Noam Siegelman, PhD
|PhD||Cognitive Sciences, Hebrew University of Jerusalem (2019)|
|MA||Cognitive Sciences, Hebrew University of Jerusalem|
|BA||Cognitive Sciences & Linguistics, Hebrew University of Jerusalem|
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.
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.