United States

CogSci 2021

Information density in visual narrative units and sequences

<center>Louis Stokes Regional Center of Excellence for the Study of STEM Interventions<center>

<CENTER>Translating Critical, Strengths-Based Conceptual Frameworks to STEM Programming Design & Dissemination<CENTER>


 **Sponsored in Partnership by:**
 National Science Foundation, Understanding Interventions, University of Michigan and University of Missouri
 
 
 		
	
Dear Colleagues,

Welcome to the inaugural Louis Stokes Regional Center of Excellence for the Study of STEM Interventions ‎‎(LSCRE ‎‎‎‎SOSI) Summer Institute. SOSI is an NSF funded initiative that reflects a collaboration of STEM and STEM Education Scholars ‎and Program Administrators from the University of Missouri-Columbia, Understanding ‎Interventions, Inc., and the University of Michigan.‎ We offer training and development for STEM program administrators, faculty, and other ‎stakeholders ‎in critical, strengths-based theories and evidence-based practices. Key to our work is providing the tools and avenues for our participants to inform their practice and contribute to the body of translational research that facilitate ‎underrepresented students’ success in STEM. Beyond the Summer Institutes, SOSI, through the Understanding Interventions Index, supports resources for access to the STEM research-to-practice translational literature, a database of journals that publish these works, relevant published measures, and the Understanding Interventions Journal as an outlet for dissemination. This work also extends to webinars and workshops held throughout the year as an integral part of the collaboration between SOSI and its partners. 

This 2021 Summer Institute is designed to address participant needs across a range of experience in our concurrent sessions. Concurrent Sessions 1 are tailored for those of us who have professional training outside the social and behavioral sciences but are looking to develop proficiency, scholarship, and utilize methodologies that test theories like Community Cultural Wealth (CCW), Phenomenological Variant of Ecological Systems Theory (PVEST) and Social Cognitive Career Theory (SCCT). Concurrent Sessions 2 are tailored to those with some experience in these areas and are looking to engage more deeply. Some sessions like those that address measures, implementation, and outcomes will be joint. For the current topic sessions, participants will not be limited a specific concurrent session but will have the flexibility to attend the session that they feel most appropriate to their level of experience. 

We look forward to an exciting and productive institute as we all leverage our varied experiences, perspectives, and ideas to this growing community of practice. We would also like to extend our deep gratitude to the National Science Foundation for its generous support of this work.


Best,

SOSI Leadership Team

SOSI Virtual Summer Institute 2021

symposium

### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year! 

**Your Program Chairs,**
![](https://assets.underline.io/uploads/markdown_image/1/image/99984908caba5e6453e5fc5ba34f3507.jpg)

**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

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To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

Evidence has shown that goals systematically change risk preferences in repeated decisions under risk. For instance, decision makers could aim to reach goals in a limited time, such as “making at least $1000 with ten stock investments within a year.” We test whether goal-based risky decisions differ when facing gains as compared to losses. More specif-ically, we examine the impact of outcome framing (gains vs. losses) and state framing (positive vs. negative resource states) on goal-based risky decisions. Our results (N=100) reveal no framing effects; instead, we find a consistently strong effect of the goal on risk preferences independent of framing. Computational modeling showed that a dynamic version of prospect theory, with a goal-dependent reference point, described 87% of participants best. This model treats outcomes as gains and losses depending on the state-goal distance. Our results show how goals can erase standard framing effects observed in risky choices without goals.

How Goals Erase Framing Effects in Risky Decision Making

From navigation in unfamiliar environments to career planning, people typically first sample information before committing to a plan. However, most studies find that people adopt myopic strategies when sampling information. Here we challenge those findings by investigating whether contingency planning is a driver of information sampling. To this aim, we developed a novel navigation task that is a shortest path finding problem under uncertainty of bridge closures. Participants (n = 109) were allowed to sample information on bridge statuses prior to committing to a path. We developed a computational model in which the agent samples information based on the cost of switching to a contingency plan. We find that this model fits human behavior well and is qualitatively similar to the approximated optimal solution. Together, this suggests that humans use contingency planning as a driver of information sampling.

Information sampling for contingency planning

Recent philosophical work has taken interest in the decision-theoretic problems posed by transformative experiences, or experiences that are epistemically revelatory and life-changing (like becoming a parent). The problem is roughly as follows: if we cannot know what it’s like to be a parent (its subjective value) before actually becoming one, then how are we to decide whether to become one? This topic has received recent empirical attention, some of which has challenged the central importance of subjective value for transformative decision-making. Here, we present empirical work that suggest these findings can be explained by the evaluability bias, in which people weigh decision criteria not based on their importance, but how easy they are to evaluate. Participants not only find subjective value important, but they report willing to pay a great deal of money to get this information. Furthermore, participants who were most uncertain about whether to undergo a transformative decision we most likely to report interest in seeking out information about subjective value. We conclude by considering the philosophical and empirical implications of this work.

Evaluating Transformative Decisions

We propose a computational model of social preference judgments that accounts for the degree of an agents’ uncertainty about the preferences of others. Underlying this model is the principle that, in the face of social uncertainty, people interpret social agents’ behavior under an assumption of expected utility maximization. We evaluate our model in two experiments which each test a different kind of social preference reasoning: predicting social choices given information about social preferences, and inferring social preferences after observing social choices. The results support our model and highlight how uncertainty influences our social judgments.

Reasoning about social attitudes with uncertain beliefs

Humans are social beings, and most of our decisions are influenced by considerations of how others will respond. Whether in poker or political negotiations, the riskiness of a decision is often determined by the variance of the other party's possible responses. Such socially-contingent decisions can be framed in terms of adversarial games, which differ from other risky situations such as lotteries because the risk arises from uncertainty about the opponent's decisions, and not some independent stochasticity in the world. 
We use chess as a lens through which we can study human risk-taking behavior in adversarial decision making. We develop a novel algorithm for calculating the riskiness of each move in a chess game, and apply it to data from over 1 billion online chess games. We find that players not only exhibit state-dependent risk preferences, but also change their risk-taking strategy depending on their opponent, and that this effect differs in experts and novices.

Risk-taking in adversarial games: What can 1 billion online chess games tell us?

Curiosity drives much of human behavior, but its open-ended nature makes it hard to study in the laboratory. Moreover, computational theories of curiosity -- models of how intrinsic motivation promotes complex behaviors -- have been challenging to test because of technical limits. To circumvent this problem, we develop a new way to assess intrinsic motivation for building: we assume people build what they find interesting, so we asked them to rate the "interestingness" of visual stimuli -- in this case, simple block towers.
Adults gave a range of ratings to towers built by children, with taller towers rated higher.
To probe interestingness further, we developed controlled tower stimuli in a simulated 3D environment. While tower height predicted much of the variation in ratings, people also favored more precarious towers, as inferred from geometric features and simulated dynamics. These ratings and features therefore give a clear target for computational accounts of curiosity to explain.

Information density in visual narrative units and sequences

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Information density in visual narrative units and sequences

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Next from CogSci 2021

How Goals Erase Framing Effects in Risky Decision Making

Similar lecture

How We (STEM Programs) Got Here

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES

Downloads