How inclusive large language models can be? The curious case of pragmatics
Key Takeaways
- •This research highlights a critical challenge for AI in education: ensuring Large Language Models genuinely understand the nuanced pragmatics essential for inclusive learning, particularly for students with Special Educational Needs.
- •This aligns with the broader push for ethical AI development, necessitating that educators critically assess LLM capabilities while developers prioritize context-aware model design to foster truly equitable EdTech solutions.
REVIEW article Front. Educ. , 21 November 2025 Sec. Special Educational Needs Volume 10 - 2025 | https://doi.org/10.3389/feduc.2025.1619662 How inclusive large language models can be? The curious case of pragmatics M M Martina Manna 1 * M E Maka Eradze 1 F C Federica Cominetti 2 1. Department of Human Studies, The University of L’Aquila, L’Aquila, Italy 2. Department of Human Studies, The University of Milano-Bicocca, Milan, Italy Article metrics View details Abstract This article provides a conceptual and critical
Our Take
This research highlights a critical challenge for AI in education: ensuring Large Language Models genuinely understand the nuanced pragmatics essential for inclusive learning, particularly for students with Special Educational Needs. This aligns with the broader push for ethical AI development, necessitating that educators critically assess LLM capabilities while developers prioritize context-aware model design to foster truly equitable EdTech solutions.
Topics & Tags
Analysis & Perspectives
Strategic Planning for AI Professional Development: Equipping Educators to Integrate AI as a Pedagogical Partner, Not Just a Tool
This article outlines a strategic framework for professional development, empowering educators to effectively integrate AI into their teaching practices. It moves beyond viewing AI as a mere tool, instead focusing on equipping educators to leverage AI as a sophisticated pedagogical partner. The aim is to enhance learning experiences and foster innovative instructional design.
Redefining Assessment and Feedback Strategies in the Age of Generative AI: From Plagiarism Detection to Promoting Critical AI Literacy
This article explores how the advent of generative AI necessitates a fundamental re-evaluation of assessment and feedback strategies in education. It advocates for a shift from solely focusing on plagiarism detection towards cultivating critical AI literacy among students. The piece outlines innovative approaches to integrate AI responsibly, ensuring academic integrity while equipping learners with essential skills for an AI-driven world.
People Also Ask
What is the best AI tool for students?▾
Is it cheating to use AI as a student?▾
How can AI help students learn more effectively?▾
Are there free AI tools for students?▾
Related Articles
Making AI chatbots friendly leads to mistakes and support of conspiracy theories
Skip to main content Skip to navigation Skip to navigation Warm chatbots are 30% less accurate and 40% more likely to support false beliefs, the study found. Photograph: Thai Liang Lim/Getty Images View image in fullscreen Warm chatbots are 30% less accurate and 40% more likely to support false beliefs, the study found. Photograph: Thai Liang Lim/Getty Images Friendly AI chatbots more likely to support conspiracy theories, study finds Chatbots programmed to respond warmly even cast doubts on Apollo moon
AI gives more praise, less criticism to Black students
Skip to content Credit: Getty Images The Hechinger Report covers one topic: education. Sign up for our newsletters to have stories delivered to your inbox. Consider becoming a member to support our nonprofit journalism. Get important education news and analysis delivered straight to your inbox Choose as many as you want (Required) Weekly Update Elementary to High School Higher Education Proof Points Climate Change Early Childhood Email (Required) Δ As schools introduce artificial intelligence into the classroom, a new analysis
Generative AI Makes Good Research Better, But Demands Human Discipline
Skip to main content Skip to search YU News Search Offset Search Offset News Channel YU News Featured News Faculty News Schools & Depts Alumni Katz Lieberman Revel Straus Sy Syms Wurzweiler Libraries News Press Releases Publications Contact Alumni Katz Lieberman Revel Straus Sy Syms Wurzweiler Libraries News Generative AI Makes Good Research Better, But Demands Human Discipline Apr 24, 2026 By: daviddefusco Sy Syms Assistant Professor Travis Oh is a co-author of the report: New Tools, New Roles: A