Masterclass in Computational Modelling
Embracing the Computational Turn in Data-Driven Linguistics
In a field where the nuances of language often defy reduction, computational approaches to linguistics offer both challenges and transformative potential. This workshop makes a compelling case for the “Computational Turn” in Data-Driven Approaches Linguistics – the DAL in the MEDAL – emphasizing how cognitive plausibility and precision can turn computational models into powerful tools for linguistic inquiry.
Participants will explore the barriers that have limited the uptake of computational methods in cognitive linguistics, such as steep learning curves, reliance on Big Data, and the demand for exact instruction. Through a rich mix of the “history of ideas” and hands-on examples, the workshop will demonstrate how computational models can be tailored to address linguistic complexity, delivering empirically testable predictions and actionable insights.
Join us to reimagine computational approaches as a means to deepen linguistic understanding, bridging the gap between the precision of algorithms and the richness of language.
When? January 29th until January 31st
Where? This is an in-person event at the University of Tartu in room Jakobi 2-438
Important information about the event:
During these sessions you will learn to use computational models based on research on learning from psychology. After an introduction to the principles of learning (Wednesday), we will demonstrate how these models can be used for the analysis of linguistic data, using some of our own work. We will show results from both L1 (Thursday) and L2 (Friday), show how annotated corpus data can be used in the computational models (Thursday), and how computational modelling can be used to generate hypotheses that can be tested in experimental or classroom settings (Friday). Mornings will be delivered lecture-style, while afternoons are hands-on workshops. The workshop are tailored for participants with no programming experience, and make use of our cloud computation infrastructure. They will include hands-on work with existing data while also setting aside time for participants to apply what they have learned to their own data. Please make sure you have a functioning Python version and check that Jupyter Notebook (or JupyterLab) is working (you can consider using the very popular Anaconda distribution available here: https://www.anaconda.com/download/
Relevant publications include, but are not limited to:
https://www.degruyter.com/document/doi/10.1515/cog-2021-0006/html - Romain, Ez-zizi, Milin & Divjak (2022)
https://brill.com/display/title/61525 - Divjak & Milin (2023)
https://www.degruyter.com/document/doi/10.1515/ling-2022-0186/html - Divjak, Romain & Milin (2023)
https://onlinelibrary.wiley.com/doi/pdf/10.1111/lang.12675 - Romain, Milin & Divjak (2024)
Schedule:
Wednesday (29-01) in room Jakobi 2-438
2:00-4:00 PM
Thursday (30-01) and Friday (31-01) in room Jakobi 2-438
10:00-12:00 AM
2:00-4:00 PM
About the instructors
Petar Milin is Professor of Psychology of Language and Language Learning. Learn more about his work here.
Dagmar Divjak is a Professor of Cognitive Linguistics and Language Cognition at the University of Birmingham and part of the Out Of Our Minds team.
Learn more about her work here.
