PSYC 3503/5570 Section 005: Introduction to Programming Complex Systems (3 credits)

Schedule: Tuesdays & Thursdays 12:30PM-1:45PM, Location TBD

Instructor: Whitney Tabor, whitney.tabor@uconn.edu

Description:

This course provides an introduction to programming in Python by exploring a series of complex systems phenomena, relevant to psychological processing.  It is open to undergraduates with Psychology, Language, Computing, Math, Physics, Cognitive Science, or Data Science background and to all graduate students.   It is open both to people who are relatively new to programming and people with more extensive programming experience who want to work on more advanced aspects of the topics.  Topics include a selection from dynamical systems, cellular automata, power laws, self-organization, fractals, machine learning, probabilistic grammars, synchronization, among others. 

Contact whitney.tabor@uconn.edu for a permission number or if you have questions.  There are no specific prerequisites but instructor permission is required to enroll in 3503.

PSYC 5150- Neurodevelopment and Plasticity (3 credits)

Schedule: Tuesdays 2PM-5PM, Location TBD

Instructor: Holly Fitch, roslyn.h.fitch@uconn.edu

Description:

PHIL 5305: Seminar on Fiction (3 credits)

Schedule: Mondays 4PM-6:30PM, Manchester Hall 227

Instructor: Mitch Green, mitchell.green@uconn.edu

Description:

This seminar will focus on issues occupying the nexus of several different philosophical areas including aesthetics, philosophy of language, philosophy of science, philosophy of mind, and metaphysics. Our phenomenon of study is the use of fictional discourse and behavior that in some way involves play, make-believe, pretense, supposition for argument’s sake, or thought experiment. We find this phenomenon in novels, short stories, plays, and fictional films—as well as in some philosophical argumentation, model-building in science, and play therapy; some also hold that we should construe certain kind of discourse, such as mathematical discourse or talk of possible worlds, as at bottom fictional.

With the aim of developing a defensible and reasonably comprehensive theory of fiction we’ll consider what kind of action is being performed by its utterer: is fiction a special kind of speech act, or does it fall outside the illocutionary realm? (Theories by Currie, Stock, Searle, Friend, and Davies will be considered here.) We will also look into theories of ‘truth in fiction’ that attempt to understand what it is for a proposition to be true in a fictional work even when not stated explicitly in that work. (Lewis, Friend, Pavel, Garcia-Carpintero.) Also, we will consider whether in spite of the fictional character of a work such as a novel, readers can gain anything of epistemic value from it such as knowledge or understanding. (Currie, Mikkonen, Green and Gibson.) We will also consider what it means to be a “fictionalist” about a certain realm of discourse (numbers, minds, possible worlds, God, propositions, values, etc.), and whether views of this kind are tenable in light of what we have learned about the nature of fictional discourse. (Rosen, Balaguer, Thomasson, Yablo, Kroon.)

This being a research seminar, students will be expected to develop work over the term that stands a chance of being a contribution to knowledge. To this end, students will write a mid-term essay (10-ish pages), and develop that into a larger paper (in the 15-20 page vicinity) due at the end of the term. Regular and informed contributions to seminar discussion are expected, and each enrolled student will present their work in progress in the final weeks of the term.

PSYC 5570 Section 002: Computational Approaches to Language and Mind (3 credits)

Schedule: Mondays 2PM-4:30PM, Bousfield 109

Instructor: Gerry Altmann, gerry.altmann@uconn.edu

Description: ChatGPT... where did it all start? And when? And what happened that AI seemed to go from 0 to 60 in a few blinks of the eye? On this course we shall answer questions such as these. We shall start in the 1980s with the advent of Connectionism and Neural Networks. We shall focus for a while on the conceptual lessons that we learned from “distributed semantic models” (DSMs) such as Latent Semantic Analysis (LSA), with vocabularies of 60,000+ words, and, perhaps more importantly, Simple Recurrent Networks (SRNs) with vocabularies of upwards of ... 27 words. Both these models became key components, through the nineties and noughties, of our understanding of how the mind might work. But things really got interesting when, on the tail- end of Gen Z, Word2Vec hit the streets; it transformed the landscape and was the flavor of the month for a good long while as yet more acronyms such as LSTMS, GRUs and others sprung from the woodwork. And then Transformers came along (not the movie...). For a while after, large-scale language models were named after Sesame Street characters. Why? Who knows... or cares. But Bert was the one to beat, until GPT 1, 2, 3.5, and 4 evolved. And by the time you read this, they’ll be old news and some new acronym will briefly occupy our lives. But through this steady evolution, one thing is clear: not much has changed conceptually in the 30+ years since Jeff Elman gave us the SRN. What has changed are the (often elegant) methods that allowed the scaling-up of those conceptual building blocks. The purpose of this course is to explain all this – to explain the concepts and (some of) the techniques that allowed them to scale up, and to de-mystify the acronyms and the buzz that surround modern-day AIs such as ChatGPT.

PSYC 5570 Section 004– Individual Differences in Language and Cognition (3 credits)

Schedule: Tuesdays 12:30PM-3:30PM, Bousfield 378A

Instructor: Jay Rueckl, jay.rueckl@uconn.edu

Description:

Individual differences in language and cognition have long been of interest to educators and clinicians and are becoming increasingly important to basic science as well.  In this course we will explore how the study of individual differences informs and is informed by theory in domains such as speech, reading, learning, memory, and attention.  We will also discuss a variety of methodological issues related to the design and analysis of individual-differences experiments.  Over the course of the semester, we will discuss research involving behavioral and neuroimaging measures, typical and atypical populations, and children and adults; explore various resources such as publicly available databases and assessment batteries; and consider individual differences and individual-difference assessments from the perspectives of both researchers and practitioners and with regard to diversity, equity, and inclusion concerns.   To the extent possible, the course will be structured to allow students to tailor their work to their own research interests and to help them conduct their own individual-differences studies. 

Note: Depending on scheduling constraints, the class may meet once per week for 3 hours or twice per week in 1- to 1.5-hour blocks.  To help set the schedule, I’ve created a When2Meet poll and I’m asking students who are interested in this course to email me (Jay.Rueckl@uconn.edu) for a link to that poll.   Completing the poll carries no obligations and I encourage you to complete the poll if there’s even a non-negligible chance that you’d take the course. 

PSYC 6783 Section 001– Tools to Analyze Language (3 credits)

Schedule: Tuesdays and Thursdays, 2PM-3:15PM, BOUS 109

Instructor: Alexandra Paxton, alexandra.paxton@uconn.edu

Description:

The purpose of this course is to introduce students to the links between natural language and psychological processes. This course is much more applied than theoretical, and it will include a range of ethical, methodological, and practical considerations that researchers weigh when working with natural data. 

Reasons for enrolling in the course:

1. Students will learn to work with existing corpora and to build novel corpora, and they will learn to analyze natural language using a range of premade software (e.g., Linguistic Inquiry and Word Count) and programming tools in R (e.g., tidytext). It thus accommodates students with varying degrees of expertise and from diverse backgrounds in the social sciences. 
2. A distinctive feature of this course lies in its project-oriented focus, culminating in conference presentations (e.g., Language Fest) and student publications. For example

2. • Ikizer et al. (2019). #sendeanlat (You tell it too): Text analysis of tweets about sexual harassment experiences of women in Turkey
   • McCloskey et al. (2022). Strange New Worlds: Comparing Star Trek fanfiction to commercial novels.
   • Pham et al. (2023). What are we fighting for? Lay theories about the goals and motivations of anti-racism activism.
   • Lin et al. (2023). Checking multiple boxes: Themes associated with bicultural identities.
3. This class is valid for students' Quantitative Methods certificates.

SLHS 6367 - 001   Topics in Hearing and Speech Science (3 credits)

Schedule: Tuesdays 10AM-12PM, HDC 147

Instructor: Derek Houston, derek.houston@uconn.edu

Description:

The aim of this course is to help prepare students for successful research careers in the speech, language, and hearing sciences by broadening their knowledge of leading-edge research questions and methodologies and by honing students’ skills of scientific inquiry, research design, and collaboration. These learning objectives will be accomplished by engaging in the following activities:

• Overview of SLHS: The first two weeks of the semester will serve as a broad survey of the constellation of topics explored within UConn’s department of Speech, Language, and Hearing Sciences. Students may be asked to represent their own labs’ research foci, and faculty will be recruited as necessary to ensure that all areas of the department are represented. 
• Deep Dives: 3-week modules to acquaint students with the research foci and methods employed by a particular researcher in the department. As part of these modules, students will prepare “Future directions follow-up” (FDF) where they will practice developing research ideas across a variety of topics. 
• Impromptu panels: The class will select broad topics and then invite 2-4 clinical and/or research faculty in SLHS to attend class and have open-ended discussions with each other and the students. Potential topics include “Hot Topics in SLHS”, “Concepts ‘known’ in clinical practice but not represented in research”, etc. Following each panel, students will write a 1-page reflection.
• Planned panels: Students will pair up to develop panels of specific research topics and invite 2-4 participants -- with an emphasis on promoting heterogeneity across divisions (clinical/research and speech/hearing) and career stage (student/faculty) – to prepare brief (5-8 minutes) ‘perspective statements’ and participate in answering prepared questions and engaging in general discussion with each other and students toward potential collaborations, future directions, etc. Following each panel, students will write a 1-page reflection.
• Guest speakers: A scientist or clinician (potentially from outside of SLHS or UConn) will give a guest-lecture overview of their work and area. Students will write 1-page reflections on what they learned, as well as application towards their own work and interests.
• Other: This course will be adaptable to student-driven learning goals and initiatives. 

It is expected that these activities will help students obtain a fund of knowledge and inquiry skills that will enhance their ability to contribute feedback to current and future colleagues’ research ideas and develop the perspective to be able to develop new interdisciplinary research areas.

This course was co-developed with Shawn Cummings with significant input from other students and faculty.