Date: Jan 27, 2021 @ 3:00pm-04:30pm
Title: How computational modeling can force theory building in psychological science
Location: Online
Speaker: Olivia Guest
Abstract:
Psychology endeavors to develop theories of human capacities and behaviors based on a variety of methodologies and dependent measures. We argue that one of the most divisive factors in our field is whether researchers choose to employ computational modeling of theories (over and above data) during the scientific inference process. Modeling is undervalued, yet holds promise for advancing psychological science.
The inherent demands of computational modeling guide us towards better science by forcing us to conceptually analyze, specify, and formalise intuitions which otherwise remain unexamined — what we dub “open theory”. Constraining our inference process through modeling enables us to build explanatory and predictive theories. Herein, we present scientific inference in psychology as a path function, where each step shapes the next. Computational modeling can constrain these steps, thus advancing scientific inference over and above stewardship of experimental practice (e.g., preregistration).
If psychology continues to eschew computational modeling, we predict more replicability “crises” and persistent failure at coherent theory-building. This is because without formal modelling we lack open and transparent theorising. We also explain how to formalise, specify, and implement a computational model, emphasizing that the advantages of modeling can be achieved by anyone with benefit to all.
Bio:
I am a postdoctoral researcher in Andrea E. Martin’s lab at the Donders Centre for Cognitive Neuroimaging at Radboud University, Netherlands. I am a computational cognitive modeller — I develop and test psychological and neuroscientific theories using formal modelling techniques. My main interests are: a) creating and evaluating models for conceptual organisation, semantic memory, and categorisation; b) metascience; and c) data science more broadly. Additionally, I am an editor-in-chief at ReScience C and a topic editor at Journal of Open Source Software.
My undergraduate degree was in Computer Science. After that, I moved on to an MSc in Cognitive and Decision Sciences. I then undertook a PhD in Psychology on computational models for semantic memory.
I am committed to equity, diversity, and inclusion in (open) science, e.g., promoting access to technical skills training — including the broader decolonisation of computational sciences. Relatedly, Christina Bergmann and I maintain a list of underrepresented cognitive computational scientists.