It has been long argued that languages have evolved to better suit the needs of human communication. Using miniature artificial language experiments administered in the lab and over the web, I explore whether preferences for efficient information transmission in individual users can indeed give rise to certain cross-linguistic commonalities in syntax and morphology found in natural languages.

Read more:

• Fedzechkina, M. & Jaeger T.F. (2020). Production efficiency can cause grammatical change: Learners deviate from the input to better balance efficiency against robust message transmission. Cognition.
• Hall Hartley, L. Fedzechkina, M. (2020). Learners’ bias to balance production effort against message uncertainty is independent of their native language. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.
• Fedzechkina, M., Newport, E.L., & Jaeger T.F. (2017). Balancing effort and information transmission during language acquisition: Evidence from word order and case marking. Cognitive Science.
• Fedzechkina, M., Jaeger T.F., & Newport, E.L. (2012). Language learners restructure their input to facilitate efficient communications. PNAS.

Sentence processing is incremental – listeners form provisional hypotheses about sentence structure as the utterance unfolds over time. I study exploring whether biases stemming from this incremental nature of sentence processing affect learners’ productions and play a role in language change.

Read more:

• Fedzechkina, M., Chu, B., & Jaeger T.F. (2018). Human information processing as a cause of language change: Learners prefer shorter dependencies. Psychological Science.
• Fedzechkina, M., Jaeger T.F., & Trueswell, J.C. (2015). Production is biased to provide informative cues early: Evidence from miniature artificial languages. Proceedings of CogSci 2015.

The underlying assumption behind miniature language learning applications to the study of language structure is that individual-level biases would be amplified as they are picked up by the population and percolate across multiple generations of speakers, gradually causing the linguistic system to explicitly express these biases. In ongoing work, I explore such questions as a) Can cognitive biases observed in a single generation of learners survive transmission across generations? b) How do these cognitive biases interact with social pressures at the population level?

Read more:

• Fedzechkina, M. & Roberts, G. (2020). Learners sacrifice robust communication as a result of a social bias. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.
• Roberts, G. & Fedzechkina, M.(2018). Social biases modulate the loss of redundant forms in the cultural evolution of language. Cognition.

I explore how second language learning outcomes are shaped by the interactions between linguistic input and learners’ expectations. I am particularly interested in how the typological distance between learners' L1 and L2 influences their expectations about L2 structure.