AI for Education Newsletter

AIEN Issue #37 - May 19th, 2025

Author

Thomas Bouwman
May 19, 2025 • Mental Processing Time: 6 minutes

News and Highlights

Summary: Facing a chronic recruitment shortfall, the U.K. must focus on retaining its current teachers—and the biggest lever, the column argues, is cutting the mountain of marking. Pilot projects using AI essay-scoring from firms such as No More Marking show that automated feedback can match human reliability while slashing hours of grading, freeing teachers for lesson planning and pupil support.

Key Takeaways

  • New National Audit Office data show England missed its trainee-teacher target by 6,500 staff last year; workload is the top driver of exits.

  • Early pilots report AI can assess writing “with 90 %+ agreement” versus human markers and return feedback in minutes.

  • Education Secretary Bridget Phillipson has earmarked £1 million to test AI marking at scale during the coming school year.

  • The author warns AI must remain a tool, not a replacement, to avoid deskilling teachers and eroding professional judgement.

Why It Matters for Teachers – If deployed responsibly, AI-assisted marking could hand back hours each week, easing burnout and letting educators spend more time on high-impact teaching and student relationships.

Summary: Scientists recorded activity from 7,400 intracranial electrodes in 46 French-speaking participants (ages 2 to 46) while they listened to The Little Prince. By comparing those neural patterns with representations inside modern speech and language models, the team mapped how low-level phonetics and higher-level word features appear and strengthen in the cortex from toddlerhood through adulthood. Their findings show striking parallels between the layer-by-layer progression of AI models and the step-by-step maturation of the human language network.

Key Takeaways

  • Phonetic awareness forms early: Even 2- to 5-year-olds already encode detailed speech sounds in the superior-temporal cortex, supporting early phonics instruction.

  • Word-level and semantic processing mature later: Higher-order language regions keep expanding through middle childhood, hinting that rich vocabulary and comprehension work should intensify after age 7.

  • AI layers mirror brain stages: Shallow layers of wav2vec 2.0 match children’s brains, while deeper layers align only with adult patterns—suggesting educators can use simpler AI-generated scaffolds for younger learners and more abstract prompts for older students.

  • AI as a “computational microscope”: The study validates large language models as tools for exploring—and potentially personalizing—language development, opening avenues for age-tuned AI tutors and diagnostics.

Why It Matters – Knowing which language features children’s brains can (and can’t) process at different ages can guide teachers in pacing phonics, vocabulary, and AI-assisted interventions, while underscoring how modern AI tools may align with learners’ developmental stages.

Noteworthy Reads

Summary: Duolingo CEO Luis von Ahn predicts a future where AI becomes a more effective and scalable teaching tool than traditional educators, potentially transforming schools into supervised childcare centers with teachers focusing on mentorship roles.

A new USF report, published May 19, describes a district–university partnership that pilots AI lessons in Tampa Bay classrooms while building teacher capacity and stressing data ethics. Researchers outline best practices—from co-designing projects with educators to teaching students how AI systems work—to ensure AI supports, rather than replaces, human judgment.

This article describes practical ways teachers can let students tap generative-AI tools during project-based learning units—using chatbots for brainstorming, drafting interview questions, and refining presentation scripts—without letting AI do the “heavy lifting” of creation. It includes classroom examples, teacher prompts, and cautions about verifying AI output.

AI Tools to Try

Gradescope is an AI-powered grading platform that streamlines the grading process for teachers. It allows teachers to create and grade assignments online, provide personalized feedback, and track student progress. It can handle various assessment formats including coding assignments.

Target Audience: Higher Education (primarily), K-12 (adaptable), Ages 14+

Snorkl – Snorkl lets students record quick voice-or-whiteboard explanations of their work (think “show your math”), then uses multimodal AI to give instant, targeted feedback while teachers get dashboards of misconceptions. Great for formative checks in STEM and language-learning classes.

Target Audience: Upper-Elementary through High School, Grades 3-12, ages 8-18 

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