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Cheng-Yu Hsieh

@cyhsieh.bsky.social
133 followers 169 following 11 posts

Born and raised in Taiwan PhD student @rhulpsychology.bsky.social Interested in language and concept

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Reposted by Cheng-Yu Hsieh
Andrea de Varda @andreadevarda.bsky.social · 01/09/2026
New preprint! 🧠👀🤖 Behavioral and brain responses to language reflect different levels of linguistic representation w/ @whylikethis.bsky.social , @evfedorenko.bsky.social , and @rplevy.bsky.social (1/10)
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Jenni Rodd @jennirodd.bsky.social · 25/06/2026
Finally out at @cp-trendscognsci.bsky.social. Everything I think I know about word meanings. Particular focus on words that are unfamiliar or ambiguous. www.sciencedirect.com/science/arti...
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Caroline Rowland @carorowland.bsky.social · 23/06/2026
My list on what to read about theory-driven cognitive science has now been updated to add a few more thoughts and references about the role of AI as 'in silico' models of human cognition. Your comments welcome - please add to the googledoc. docs.google.com/document/d/1...
docs.google.com
Theory: What to read
The role of theory in cognitive science Or: my guide to what to read if you really want to understand how to do good, robust , theory-driven cognitive science. (disclaimer: this is an aspirational gu...
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Andrew Wang @andreww3-wang.bsky.social · 07/05/2026
📄 New paper out in Collabra: Psychology. This work (with @perfors.net) shows how subtle differences in language use between humans & LLMs can be captured by measures of vocabulary centrality. 🔗 doi.org/10.1525/coll... @ucpress.bsky.social
doi.org
Core Vocabulary Reveals Differences Between Human Word Prediction and Large Language Models
The question of which words are the most central or important to a language has been explored in various ways. In this study, we propose definitions of core vocabulary that are based on how language i...
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Greg Woodin @gregwoodin.bsky.social · 16/06/2026
How precise are numbers? Our new article in Language and Cognition (with @bodowinter.bsky.social and @lordlorson.bsky.social) finds that round numbers are used more approximately at higher magnitudes. (1/5) 👇 www.cambridge.org/core/journal...
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Women in AI Research - WiAIR @wiair.bsky.social · 18/06/2026
🎙️ 𝐍𝐞𝐰 #𝐖𝐢𝐀𝐈𝐑 𝐄𝐩𝐢𝐬𝐨𝐝𝐞 𝐎𝐮𝐭! In the new #WiAIRpodcast episode with @neuranna.bsky.social, we talk about the relationship between language, thought, and intelligence, with insights from neuroscience, cognitive science, and AI research. 📷 YouTube: youtu.be/e36ryy0Dsdo
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Open Encyclopedia of Cognitive Science bot @oecs-bot.bsky.social · 19/06/2026
Meaning emerges from context: by mapping how words share linguistic environments, algorithms can mathematically capture the nuanced relationships… Distributional Semantics by Gemma Boleda oecs.mit.edu/pub/gbaucew9 #CognitiveScience
Figure from the OECS article "Distributional Semantics".
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languagemit.bsky.social @languagemit.bsky.social · 20/06/2026
—— Open Mind is MIT Press’s Diamond Open Access Cognitive Science journal. We now have our first Impact Factor: 2.9 as of June 2026 Submit your papers to Open Mind direct.mit.edu/opmi
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Andrew Lampinen @lampinen.bsky.social · 26/05/2026
We've updated the preprint of our Naturalistic Computational Cognitive Science paper (arxiv.org/abs/2502.20349) — we've tried to clarify and streamline the arguments, and added some new examples: 1/5
arxiv.org
Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior
How can cognitive science build generalizable theories that span the full scope of natural situations and behaviors? We argue that progress in Artificial Intelligence (AI) offers timely opportunities ...
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Open Mind @openmindjournal.bsky.social · 26/05/2026
Child-Directed Speech Facilitates Semantic Role Learning: A Machine Learning Approach
direct.mit.edu
Child-Directed Speech Facilitates Semantic Role Learning: A Machine Learning Approach
Abstract. Semantic roles, namely the agent (‘doer’) and patient (‘undergoer’) roles, are fundamental to language acquisition, as they enable learners to map meaning onto syntactic structure. Grammars…
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Mike Frank @mcxfrank.bsky.social · 26/05/2026
If a student reads a typical psychology paper, picks an experiment, and tries to replicate it, they have roughly a coin-flip chance of success. That's the punchline of a decade of metascience, and it's the focus of Ch 3 of Experimentology. 🧵 experimentology.io
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arXiv q-bio.NC Neurons and Cognition @qbionc-bot.bsky.social · 30/07/2025
Katerina Marie Simkova, Adrien Doerig, Clayton Hickey, Ian Charest: Representations in vision and language converge in a shared, multidimensional space of perceived similarities arxiv.org/abs/2507.21871 arxiv.org/pdf/2507.21871 arxiv.org/html/2507.21871
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Iris van Rooij 💭 @irisvanrooij.bsky.social · 06/01/2026
✨ Updated preprint ✨ Iris van Rooij & Olivia Guest (2026). Combining Psychology with Artificial Intelligence: What Could Possibly Go Wrong? PsyArXiv osf.io/preprints/psyarxiv/aue4m_v2 @olivia.science Our aim is to make these ideas accessible for a.o. psych students. Hope we succeeded 🙂
Figure 1
Illustration of why AI systems cannot realistically scale to human cognition within the foreseeable future: (b) Human cognitive capacities (such as reasoning, communication, problem solving, learning, concept formation, planning etc.) can handle unbounded situations across many domains, ranging from simple to complex. (a) Engineers create AI systems using machine learning from human data. (d) In an attempt to approximate human cognition a lot of data is consumed. (c) Making AI systems that approximate human cognition is intractable (van Rooij, Guest, et al., 2024), i.e., the required resources (e.g. time, data) grows prohibitively fast as input domains get more complex, leading to diminishing returns. (a) Any existing AI system is
created in limited time (hours, months or years, not millennia or eons). Therefore, existing AI systems cannot realistically have the domain-general cognitive capacities that humans have. [Made with elements from freepik.com.]
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Sathvik @sathvik.bsky.social · 22/05/2026
What (if anything) can LLMs tell us about human language processing? I discuss this question and how psycholinguistics is moving forward with @colinphillips.bsky.social , to appear in BBS as a commentary on Futrell & Mahowald's article about LLMs & linguistics. arxiv.org/abs/2604.09466
Title & Abstract:
Across the Levels of Analysis: Explaining Predictive Processing in Humans Requires More Than Machine-Estimated Probabilities
Sathvik Nair & Colin Phillips
Commentary on Futrell, R. & Mahowald, K. (in press). How Linguistics Learned to Stop Worrying and Love the Language Models. Behavioral and Brain Sciences. http://doi.org/10.1017/S0140525X2510112X
Abstract
Under the lens of Marr’s levels of analysis, we critique and extend the authors’ two points about language models (LMs) and language processing: first, predicting upcoming linguistic information based on context is key to language processing, and second, that many advances in psycholinguistics would be impossible without LLMs. We also outline directions combining LLMs’ strengths with psycholinguistic models.
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Nicole Rust @nicolecrust.bsky.social · 22/05/2026
Brilliant! In part b/c it holds up happiness as an illustration of what’s what 😉. But more seriously: IF YOUR SO CALLED THEORY DOESN‘T MAKE TESTABLE PREDICTIONS IT’S A FRAMEWORK. #TheoriesAreTheGoal Excellent example of an influential framework-not-a-theory here: experimentology.io/002-theories...
experimentology.io
2  Theories – Experimentology
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Tom McCoy @rtommccoy.bsky.social · 18/05/2026
🤖🧠 New commentary 🧠🤖 What role should large language models (LLMs) play in linguistics? I reflect on this question in a commentary now on arXiv: arxiv.org/abs/2605.10061 To appear in BBS as a commentary on @futrell.bsky.social and @kmahowald.bsky.social's excellent piece on LLMs & Linguistics!
Screenshot of the title and abstract of a paper.
Title: "Not-So-Strange Love: Language Models and Generative
Linguistic Theories are More Compatible than They Appear"
Further information: "Open Peer Commentary on “How Linguistics Learned to Stop Worrying and
Love the Language Models” by Richard Futrell and Kyle Mahowald"
Author: R. Thomas McCoy
Abstract: Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in the generative tradition. This argument expands the space of theories that can be tested with LMs, potentially enabling reconciliations between usage-based and generative accounts.
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Rebecca Saxe @rebeccasaxe.bsky.social · 18/05/2026
Congratulations to @olaozpal.bsky.social & big team on new paper: large sample of children reveals the early origins of left-lateralization in language processing. Nice profile in MIT news: news.mit.edu/2026/languag...
news.mit.edu
Language development in the brain
The brain’s capacity to use and understand language expands rapidly in the first years of life. But by age 4, language processing is already handled by the left side of the brain, as in adults, accord...
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Daniel Lakens @lakens.bsky.social · 18/05/2026
New interactive simulation in my online textbook illustrating publication bias in meta-analyses, and some techniques to model bias-adjusted effect sizes. None of these work perfectly. We need an unbiased literature to draw valid inferences. lakens.github.io/statistical_...
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Mike Frank @mcxfrank.bsky.social · 18/05/2026
What is a psychological theory? Here's our take on this tricky and controversial question in this week's Experimentology chapter summary. Many things called "theories" in psychology aren't actually theories — they're frameworks. 🧵 experimentology.io
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Xinchi Yu @xinchiyu.bsky.social · 13/05/2026
Excited to share our (w/ @smancha.bsky.social ) latest work, where we offered some EEG evidence suggesting that morphology and syntax might not be that different in language comprehension, capitalizing on some interesting properties of Mandarin Chinese. onlinelibrary.wiley.com/doi/10.1111/...
onlinelibrary.wiley.com
Shared Neural Computations for Syntactic and Morphological Structures: Evidence From Mandarin Chinese
Although psycho-/neuro-linguistics has assumed a distinction between morphological and syntactic structure building as in traditional theoretical linguistics, this distinction has been increasingly c...
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Ev Fedorenko @evfedorenko.bsky.social · 20/04/2026
Remember Chomsky's arguments about language innateness based on its putative un-learnability? Those arguments hinge on a pretty crazy theory of grammar. Here is Ted Gibson's summary of the original claims and a proposed solution in the form of dependency grammar: tinyurl.com/yzjrpbb8
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Rob Mok @robmok.bsky.social · 14/04/2026
Excited to share our new preprint: "Do Machines Fail Like Humans? A Human-Centered Out-of-Distribution Spectrum for Mapping Error Alignment" led by @binxia.bsky.social w @ken-lxl.bsky.social & co-senior author Luke Dickens (UCL) 🤖🧵👇 Link: arxiv.org/abs/2603.07462 🧠📈#PsychSciSky #compneuro #mlsky /1
arxiv.org
Do Machines Fail Like Humans? A Human-Centred Out-of-Distribution Spectrum for Mapping Error Alignment
Determining whether AI systems process information similarly to humans is central to cognitive science and trustworthy AI. While modern AI models can match human accuracy on standard tasks, such parit...
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tweety fish oh wow like a chimera or something spoooky @sifu.tweety.fish · 06/03/2026
@kjhealy.co has a new version of his data visualization book coming out and 1) you’d be a fool not to get it especially if you do R stuff 2) it’s gonna be even more beautiful than the first one, which is truly lovely book 3) he put the ENTIRE content on his website for free, you lucky so-and-so
socviz.co
Data Visualization
A Practical Introduction
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Adele Goldberg @adelegoldberg.bsky.social · 27/02/2026
Idan Blank (UCLA, psych) makes the complex intuitive if you want to learn how LLMs work, watch👇 newly posted to YouTube (no ads) www.youtube.com/watch?v=cGMn...
youtu.be
How Transformers Work: A Detailed, Conceptual Explanation (No Coding / Math)
YouTube video by IbanDlank
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Matt Goldrick @mattgoldrick.bsky.social · 11/02/2026
Out today! "How Does a Deep Neural Network Look at Lexical Stress in English Words?" w/ I. Allouche, I. Asael, R. Rousso, V. Dassa, A. Bradlow, S.-E. Kim & @keshet.bsky.social doi.org/10.1121/10.0... 1/
doi.org
How does a deep neural network look at lexical stress in English words?
Despite their success in speech processing, neural networks often operate as black boxes, prompting the following questions: What informs their decisions, and h
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Kathy Rastle @kathyrastle.bsky.social · 05/02/2026
**New** chapter on “Literacy” just published in the Open Encyclopaedia of Cognitive Science. The whole series is super, accessible chapters and no paywalls, a great resource for teaching. oecs.mit.edu/pub/epclh9no...
oecs.mit.edu
Literacy
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Max Planck Institute for Psycholinguistics @mpi-nl.bsky.social · 11/02/2026
The elusive lemma: On the representation of grammatical information in the mental lexicon. New paper by Antje Meyer. doi.org/10.1080/2327....
doi.org
The elusive lemma: on the representation of syntactic information in the mental lexicon
According to Levelt, W. J., Roelofs, A., and Meyer, A. S. [(1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22(1), 1–38.] theory of lexical access, word produ...
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Cognition @cognitionjournal.bsky.social · 25/11/2025
1/10 A new paper by shirilevari.bsky.social shows that sound symbolism highlights the properties that distinguish referents from their competitors: www.sciencedirect.com/science/arti... A🧵
sciencedirect.com
Sound symbolism highlights relative distinctiveness: Evidence from English vocabulary
There is robust evidence that people associate certain sounds with meanings, yet the prevalence and importance of sound symbolism in natural language …
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Cognition @cognitionjournal.bsky.social · 21/11/2025
New in Cognition: In politics, people are not always truth seekers. Often, we reach conclusions because they fit with preferred narratives: we are biased by ideological motivations. Are some people better equipped to overcome such bias than others?
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Royal Holloway Psychology @rhulpsychology.bsky.social · 13/11/2025
Postdoctoral teaching associates: Two full-time posts, one permanent, one for 12 months jobs.royalholloway.ac.uk/vacancy.aspx...
jobs.royalholloway.ac.uk
Job Opportunity at Royal Holloway University of London: Postdoctoral Teaching Associate
Full-Time, Permanent/Fixed-Term - One permanent appointment and one 12-month appointmentApplications are invited for a Post-Doctoral Teaching Associate post in the Department of Psychology, Royal Holl...
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Benjamin Gagl @benjamingagl.bsky.social · 13/11/2025
🚨Now out in *Open Mind* 🚨 "Can we utilize Large Language Models (LLMs) to generate useful linguistic corpora? A case study of the word frequency effect in young German readers" direct.mit.edu/opmi/article... with @jobschepens.bsky.social @hannawoloszyn.bsky.social @nicolekmarx.bsky.social
direct.mit.edu
Can Large Language Models Generate Useful Linguistic Corpora?: A Case Study of the Word Frequency Effect in Young German Readers
Abstract. Linguistic corpora are an essential resource in psycholinguistic research. Here, we generate new corpora using large language models (LLMs) and determine their usefulness for estimating the ...
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The Experimental Psychology Society @exppsychsoc.bsky.social · 10/11/2025
We are pleased to announce a call for papers for a QJEP special issue: New Perspectives on the Mental Lexicon, guest edited by Jo Taylor, Kathy Rastle and Matthew Mak. Expressions of interest are due by 20th December 2025. Further details can be found here: journals.sagepub.com/pb-assets/PD...
journals.sagepub.com
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ERCbravenewword @ercbravenewword.bsky.social · 03/11/2025
For those who couldn't attend, the recording of Hsieh Cheng-Yu's seminar is now available on our YouTube channel. Watch the full presentation here: youtu.be/v7DHox_6duE
youtu.be
Making sense from the parts: What Chinese compounds tell us about reading | Cheng-Yu Hsieh | Milan
YouTube video by Mbs Vector Space Lab
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Cheng-Yu Hsieh @cyhsieh.bsky.social · 03/11/2025
The talk I gave in Milan is now on YouTube!
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Royal Holloway Psychology @rhulpsychology.bsky.social · 03/11/2025
🚨We are looking for a scholar to join us as a lecturer (teaching & research contract, full-time, permanent), starting 1 April 2026! The application deadline is 1 December 2025. jobs.royalholloway.ac.uk/Vacancy.aspx...
jobs.royalholloway.ac.uk
Job Opportunity at Royal Holloway University of London: Lecturer in Psychology (Research & Teaching)
Full-time, PermanentApplications are invited for a post of Lecturer in the Department of Psychology, Royal Holloway, University of London, starting 1 April 2026. The post is open to ambitious, researc...
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Matthew Mak @matthewmakpsy.bsky.social · 24/10/2025
I am guest editing a special issue—"New Perspectives on the Mental Lexicon" in @qjep.bsky.social with @kathyrastle.bsky.social and Jo Taylor. Expression of interest until 20th Dec. Get in touch!
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Cheng-Yu Hsieh @cyhsieh.bsky.social · 20/10/2025
Another talk next week!
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Cheng-Yu Hsieh @cyhsieh.bsky.social · 20/10/2025
Thanks for having me. It was lovely meeting you all online! If you missed it today, I’m giving another talk next Monday in Italy (it’ll be hybrid).
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German Word Nerd Network @gewonnofficial.bsky.social · 15/10/2025
Join our journal club next Monday! We're happy to have @cyhsieh.bsky.social to discuss "What Chinese Compounds Tell Us About Reading"! Scan the QR code to register or click here: forms.gle/JV5cp1RHHaH2...
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Michael Beyeler @mbeyeler.bsky.social · 27/09/2025
👁️🧠 New preprint: We demonstrate the first data-driven neural control framework for a visual cortical implant in a blind human! TL;DR Deep learning lets us synthesize efficient stimulation patterns that reliably evoke percepts, outperforming conventional calibration. www.biorxiv.org/content/10.1...
Diagram showing three ways to control brain activity with a visual prosthesis. The goal is to match a desired pattern of brain responses. One method uses a simple one-to-one mapping, another uses an inverse neural network, and a third uses gradient optimization. Each method produces a stimulation pattern, which is tested in both computer simulations and in the brain of a blind participant with an implant. The figure shows that the neural network and gradient methods reproduce the target brain activity more accurately than the simple mapping.
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Cheng-Yu Hsieh @cyhsieh.bsky.social · 02/10/2025
Thanks for the invite. Looking forward to seeing many of you online!
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Aidan Horner @aidanhorner.bsky.social · 21/07/2025
2 Lecturer (Assistant Prof) positions available @yorkpsychology.bsky.social! Come join our department! #neuroskyence #cognition #psychscisky #neurojobs jobs.york.ac.uk/vacancy/lect...
jobs.york.ac.uk
Jobs - The University of York
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Rob Mok @robmok.bsky.social · 18/07/2025
JOB ALERT: Computational Cognitive Neuroscience Postdoc position in Osaka, Japan! Possible start in October 2025 (contact me ASAP), or from April 2026. PLEASE REPOST! #postdocjobs #neuroskyence #neuroscience #psychscisky #compneurosky #neurojobs 1/
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Morten H. Christiansen @mh-christiansen.bsky.social · 18/07/2025
📣 Save the date 🗓️ to present your exciting statistical learning research at the 6th Interdisciplinary Advances in Statistical Learning Conference June 10-12 2026 in San Sebastián 🇪🇸 Keynotes by @jennysaffran.bsky.social @noranewcombe.bsky.social @pyoudeyer.bsky.social More info to follow #IASL26
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Marco Ciapparelli @marcociapparelli.bsky.social · 18/07/2025
I'm sharing a Colab notebook on using large language models for cognitive science! GitHub repo: github.com/MarcoCiappar... It's geared toward psychologists & linguists and covers extracting embeddings, predictability measures, comparing models across languages & modalities (vision). see examples 🧵
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Jamie Reilly 🦜 @reilly-coglab.com · 20/05/2025
Updated our lab's psycholinguistic database page to include Kathy Rastle et al's new web interface for the Children and Young Peoples Books Lexicon (CYP-LEX). Check it out! Give me a holler if you want us to link to your dataset or know of others I've missed. www.reilly-coglab.com/data
reilly-coglab.com
Psycholinguistic Databases, Stimuli, Utilities — Concepts & Cognition Laboratory
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Kathy Rastle @kathyrastle.bsky.social · 20/05/2025
** New resource ** We analysed the characteristics of words in 1200 books suitable for children and young people. Properties of each word (frequencies, etc) are now available in an interactive website. cyp-lex.rastlelab.com
cyp-lex.rastlelab.com
CYP-LEX
Discover what words children and young people encounter when they read
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Kathy Rastle @kathyrastle.bsky.social · 20/05/2025
What can children learn about morphology when they read for pleasure? We analysed the words in 1200 books suitable for children and young people to find out! Read the blog post here: www.rastlelab.com/post/what-ca...
rastlelab.com
What can children learn about morphology from reading for fun?
A key part of becoming a skilled reader is understanding how words are built — that is, how small parts of words that carry meaning come together to form words. For example, the word unhappy is made u...
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