The Computational Reproducibility of Psychology Learning and Teaching Research

Background Research is computationally reproducible when independent analysts can use the underlying data to reproduce the original results. Some research in psychology is computationally reproducible, although much is not. Objective To assess the computational reproducibility of research published in Teaching of Psychology (ToP), Psychology Learning and Teaching (PLaT), and Scholarship of Teaching and Learning in Psychology (SoTL-P). Method We identified key claims in 60 papers published with open data in ToP, PLaT, and SoTL-P between 2017 and 2025. We then sought to reproduce 101 results supporting these claims. Results We exactly reproduced 73 of the 101 results. For a further 23 results, the substantive interpretations of our results matched those of the original researchers. The majority of the reproductions were performed relatively quickly by a psychology undergraduate with 2 years of relevant experience. Conclusion Psychology learning and teaching research appears more computationally reproducible than research in other psychology sub-fields. However, reproducibility is undermined by several factors, including a lack of open data and code. Teaching Implications Computational reproducibility activities can be incorporated into undergraduate research methods classes, effectively address many research methods learning outcomes, and help students develop both subject-specific and transferable employability skills.