouq@mit.edu
Thomas L. Griffiths
Affiliation:
Departments of Psychology and Computer Science, Princeton University, Princeton, NJ, USA tomg@princeton.edu
Jordan W. Suchow
Affiliation:
School of Business, Stevens Institute of Technology, Hoboken, NJ, USA jws@stevens.edu
Mark E. Whiting
Affiliation:
School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA markew@seas.upenn.edu
James Evans
Affiliation:
Department of Sociology, University of Chicago, Chicago, IL, USA jevans@uchicago.edu Santa Fe Institute, Santa Fe, NM, USA
Duncan J. Watts
Affiliation:
Department of Computer and Information Science, Annenberg School of Communication, and Operations, Information, and Decisions Department, University of Pennsylvania, Philadelphia, PA, USA djwatts@seas.upenn.edu
*
Corresponding author: Abdullah Almaatouq; Email: amaatouq@mit.edu

Abstract

The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment's specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process of integration is at best inefficient, and at worst it does not, in fact, occur. We further show that the challenge of integration cannot be adequately addressed by recently proposed reforms that focus on the reliability and replicability of individual findings, nor simply by conducting more or larger experiments. Rather, the problem arises from the imprecise nature of social and behavioral theories and, consequently, a lack of commensurability across experiments conducted under different conditions. Therefore, researchers must fundamentally rethink how they design experiments and how the experiments relate to theory. We specifically describe an alternative framework, integrative experiment design, which intrinsically promotes commensurability and continuous integration of knowledge. In this paradigm, researchers explicitly map the design space of possible experiments associated with a given research question, embracing many potentially relevant theories rather than focusing on just one. Researchers then iteratively generate theories and test them with experiments explicitly sampled from the design space, allowing results to be integrated across experiments. Given recent methodological and technological developments, we conclude that this approach is feasible and would generate more-reliable, more-cumulative empirical and theoretical knowledge than the current paradigm – and with far greater efficiency.

Type
Target Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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