Kristine Zheng

My statement on Ai from the mini-comic as syllabus i made for new class I'm teaching that starts tomorrow! It robs you of your decisions & struggles - and the joy of being surprised. We won’t to be robbed of our learning - this is essential. This & the full mini at post:
bsky.app/profile/nsou...

Now out in Cognition, work with the great @gershbrain.bsky.social @tobigerstenberg.bsky.social on formalizing self-handicapping as rational signaling!
📃 authors.elsevier.com/a/1lo8f2Hx2-...

🚨 NEW PREPRINT: Multimodal inference through mental simulation.

We examine how people figure out what happened by combining visual and auditory evidence through mental simulation.

Paper: osf.io/preprints/ps...
Code: github.com/cicl-stanfor...

Josh Tenenbaum's inspiring keynote at #cogsci2025 on growing vs scaling AI, the big questions of cognitive science, and the many open questions for the field.

If you're heading to @cogscisociety.bsky.social, come to our symposium “Perception as a Foundation for Common‑Sense Theories of the World”

📅 August 1 • 9 AM
📍 Salon 2

With
@thiskevinsmith.bsky.social
@shariliu.bsky.social
@judithfan.bsky.social
@ardeeb.bsky.social
— See you there! #CogSci2025

In ongoing work, we’re exploring other behavioral measures of student engagement and developing interventions to help more students overcome psychological barriers to succeeding in these courses!

We found robust links between various psychological factors (math anxiety, stress expectations, interest in math, self-efficacy, etc.) and quiz performance. But simply completing more of the learning activities was not associated with better performance!

We focused on estimating the strength of links between the attitudes/beliefs/knowledge students brought with them to the course (e.g., math anxiety; prior coding experience), their subsequent day-to-day engagement with the material, and their performance on quizzes.

We partnered with CourseKata (coursekata.org) to analyze longitudinal student learning data from 45 college-level data sci courses across 11 institutions.

Students come into data sci courses with varying levels of motivation and assumptions about themselves and the material. How do these psychological factors interact with their level of engagement with the course to determine how much they learn?

Linking student psychological orientation, engagement & learning in intro college-level data science

New work ‪‪at @cogscisociety.bsky.social w/ @erikbrockbank.bsky.social @shawnschwartz.bsky.social, C.Bryan, D.Yeager, C.Dweck & @judithfan.bsky.social

poster 8/1 @ 10:30
tinyurl.com/solds-cogsci25

We focused on estimating the strength of links between the attitudes/beliefs/knowledge students brought with them to the course (e.g., math anxiety; prior coding experience), their subsequent day-to-day engagement with the material, and their performance on quizzes.

We partnered with CourseKata (coursekata.org) to analyze longitudinal student learning data from 45 college-level data sci courses across 11 institutions.

Students come into data sci courses with varying levels of motivation and assumptions about themselves and the material. How do these psychological factors interact with their level of engagement with the course to determine how much they learn?

Students come into data sci courses with varying levels of motivation and assumptions about themselves and the material. How do these psychological factors interact with their level of engagement with the course to determine how much they learn?

Excited to share our new work at #CogSci2025!

We explore how people plan deceptive actions, and how detectives try to see through the ruse and infer what really happened based on the traces left behind. 🕵️‍♀️

Paper: osf.io/preprints/osf/vqgz5_v1
Code: github.com/cicl-stanford/recursive_deception

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Excited to be sharing my latest work with @tobigerstenberg.bsky.social at #CogSci2025!

Learning usually occurs when we encounter new data. But we also have the capacity to reflect on our past experiences. What can we learn from simulating past experience?

📃 cicl.stanford.edu/papers/yang2...

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"36 Questions That Lead To Love" was the most viewed article in NYT Modern Love.
Excited to share new results investigating these and other “deep questions” with @tobigerstenberg.bsky.social @judithfan.bsky.social & @rdhawkins.bsky.social
Preprint: tinyurl.com/bdfx5smk
Code: tinyurl.com/3v6pws4s

🎤 "Your #CogSci presentation was quite good this year."

How flattered or offended will you be? The answer may depend on whether you speak British or American English 🇺🇸🇬🇧. Our new #CogSci2025 paper reveals systematic differences in how different cultures interpret the same words.

Decoding predicted future states from the brain’s “physics engine” Using fMRI in humans, this study provides evidence for future state prediction in brain regions involved in physical reasoning.

Thrilled to announce our new publication titled 'Decoding predicted future states from the brain's physics engine' with @emiecz.bsky.social, Cyn X. Fang, @nancykanwisher.bsky.social, @joshtenenbaum.bsky.social

www.science.org/doi/full/10....

(1/n)

Delighted to announce our CogSci '25 workshop at the interface between cognitive science and design 🧠🖌️!

We're calling it: 🏺Minds in the Making🏺
🔗 minds-making.github.io

June – July 2024, free & open to the public
(all career stages, all disciplines)

Attending to Remember: Recent Advances in Methods and Theory - Shawn T. Schwartz, Haopei Yang, Alice M. Xue, Anthony D. Wagner, 2025 The ability to learn from and remember experiences (episodic memory) depends on multiple neurocognitive systems. In this article, we highlight recent advances i...

I’m pleased to share our new review article, “Attending to Remember: Recent Advances in Methods and Theory”, written with Haopei Yang (HY), Alice Xue, and Anthony Wagner, now out in Current Directions in Psychological Science. 🚀🧠 A brief thread 🧵
doi.org/10.1177/09637214251339452

Looking at Van Gogh’s Starry Night, we see not only its content (a French village beneath a night sky) but also its *style*. How does that work? How do we see style?

In @nathumbehav.nature.com, @chazfirestone.bsky.social & I take an experimental approach to style perception! osf.io/preprints/ps...

🕊️📈

Whoops I apparently have no idea how graphics work, please enjoy this hilarious inverted SVG situation and head to project-nightingale.stanford.edu to see the *real* graphic

Hello bluesky world :) excited to share a new paper on data visualization literacy 📈 🧠 w/ @judithfan.bsky.social, @arnavverma.bsky.social, Holly Huey, Hannah Lloyd, @lacepadilla.bsky.social!

📝 preprint: osf.io/preprints/ps...
💻 code: github.com/cogtoolslab/...

AI is ‘beating’ humans at empathy and creativity. But these games are rigged | MJ Crockett Research pitting people against AI systems gives AI an edge by asking us to perform in machine-like ways

My new piece in @theguardian.com

Techno-optimism is human pessimism.

www.theguardian.com/commentisfre...

Does the culture you grow up in shape the way you see the world? In a new Psych Review paper, @chazfirestone.bsky.social & I tackle this centuries-old question using the Müller-Lyer illusion as a case study. Come think through one of history's mysteries with us🧵(1/13):