Noam Siegelman, PhD
|PhD||Cognitive Sciences, Hebrew University of Jerusalem (2019, expected)|
|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., 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.