Noam Siegelman, PhD

Education:

Research Interests:

My research is concerned with statistical learning, reading, and their intersection, mostly from the prism of individual-differences. I am currently particularly interested in how individuals differ from one another in their literacy skills given their learning capacities and the properties of their native language’s writing system. I also have a soft spot for psychometrics, methodology, and statistical modeling.

Selected Publications:

Siegelman, N., Rueckl, J. G., Steacy, L. M., Frost, S. J., van den Bunt, M., Zevin, J. D., Seidenberg, M. S., Pugh, K. R., Compton, D. L., & Morris, R. D. (2020). Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills. Journal of Memory and Language. 

Siegelman, N., Bogaerts, L., Elazar, A., Arciuli, J., & Frost, R. (2018). Linguistic entrenchment: Prior knowledge impacts statistical learning performance. Cognition.

Siegelman, N., Bogaerts, L., Christiansen, M. H., & Frost, R. (2017). Towards a theory of individual differences in statistical learning. Philosophical Transactions of the Royal Society B.

Siegelman, N., Bogaerts, L., Kronenfeld, O., & Frost, R. (2017). Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities? Cognitive Science.

Siegelman, N., Bogaerts, L., & Frost, R. (2017). Measuring individual differences in statistical learning: Current pitfalls and possible solutions. Behavior Research Methods.

Siegelman, N., & Frost, R. (2015). Statistical learning as an individual ability: Theoretical perspectives and empirical evidence. Journal of Memory and Language.

Google Scholar: https://scholar.google.co.il/citations?user=u05YOWIAAAAJ&hl=en&oi=ao

Researchgate: https://www.researchgate.net/profile/Noam_Siegelman