Elizabeth Pankratz

Dr. Elizabeth Pankratz is a Lecturer in the Department of Psychology at the University of Edinburgh, where she teaches statistics. She is affiliated with the School of Philosophy, Psychology and Language Sciences (PPLS) and maintains strong connections with the Centre for Language Evolution.

Dr. Pankratz completed her PhD at the University of Edinburgh's Centre for Language Evolution under the supervision of Prof. Jennifer Culbertson and Prof. Simon Kirby. Her doctoral research focused on language acquisition phenomena from a cognitive science perspective, culminating in her thesis "Segmentation, rule formation, and the emergence of generalisation."

Her research spans cognitive science, linguistics, and psychology, with particular emphasis on how humans learn and generalize from concrete surface representations to abstract rules and patterns. Dr. Pankratz investigates language acquisition mechanisms, examining word segmentation, rule learning, and generalization processes through diverse methodological approaches including behavioral experiments, computational modeling, and corpus analysis.

Dr. Pankratz's publication record reveals a cohesive research trajectory focused on cognitive mechanisms underlying language processing and acquisition. Her work explores how frequency distributions influence linguistic rule generalization, the relationship between language production and morphosyntactic learning, and the cognitive foundations of scalar inferences. She employs complementary methods to investigate language phenomena across different contexts, ages, and languages, contributing to our understanding of the cognitive architecture that supports language knowledge.

• Supervises undergraduate and postgraduate dissertations
• Mentored Sigurd Farstad Iversen (MSc Language and Cognition, 2023)

Dr. Pankratz is actively engaged in research collaborations examining language register, cognitive modeling of linguistic phenomena, and the statistical properties of language processing. Her teaching focuses on statistics for psychology students, bridging methodological rigor with practical applications in cognitive science research.