Copertina

"Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in Education

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Harvey, Emma, Koenecke, Allison, Kizilcec, Rene F.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computers and Society
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Framework for Auditing Chatbots for Dialect-Based Quality-of-Service Harms
di: Harvey, Emma, et al.
Pubblicazione: (2025)

The Life Cycle of Large Language Models: A Review of Biases in Education
di: Lee, Jinsook, et al.
Pubblicazione: (2024)

Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese
di: Lyu, Hanjia, et al.
Pubblicazione: (2025)

Hey, Teacher, (Don't) Leave Those Kids Alone: Standardizing HRI Education
di: Block, Alexis E.
Pubblicazione: (2024)

Into the Unknown: Accounting for Missing Demographic Data when Mitigating Ad Delivery Skew
di: Corpus, Isabel, et al.
Pubblicazione: (2026)

Modernizing Ground Truth: Four Shifts Toward Improving Reliability and Validity in AI in Education
di: Thomas, Danielle R., et al.
Pubblicazione: (2026)

Careless Whisper: Speech-to-Text Hallucination Harms
di: Koenecke, Allison, et al.
Pubblicazione: (2024)

Algorithms for College Admissions Decision Support: Impacts of Policy Change and Inherent Variability
di: Lee, Jinsook, et al.
Pubblicazione: (2024)

The Digital Divide in Generative AI: Evidence from Large Language Model Use in College Admissions Essays
di: Lee, Jinsook, et al.
Pubblicazione: (2026)

A Critical Pragmatism Approach for Algorithmic Fairness: Lessons from Urban Planning Theory
di: Gosciak, Jennah, et al.
Pubblicazione: (2026)

Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems
di: Yan, Jing Nathan, et al.
Pubblicazione: (2025)

How well do Large Language Models Recognize Instructional Moves? Establishing Baselines for Foundation Models in Educational Discourse
di: Vanacore, Kirk, et al.
Pubblicazione: (2025)

What Explains Teachers' Trust of AI in Education across Six Countries?
di: Viberg, Olga, et al.
Pubblicazione: (2023)

Investigating Student Interaction Patterns with Large Language Model-Powered Course Assistants in Computer Science Courses
di: Liu, Chang, et al.
Pubblicazione: (2025)

Teachers' Perceived Benefits and Risks of AI Across Fifty-Five Countries: An Audit of LLM Alignment and Steerability
di: Tao, Yan, et al.
Pubblicazione: (2026)

Who Decides in AI-Mediated Learning? The Agency Allocation Framework
di: Borchers, Conrad, et al.
Pubblicazione: (2026)

Reflection on Purpose Changes Students' Academic Interests: A Scalable Intervention in an Online Course Catalog
di: Chen, Youjie, et al.
Pubblicazione: (2024)

Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes
di: Corpus, Isabel, et al.
Pubblicazione: (2025)

Scrutinizing Index-Based Risk Assessments: A Case Study in NYC Decision-making for Heat Emergency Management
di: Gosciak, Jennah, et al.
Pubblicazione: (2026)

Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations
di: Anand, Abhishek, et al.
Pubblicazione: (2024)

Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems
di: Harvey, Emma, et al.
Pubblicazione: (2025)

Does Algorithmic Uncertainty Sway Human Experts? Evidence from a Field Experiment in Selective College Admissions
di: Lee, Hansol, et al.
Pubblicazione: (2026)

The "Huh?" Button: Improving Understanding in Educational Videos with Large Language Models
di: Ruf, Boris, et al.
Pubblicazione: (2024)

Understanding Teacher Revisions of Large Language Model-Generated Feedback
di: Borchers, Conrad, et al.
Pubblicazione: (2026)

You Don't Have to Live Next to Me: Towards Demobilizing Individualistic Bias in Computational Approaches to Urban Segregation
di: Vybornova, Anastassia, et al.
Pubblicazione: (2025)

A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training
di: Precel, Heila, et al.
Pubblicazione: (2024)

LLMs in social services: How does chatbot accuracy affect human accuracy?
di: Gosciak, Jennah, et al.
Pubblicazione: (2026)

When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts
di: Yao, Chengyuan, et al.
Pubblicazione: (2025)

Don't Kill the Baby: The Case for AI in Arbitration
di: Broyde, Michael, et al.
Pubblicazione: (2024)

Don't Forget Imagination!
di: Vityaev, Evgenii E., et al.
Pubblicazione: (2025)

Shiksha Copilot: Teacher-AI Collaboration for Curating and Customizing Lesson Plans in Low-Resource Schools
di: Dennison, Deepak Varuvel, et al.
Pubblicazione: (2025)

Rethinking Digitalization and Climate: Don't Predict, Mitigate
di: Gritsenko, Daria, et al.
Pubblicazione: (2024)

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments
di: Gosciak, Jennah, et al.
Pubblicazione: (2025)

Position: Measure Dataset Diversity, Don't Just Claim It
di: Zhao, Dora, et al.
Pubblicazione: (2024)

Advancing Global South University Education with Large Language Models
di: L, Kemas Muslim, et al.
Pubblicazione: (2024)

The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education?
di: Chan, Cecilia Ka Yuk, et al.
Pubblicazione: (2023)

Large Language Models for Education: A Survey
di: Xu, Hanyi, et al.
Pubblicazione: (2024)

Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems
di: Harvey, Emma, et al.
Pubblicazione: (2024)

"What Is It That You Don't Understand?" Language Games and Black Box Algorithms
di: Demichelis, Remy
Pubblicazione: (2026)

MedSimAI: Simulation and Formative Feedback Generation to Enhance Deliberate Practice in Medical Education
di: Hicke, Yann, et al.
Pubblicazione: (2025)