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A good teacher should not only be knowledgeable, but should also be able to communicate in a way that the student understands -- to share the student's representation of the world.
Logic and conversation
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Processing and using information about students: A study of expert, novice, and postulant teachers
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Bothered by abstraction: the effect of expertise on knowledge transfer and subsequent novice performance
Pamela J Hinds, Michael Patterson, and Jeffrey Pfeffer · 2001
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Jennifer King Rice · 2003
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Teachers, race, and student achievement in a randomized experiment
Thomas S Dee · 2004
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Twelve-month-olds communicate helpfully and appropriately for knowledgeable and ignorant partners
Ulf Liszkowski, Malinda Carpenter, and Michael Tomasello · 2008
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Natural pedagogy
Gergely Csibra and György Gergely · 2009
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Elizabeth Bonawitz, Patrick Shafto, Hyowon Gweon, Noah D Goodman, Elizabeth Spelke, and Laura Schulz · 2011
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Michael Frank · 2014
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Disruptor, distracter, or what? a policymaker’s guide to massive open online courses (MOOCs)
Andrew P Kelly · 2014
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Effectiveness of cognitive tutor algebra I at scale
John F Pane, Beth Ann Griffin, Daniel F McCaffrey, and Rita Karam · 2014
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A rational account of pedagogical reasoning: Teaching by, and learning from, examples
Patrick Shafto, Noah D Goodman, and Thomas L Griffiths · 2014
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Representation in the classroom: The effect of own-race teachers on student achievement
Anna J. Egalite, Brian Kisida, and Marcus A. Winters · 2015
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Machine teaching: An inverse problem to machine learning and an approach toward optimal education
Xiaojin Zhu · 2015
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Reasoning about pragmatics with neural listeners and speakers
Jacob Andreas and Dan Klein · 2016
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Pragmatic language interpretation as probabilistic inference
Noah D Goodman and Michael C Frank · 2016
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Showing versus doing: Teaching by demonstration
Mark K Ho, Michael Littman, James MacGlashan, Fiery Cushman, and Joseph L Austerweil · 2016
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The teaching dimension of linear learners
Ji Liu and Xiaojin Zhu · 2016
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Learning language games through interaction
Sida I Wang, Percy Liang, and Christopher D Manning · 2016
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Iterative machine teaching
Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B Smith, James M Rehg, and Le Song · 2017
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Speaker-follower models for vision-and-language navigation
Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, and Trevor Darrell · 2018
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The role of the community in teacher preparation: Exploring a different pathway to becoming a teacher
G Harfitt · 2018
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Towards black-box iterative machine teaching
Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, and Le Song · 2018
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Teacher Improves Learning by Selecting a Training Subset
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, and Xiaojin Zhu · 2018
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Prolific.ac—A subject pool for online experiments
Stefan Palan and Christian Schitter · 2018
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How to talk so AI will learn: Instructions, descriptions, and autonomy
Theodore Sumers, Robert Hawkins, Mark K Ho, Tom Griffiths, and Dylan Hadfield-Menell · 2022
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When naive pedagogy breaks down: Adults rationally decide how to teach, but misrepresent learners’ beliefs
Rosie Aboody, Joey Velez-Ginorio, Laurie R Santos, and Julian Jara-Ettinger · 2023
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Improving the robustness of NLI models with minimax training
Michalis Korakakis and Andreas Vlachos · 2023
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Dimensions of disagreement: Unpacking divergence and misalignment in cognitive science and artificial intelligence, 2023
Kerem Oktar, Ilia Sucholutsky, Tania Lombrozo, and Thomas L. Griffiths · 2023
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Iterative teaching by data hallucination
Zeju Qiu, Weiyang Liu, Tim Z Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, and Bernhard Schölkopf · 2023
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Xiaojin Zhu, Adish Singla, Sandra Zilles, and Anna N Rafferty · 2018
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An optimal control approach to sequential machine teaching
Laurent Lessard, Xuezhou Zhang, and Xiaojin Zhu · 2019
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The MOOC pivot
Justin Reich and José A Ruipérez-Valiente · 2019
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Iterative classroom teaching
Teresa Yeo, Parameswaran Kamalaruban, Adish Singla, Arpit Merchant, Thibault Asselborn, Louis Faucon, Pierre Dillenbourg, and Volkan Cevher · 2019
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Young children consider the expected utility of others’ learning to decide what to teach
Sophie Bridgers, Julian Jara-Ettinger, and Hyowon Gweon · 2020
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Mining big data in education: Affordances and challenges
Christian Fischer, Zachary A. Pardos, Ryan Shaun Baker, Joseph Jay Williams, Padhraic Smyth, Renzhe Yu, Stefan Slater, Rachel Baker, and Mark Warschauer · 2020
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Literal or pedagogic human? analyzing human model misspecification in objective learning
Smitha Milli and Anca D Dragan · 2020
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Sunayana Rane, Mark Ho, Ilia Sucholutsky, and Thomas L Griffiths · 2023
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Testing theory of mind in GPT models and humans
James Strachan, Dalila Albergo, Giulia Borghini, Oriana Pansardi, Eugenio Scaliti, Alessandro Rufo, Guido Manzi, Michael Graziano, and Cristina Becchio · 2023
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Alignment with human representations supports robust few-shot learning
Ilia Sucholutsky and Thomas L Griffiths · 2023
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Show or Tell? Exploring when (and why) teaching with language outperforms demonstration
Theodore R Sumers, Mark K Ho, Robert D Hawkins, and Thomas L Griffiths · 2023
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Teachers recruit mentalizing regions to represent learners’ beliefs
Natalia Vélez, Alicia M Chen, Taylor Burke, Fiery A Cushman, and Samuel J Gershman · 2023
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Examining the applications of intelligent tutoring systems in real educational contexts: A systematic literature review from the social experiment perspective
Huanhuan Wang, Ahmed Tlili, Ronghuai Huang, Zhenyu Cai, Min Li, Zui Cheng, Dong Yang, Mengti Li, Xixian Zhu, and Cheng Fei · 2023
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Learning human-like representations to enable learning human values
Andrea Wynn, Ilia Sucholutsky, and Thomas L Griffiths · 2023
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Nonparametric iterative machine teaching
Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor Tsang, and James Kwok · 2023
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Building machines that learn and think with people
Katherine M Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E Zhang, Tan Zhi-Xuan, Mark Ho, Vikash Mansinghka, et al · 2024
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Dun-Ming Huang, Pol Van Rijn, Ilia Sucholutsky, Raja Marjieh, and Nori Jacoby · 2024
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Large language models assume people are more rational than we really are
Ryan Liu, Jiayi Geng, Joshua C Peterson, Ilia Sucholutsky, and Thomas L Griffiths · 2024
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Studying the Effect of Globalization on Color Perception using Multilingual Online Recruitment and Large Language Models, Feb 2024
Jakob Niedermann, Ilia Sucholutsky, Raja Marjieh, Elif Celen, Thomas L Griffiths, Nori Jacoby, and Pol van Rijn · 2024
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URL https://news.ontario.ca/en/backgrounder/1004649/modern-relevant-and-skills-focused-a-stronger-ontario-high-school-diploma
Ontario, May 2024 · 2024
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Large language models approach expert-level clinical knowledge and reasoning in ophthalmology: A head-to-head cross-sectional study
Arun James Thirunavukarasu, Shathar Mahmood, Andrew Malem, William Paul Foster, Rohan Sanghera, Refaat Hassan, Sean Zhou, Shiao Wei Wong, Yee Ling Wong, Yu Jeat Chong, Abdullah Shakeel, Yin-Hsi Chang, Benjamin Kye Jyn Tan, Nikhil Jain, Ting Fang Tan, Saaeha Rauz, Daniel Shu Wei Ting, and Darren Shu Jeng Ting · 2024
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Tutor copilot: A human-ai approach for scaling real-time expertise
Rose E Wang, Ana T Ribeiro, Carly D Robinson, Susanna Loeb, and Dora Demszky · 2024
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Pragmatic instruction following and goal assistance via cooperative language-guided inverse planning, 2024
Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka, and Joshua B. Tenenbaum · 2024
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On the informativeness of supervision signals
Ilia Sucholutsky, Ruairidh M Battleday, Katherine M Collins, Raja Marjieh, Joshua Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, and Thomas L Griffiths · 2046
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