In one line of research, I explore how people represent and retrieve concepts from semantic memory. How does semantic cognition vary across different groups?

In another line of research, I investigate how people reason about explanations in everyday life. When does an explanation lead to increased understanding? Why do we find some explanations compelling, even when they are wrong?

Methodologically, my work primarily focuses on behavioral data from healthy adults but also intersects with research on aging and age-related disorders. I use a variety of computational tools, including Bayesian graphical models, network science, and distributed semantic representations.

Zemla, J. C., Sloman, S. A., Bechlivanidis, C., & Lagnado, D. A. (2023). Not so simple! Causal mechanisms increase preference for complex explanations. Cognition, 239, 105551.

Zemla, J. C., Gooding, D. C., & Austerweil, J. L. (2023). Evidence for optimal semantic search throughout adulthood. Scientific Reports, 13(1), 22528.

Zemla, J. C., & Austerweil, J. L. (2019). Analyzing knowledge retrieval impairments associated with Alzheimer’s disease using network analyses. Complexity, 2019(1), 4203158.

Zemla, J. C., Sloman, S., Bechlivanidis, C., & Lagnado, D. A. (2017). Evaluating everyday explanations. Psychonomic Bulletin & Review, 24, 1488-1500.