National Science Foundation (DFG) awards grant to Prof. Dr. Ulf-Dietrich Reips

National Science Foundation (DFG) awards grant to Prof. Dr. Ulf-Dietrich Reips: A new three-year collaborative project on “Replicability of Fundamental Results on Spatial-Numerical Associations in Highly Powered Online Experiments (e-SNARC)” was awarded for a collaboration between Prof. Dr. Nuerck (University of Tübingen), Dr. Krzysztof Cipora (Loughborough University, UK) and iScience group.

Project summary: Spatial-Numerical Associations (SNAs) play a fundamental role for how humans represent numbers, and how they learn and use mathematics. Among SNAs, the Spatial-Numerical Association of Response Codes (SNARC, i.e., faster responses to small / large magnitude numbers with left / right hand respectively) effect is the hallmark, most thoroughly investigated effect. Nevertheless, despite almost three decades of research, many pivotal questions still remain unresolved. This may be partly due to the fact that several early SNARC results were obtained in small N (and probably underpowered) experiments. Because this limitation holds even for theoretically important and popular foundations of the SNARC effect, our understanding of SNAs considerably lacks in solidity of evidence and makes our common ground for further research shaky. For the presently granted project, we identify 3 fundamental questions about the SNAs and the SNARC effect, which we plan to address in highly powered large-scale online experiments: (1) automaticity – i.e., how much active semantic processing of the numerical stimuli is needed to evoke the spatial association, (2) task (in- )dependence – i.e., whether and how SNAs differ depending on the specific task we use to measure them, and (3) context (in-)dependence – i.e., whether spatial associations depend only on relative or also on absolute numerical magnitudes. For future empirical and theoretical developments it is essential to clarify these fundamental properties of the SNARC effect and provide high-quality empirical evidence, whether and under which circumstances these properties exist or not, and how large and reliable they are.