LLMs are Biased Teachers: Evaluating LLM Bias in Personalized Education

The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance

Milton Friedman. 1937 · 1937

Earlier work this paper cites.

A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings

Milton Friedman. 1940 · 1940

Earlier work this paper cites.

The Technique of Clear Writing

Robert Gunning. 1952 · 1952

Earlier work this paper cites.

A computer readability formula designed for machine scoring

Meri Coleman and T. L. Liau. 1975 · 1975

Earlier work this paper cites.

Derivation Of New Readability Formulas (Automated Readability Index, Fog Count And Flesch Reading Ease Formula) For Navy Enlisted Personnel

J. Kincaid, Robert Fishburne, Richard Rogers, and Brad Chissom. 1975 · 1975

Earlier work this paper cites.

Mind in society: the development of higher psychological processes , nachdr. edition

Lev Semenovič Vygotskij and Michael Cole. 1981 · 1981

Earlier work this paper cites.

“Without handicap”: issues of medical schools and physically disabled students

M J Reichgott. 1996 · 1996

Earlier work this paper cites.

Situated Cognition, Vygotskian Thought and Learning from the Communities of Practice Perspective: Implications for the Design of Web-Based E-Learning

David W L Hung and Der-Thanq Chen. 2001 · 2001

Earlier work this paper cites.

School, Studying, and Smarts: Gender Stereotypes and Education Across 80 Years of American Print Media, 1930–2009

Andrei Boutyline, Alina Arseniev-Koehler, and Devin J Cornell. 2023 · 2009

Earlier work this paper cites.

Flow: The psychology of optimal experience , nachdr. edition

Mihaly Csikszentmihalyi. 2009 · 2009

Earlier work this paper cites.

Evidence for the social role theory of stereotype content: Observations of groups’ roles shape stereotypes

Anne M. Koenig and Alice H. Eagly. 2014 · 2014

Earlier work this paper cites.

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings

Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai. 2016 · 2016

Earlier work this paper cites.

Gender stereotypes about intellectual ability emerge early and influence children’s interests

Lin Bian, Sarah-Jane Leslie, and Andrei Cimpian. 2017 · 2017

Earlier work this paper cites.

Semantics derived automatically from language corpora contain human-like biases

Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan. 2017 · 2017

Earlier work this paper cites.

Algorithmic Bias in Autonomous Systems

David Danks and Alex John London. 2017 · 2017

Earlier work this paper cites.

If they think I can: Teacher bias and youth of color expectations and achievement

Hua-Yu Sebastian Cherng. 2017 · 2017

Earlier work this paper cites.

Gender bias in coreference resolution

Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018

Earlier work this paper cites.

Assessing the Fairness of Graduation Predictions

Henry Anderson, Afshan Boodhwani, and Ryan S Baker. 2019 · 2019

Earlier work this paper cites.

Examining Americans’ Stereotypes about Immigrant Illegality

René D. Flores and Ariela Schachter. 2019 · 2019

Earlier work this paper cites.

On Measuring and Mitigating Biased Inferences of Word Embeddings

Sunipa Dev, Tao Li, Jeff M. Phillips, and Vivek Srikumar. 2020 · 2020

Earlier work this paper cites.

Unintended machine learning biases as social barriers for persons with disabilitiess

Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020 · 2020

Earlier work this paper cites.

UNQOVERing stereotyping biases via underspecified questions

Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, and Vivek Srikumar. 2020 · 2020

Earlier work this paper cites.

Using Assessment to Improve the Accuracy of Teachers’ Perceptions of Students’ Academic Competence

Brandy Gatlin-Nash, Jin Kyoung Hwang, Novell E. Tani, Elham Zargar, Taffeta Star Wood, Dandan Yang, Khamia B. Powell, and Carol McDonald Connor. 2021 · 2021

Earlier work this paper cites.

Measuring Mathematical Problem Solving With the MATH Dataset

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

Earlier work this paper cites.

Uncovering implicit gender bias in narratives through commonsense inference

Tenghao Huang, Faeze Brahman, Vered Shwartz, and Snigdha Chaturvedi. 2021 · 2021

Earlier work this paper cites.

A Survey on Bias and Fairness in Machine Learning

Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan. 2021 · 2021

Earlier work this paper cites.

StereoSet: Measuring stereotypical bias in pretrained language models

Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021

Cited alongside, same era.

Artificial intelligence in education: Addressing ethical challenges in K-12 settings

Selin Akgun and Christine Greenhow. 2022 · 2022

Cited alongside, same era.

A Survey of Bias in Machine Learning Through the Prism of Statistical Parity

Philippe Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes, and Laurent Risser. 2022 · 2022

Cited alongside, same era.

On the Opportunities and Risks of Foundation Models

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, and Percy Liang. 2022 · 2022

From Persona to Personalization: A Survey on Role-Playing Language Agents

Original

Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan, Yikai Zhang, Wei Shi, Jian Xie, Shuang Li, Ruihan Yang, Tinghui Zhu, Aili Chen, Nianqi Li, Lida Chen, Caiyu Hu, Siye Wu, Scott Ren, Ziquan Fu, and Yanghua Xiao. 2024 · 2024

Closest in time.

Impact of AI assistance on student agency

Ali Darvishi, Hassan Khosravi, Shazia Sadiq, Dragan Gašević, and George Siemens. 2024 · 2024

Closest in time.

I Am Not Them: Fluid Identities and Persistent Out-group Bias in Large Language Models

Original

Wenchao Dong, Assem Zhunis, Hyojin Chin, Jiyoung Han, and Meeyoung Cha. 2024 · 2024

Closest in time.

From Melting Pots to Misrepresentations: Exploring Harms in Generative AI

Original

Sanjana Gautam, Pranav Narayanan Venkit, and Sourojit Ghosh. 2024 · 2024

Closest in time.

What’s in a Name? Auditing Large Language Models for Race and Gender Bias