United States

Previous research suggests that humans use multimodal information during emotional communication. Only a few studies have investigated how emotional information is presented in non-verbal channels. We examined the role of hand gestures in communicating emotions. In a between-subject design, we analyzed the size, frequency, and type of gestures under encouraged and spontaneous gesturing conditions. Participants (N=36) were asked to describe narratives with emotional content. Preliminary analyses with 18 individuals show that, interestingly, gesture frequencies and gesture use with specific emotional phrases did not differ between groups. Also, there was not a significant difference between the two groups in the types of gestures they produced. However, the gestures in the encouraged condition were significantly bigger in size compared to gestures in the spontaneous condition. These diverse preliminary results suggest that people’s hand gestures during emotional communication should be investigated with all their dimensions instead of focusing on one aspect.

CogSci 2021

The Role of Hand Gestures in Emotion Communication

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### THE CONFERENCE WE KNOW AND WE WANT.
**COLING**, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes but also in industrial research departments including tech-startups. COLING provides opportunities for all these communities to showcase their exciting discovery.

In fall of 2022, COLING will be held in Gyeongju in a hybrid format. All participants can either present at the venue site or join virtually. As more people get vaccinated, we are happy to provide safer environments for our colleagues. We believe that COLING 2022 will be one of the conferences, free from the pandemic. The hybrid format gives presenters and sponsors a valuable opportunity to promote their companies in both an online and in-person venue. For the first time in a long time, customers can interact with their sponsor's products first-hand. The online venue, too, gives sponsors the chance to network with those unable to attend the in-person session.

The hybrid format ultimately lends itself to greater exposure for our sponsors: COLING2022 will let you reach more potential partners and customers than ever before!<br><br><br>

To gain access to this event page you are required to register.<br> Find more information and pay the registration fee on event the organizer’s website **[https://coling2022.org/reg](https://coling2022.org/reg)**

COLING 2022

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

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### 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!<br><br>

**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.

Altering an individual’s identity during virtual tasks, such that it is incongruent with their own identity, can reduce unconscious biases and increase empathy and prosocial behavior. While such virtual embodiment has been investigated for race, age, and socioeconomic status, the question remains whether immersive perspective taking reduces implicit gender bias. Accordingly, we investigated the effect of gendered embodiment on gender bias related to the underrepresentation of women in science, technology, engineering, and math fields. Undergraduate students (N=65) undertook a simulated virtual interview task, which included the rating and selection of male and female candidates. Females were significantly more empathetic than males. Greater empathy predicted higher candidate ratings, except for competence of the female candidate. Preliminary findings establish foundations for future comparative studies and contribute to elucidating the nature of empathy during and after virtual perspective taking, such that it may have a greater impact on males for modulating gender bias.

Perspective Taking in Virtual Reality: Addressing Gender Bias in STEM

The COVID-19 pandemic and its profound global effects may be changing the way we think about illness. We surveyed 120 American adults to explore the effects of the pandemic on their mental models of illness. Participants read three vignettes: one relating to COVID-19, one to cancer, and another to the common cold, and were asked questions relating to the diagnosis, treatment, prevention, time-course, and transmission of each disease. Results showed that participants were more likely to correctly diagnose COVID-19 (93% accuracy) compared to a cold (60% accuracy) or cancer (51% accuracy). Of the 40 participants that incorrectly diagnosed the cold vignette, 7 misdiagnosed a cold as COVID-19. These and other preliminary findings suggest a distinct mental model for COVID-19 compared to other illnesses. The prevalence of COVID-19 in everyday discourse may lead to biased responding, similar to errors in medical diagnosis that result from physicians’ expertise (Hashem et al., 2003).

Mental Models of Illness in the COVID-19 Era

Across the lifespan, humans direct their learning towards information they are curious to know. However, it is unclear what elicits curiosity, and whether and how this changes across development. Is curiosity triggered by surprise and uncertainty, as prior research suggests, or by expected learning, which is often confounded with these features? In the present research, we use a Bayesian reinforcement learning model to quantify and disentangle surprise, uncertainty, and expected learning. We use the resulting model-estimated features to predict curiosity ratings from 5- to 9-year-olds and adults in an augmented multi-armed bandit task. Like adults’ curiosity, children’s curiosity was best predicted by expected learning. However, after accounting for expected learning, children (but not adults) were also more curious when uncertainty was higher and surprise lower. This research points to developmental changes in what elicits curiosity and calls for a reexamination of research that confounds these elicitors.

Developmental Change in What Elicits Curiosity

Relational reasoning is an important component of abstract thought that emerges early in development but shows substantial variation across contexts, with children in the US and China following distinct developmental trajectories in one paradigm between 18m and 4y. To understand the mechanisms through which variation in the learning environment influences the development of relational reasoning, we examine early relational reasoning in Punjabi speakers in India, who share some cultural and linguistic elements of their experience with children in both the US and China. In a causal relational match-to-sample task, we find that 3-year-olds in India exhibit performance that is intermediate to their high-performing peers in China and the relatively poor performance observed in the US at this age. These results suggest complexity and variability in the development of relational reasoning and lay a foundation for future research designed to tease apart the factors associated with early diversity in relational reasoning.

Characterizing the development of relational reasoning in India

Novel word disambiguation via mutual exclusivity is the tendency to discard familiar objects as referents of novel words. While mutual-exclusivity inferences have been widely documented in toddlers beyond 18 months of age, studies typically failed to show it in younger infants. Recently, Pomiechowska, Brody, Csibra, and Gliga (2021) showed that 12-month-old infants can use mutual exclusivity, but only if familiar objects are targeted by non-verbal communication (i.e., pointing) prior to labeling. This arguably triggers infants to represent these objects under a conceptual description, a representational format that is necessary for mutual exclusivity inferences but is not spontaneously generated in young infants. The present study is a direct online replication of the task used by Pomiechowska et al. with a wider age range (12-15 months) and adapted for Zoom-based testing.

Mutual exclusivity inferences in 12-to-15-month-olds: an online looking-while-listening study

We investigate whether reasoners are sensitive to the underlying causal structure of an event when evaluating its likely causes. Participants read stories in which two unknown causes led to an outcome in either a converging or linear structure. They were then asked to select two of three possible causes to complete the story. Two candidates were semantically-related, direct causes of the outcome. The third was an unrelated, indirect cause of the outcome that was conditional on a directly-related event. Differences in abstract structure, and not association, guided people’s evaluations of the most likely causes (e.g., ‘breeze blowing’ was judged an unlikely direct cause of a noisy room compared to ‘alarm ringing’ or ‘door slamming’, but a likely indirect cause, conditional on the door slamming). Results demonstrate that people consider abstract information about the structure of an event when evaluating causes. Knowledge of causal structure may therefore guide hypothesis evaluation.

Knowing the Shape of the Solution: Causal Structure Constrains Evaluation of Possible Causes.

Elementary schools provide students with their first encounters with formal science, creating both foundations for students’ knowledge of science content, and impressions of what it means to learn science. Here, we examined adult, including K-12 teachers’, intuitions regarding different types of content relevant to elementary school science, namely, labels, function, and mechanism. We focused primarily on perceptions of mechanistic explanations—causal explanations that explain how something works. This focus stems from children’s curiosity and aptitude for mechanism. Across four studies we predicted, and found, that participants deprioritize mechanistic explanations relative to more superficial explanation types: labels and function. This intuition, which appears to be reflected in formal science curricula, misestimates children’s abilities and attitudes towards mechanistic information.

Adult Intuitions about Mechanistic Content in Elementary School Science Lessons

The recent pandemic has emphasized the need for developing more effective pedagogical practices in online education. While activities that require more deep connection of concepts can enhance overall learning versus mere rote rehearsal, are conceptual activities also viable options for inclusion in online coursework, given the asynchronous and flexible nature of online learning? To answer this question, students in 2 online courses either completed concept-mapping exercises, or control exercises (i.e., definitions of concepts). Results indicate that while initially concept-mapping is no better than memorization, as experience with mapping increases, a growth in learning emerges later in the course. Students also rate the educational utility and enjoyablity of conceptual activities similarly to control exercises, suggesting that students do not perceive these conceptual activities more negatively. As such, concept-mapping does have a utility for online learning, but there is a necessary a warm-up period before benefits are realized.

Concept mapping produces delayed benefits in online learning.

As adults, we do not only choose what we prefer, but we also tend to adapt our preferences post-hoc to fit our previous choices, even when these were blind. This is thought to result from cognitive dissonance as an effort to reconcile our choices and preferences. It has been argued to rely on the self-concept, but has also been found in preschoolers and monkeys.
In a preregistered study, we therefore investigated when blind choice-induced preferences emerge and whether they are related to self-concept development in the second year of life. Results in N=200 children aged 16-36 months provide strong evidence that blind-choice induced preferences develop between 1 and 2 years (BF10=12.5). Two-year-olds avoided an object that they had previously discarded in a blind choice, whereas 1-year-olds did not show any such preferences yet. Further, we found substantial evidence against a relation with measures of self-concept development (BF10=0.2).

Does cognitive dissonance depend on self-concept? 2-year-old children, but not 1-year-olds, show blind choice-induced preferences

Though humans should defer to the superior judgement of AI in an increasing number of domains, certain biases prevent us from doing so. Understanding when and how these biases occur is a central challenge for human-computer interaction. A proposed source of such bias is the perceived subjectivity of tasks. We tested this hypothesis using one of the most subjective tasks possible: Evaluating joke funniness. Across two experiments, we addressed the following: Would people rate jokes as less funny if they believed an AI created them? When asked to rate jokes and guess their likeliest source, participants evaluated jokes attributed to humans as the funniest and those to AI as the least funny. However, when we explicitly framed these same jokes as either human or AI-created, there was no difference in performance-level ratings. These results challenge the notion that task subjectivity always biases users against AI if the source is transparent.

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Perspective Taking in Virtual Reality: Addressing Gender Bias in STEM

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