Zoom link for my talk: Twenty years of retrieval models

Here is the zoom registration link to my talk at UMass on Sept 25, 21:30 CEST (15:30 UMass time).
Title: Twenty years of retrieval models
Abstract:
After Newell wrote his 1973 article, "You can't play twenty questions with nature and win", several important cognitive architectures emerged for modeling human cognitive processes across a wide range of phenomena. One of these, ACT-R, has played an important role in the study of memory processes in sentence processing. In this talk, I will talk about some important lessons I have learnt over the last 20 years while trying to evaluate ACT-R based computational models of sentence comprehension. In this connection, I will present some new results from a recent set of sentence processing studies on Eastern Armenian.
Reference: Shravan Vasishth and Felix Engelmann. Sentence comprehension as a cognitive process: A computational approach. 2021. Cambridge University Press. https://vasishth.github.io/RetrievalModels/ Zoom registration link:
You are invited to a Zoom webinar. When: Sep 25, 2020 09:30 PM Amsterdam, Berlin, Rome, Stockholm, Vienna Topic: UMass talk Vasishth
Register in advance for this webinar: https://zoom.us/webinar/register/WN_89F7BObjSwmxnK6DRC9fuQ
After registering, you will receive a confirmation email containing information about joining the webinar.

Twenty years of retrieval models: A talk at UMass Linguistics (25 Sept 2020)

I'll be giving a talk at UMass' Linguistics department on 25 September, 2020, over zoom naturally. Talk title and abstract below:
Twenty years of retrieval models
Shravan Vasishth (vasishth.github.io)
After Newell wrote his 1973 article, "You can't play twenty questions with nature and win", several important cognitive architectures emerged for modeling human cognitive processes across a wide range of phenomena. One of these, ACT-R, has played an important role in the study of memory processes in sentence processing. In this talk, I will talk about some important lessons I have learnt over the last 20 years while trying to evaluate ACT-R based computational models of sentence comprehension. In this connection, I will present some new results from a recent set of sentence processing studies on Eastern Armenian.
Reference: Shravan Vasishth and Felix Engelmann. Sentence comprehension as a cognitive process: A computational approach. 2021. Cambridge University Press. https://vasishth.github.io/RetrievalModels/

Registration open for two statistics-related webinars: SMLP Wed 9 Sept, and Fri 11 Sept 2020

As part of the summer school in Statistical Methods for Linguistics and Psychology, we have organized two webinars that anyone can attend. However, registration is required. Details below

Keynote speakers

• Wed 9 Sept, 5-6PM:Christina Bergmann (Title: The "new" science: transparent, cumulative, and collaborative)
  Register for webinar: here
  Abstract: Transparency, cumulative thinking, and a collaborative mindset are key ingredients for a more robust foundation for experimental studies and theorizing. Empirical sciences have long faced criticism for some of the statistical tools they use and the overall approach to experimentation; a debate that has in the last decade gained momentum in the context of the "replicability crisis." Culprits were quickly identified: False incentives led to "questionable research practices" such as HARKing and p-hacking and single, "exciting" results are over-emphasized. Many solutions are gaining importance, from open data, code, and materials - rewarded with badges - over preregistration to a shift away from focusing on p values. There are a host of options to choose from; but how can we pick the right existing and emerging tools and techniques to improve transparency, aggregate evidence, and work together? I will discuss answers fitting my own work spanning empirical (including large-scale), computational, and meta-scientific studies, with a focus on strategies to see each study for what it is: A single brushstroke of a larger picture.
• Fri 11 Sept, 5-6PM: Jeff Rouder Title: Robust cognitive modeling
  Register for webinar: here
  Abstract: In the past decade, there has been increased emphasis on the replicability and robustness of effects in psychological science. And more recently, the emphasis has been extended to cognitive process modeling of behavioral data under the rubric of “robust models." Making analyses open and replicable is fairly straightforward; more difficult is understanding what robust models are and how to specify and analyze them. Of particular concern is whether subjectivity is part of robust modeling, and if so, what can be done to guard against undue influence of subjective elements. Indeed, it seems the concept of "researchers' degrees of freedom" plays writ large in modeling. I take the challenge of subjectivity in robust modeling head on. I discuss what modeling does in science, how to specify models that capture theoretical positions, how to add value in analysis, and how to understand the role of subjective specification in drawing substantive inferences. I will extend the notion of robustness to mixed designs and hierarchical models as these are common in real-world experimental settings.