How is AI changing the literacy landscape?

AI tools are no longer experimental add-ons; they’re steadily becoming embedded in everyday teaching and learning. The Department for Education (DfE) in the UK recently published a set of support materials to help schools and colleges use generative AI safely, ethically and effectively. DfE's list of support materials can be reviewed here.

These materials, created by the Chiltern Learning Trust (CLT) and Chartered College of Teaching (CCT), are structured as modules covering:

Understanding what AI is and how it works in an educational context
Interacting with generative AI (i.e. practical use)
Safe use - including ethical / safeguarding considerations
Real-world use cases of AI in education

In fact, this week, the government has issued Generative AI: Product Safety Standards guidance that sets out safety and quality standards that generative AI products must meet for use in educational settings, focusing on protecting learners from harmful content and ensuring responsible design, data protection, security, and transparency. The guidance also aims to help edtech developers and suppliers clarify product purpose and embed safeguards against risks (e.g., inappropriate content, misuse, cognitive harm). It will also endeavour to support schools and colleges in assessing safe AI tools.

AI Use Among Students and Teachers

Generative AI use among 13–18 year-olds surged from 37% in 2023 to 77% in 2024 (NLT study).

Students use it for schoolwork (writing stories, non-fiction) and general help (coming up with ideas, understanding concepts). Nearly half of students adapt AI output, and 40% check accuracy and look for errors. Worryingly though, 20% admit to simply copying AI text without checking.

Teacher use also rose (31% to 48% in 2024), mainly for generating model writing, quizzes, and summarising texts. However, about half of teachers fear AI could harm students' writing skills, and most agree students need critical AI training.

Opportunities vs Risks

Opportunities:

Engagement & Creativity: AI helps overcome 'blank page syndrome' for enthusiastic writers and facilitates experimentation.
Struggling Learners: AI offers feedback and scaffolding, lowering the barrier to entry for those who lack confidence.
Teacher Support: AI saves time on lesson planning, allowing for more personalised and differentiated teaching, as well as meaningful interaction.

Risks:

Uncritical Copying & Skill Loss: 1 in 5 young people copy AI text unchecked, risking underdeveloped critical thinking and weaker writing skills.
Over-reliance: AI may foster dependence rather than autonomy, especially when students lack other support.
Teacher Concerns: Many teachers worry about AI devaluing writing and reading skills.
Safety & Ethics: DfE guidance stresses safe use to mitigate risks like academic dishonesty and exposure to harmful content.

Study - Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task

The concerns of skill loss and over-reliance are compounded by a recent study looking at the use of AI and the effect on brain activity, comparing three modes of essay writing - one group using a large language model (LLM) assistant, a second group using a search engine, and the third group working “brain-only” (no external tools).

Participants wrote multiple essays over several sessions while researchers measured brain activity using EEG, analysed writing patterns, and assessed essays via human and AI evaluators. The study found that neural engagement, reflected in brain connectivity, was highest in the brain-only group, moderate in the search-engine group, and lowest in the LLM-assisted group. Essays created with the LLM showed less variety in linguistic patterns and topic usage compared to other groups, and participants reported the lowest sense of ownership over their work when using the LLM.

Moreover, when some participants switched from LLM use to brain-only writing in a later session, their brain connectivity did not rebound, suggesting a persistent under-engagement effect. Meanwhile those who switched from brain-only to LLM-assisted regained engagement levels akin to search-engine users. The authors argue these findings reveal a risk of “cognitive debt” - a weakening of mental effort, independent thinking and creative variation, when people rely on AI assistants for writing tasks. Over time, this could have adverse implications for learning, creativity, and critical thinking.

This is where Inspiration Flow's gentle reliance on AI will help students - rather than over-relying on AI, the way AI is delicately woven into the student's workflow means it doesn't do the work for you, nor does it do the thinking for you. Instead, Inspiration Flow turns AI-generated output into a map to support your learning, to encourage you to work from the basics it gives you - to turn a rudimentary diagram into more, into an outline for the start of an essay structure, or into a revision aid. This kind of assistance means your brain is still working hard and will retain its full capacity, thus not leading to 'cognitive decline'.

The Evolving Definition of "Literacy"

Literacy now includes:

Prompt literacy: Asking AI effective questions.
Critical AI literacy: Evaluating and adapting AI outputs.
Digital-first practices: Blending human and machine writing and reading.
School Response: Schools must provide structured training (like DfE modules), incorporate critical AI literacy teaching, encourage balanced use (AI as support, not replacement), and monitor vulnerable pupils.

Final Thoughts...

Generative AI offers students creativity and convenience, and it offers teachers opportunities to redesign learning. However, risks like over-reliance and skill loss are significant. The future of literacy depends on careful guidance, critical thinking, and balanced use to ensure AI enhances rather than weakens core human skills.