For tutors & teachers
Guide for tutors and teachers
How to introduce the reflective-writing toolkit safely, set clear rules, protect the people students write about, and use AI feedback as part of learning rather than a shortcut around it.
What the toolkit can help with
Reflective writing is required across nursing, medicine, teaching, social work and higher education, but students are rarely taught how to reflect. The tools give structured, formative help: spotting where writing is still description, deepening a “so what”, applying a model such as Gibbs, turning a lesson into an action, and checking anonymity. The student does the reflecting; the tool coaches.
What it should not be used for
It must not be used to generate a reflection for a student to submit. The reflection’s value is that it is theirs — their experience, their feelings, their insight. The tools are built to refuse ghost-writing, but you should confirm that on your platform (see the deployment check) and make the expectation explicit to students.
Be careful with private and sensitive material
This matters more for reflection than for ordinary essays, because reflections describe real people — patients, service users, clients, colleagues, pupils. Before recommending any tool, tell students plainly: never paste anything that could identify a real person into an AI tool. Point them to the anonymisation guide and the NH4 / MD3 tools, and check your institution’s and regulator’s rules on AI use and confidentiality first.
Set clear rules before students use it
Decide and state, in writing, whether AI feedback is permitted for the specific assessment, what students must declare, and what records they should keep. Many courses now expect an AI-use statement; the toolkit’s approach (the student writes; AI questions) is easier to declare honestly than open-ended generation. Make the rule concrete: “you may use it to get feedback on your own draft; you may not use it to produce text you submit.”
How to introduce it to students
- Use it as a conversation starter. Run a tool live on an invented, anonymised passage so students see it diagnosing rather than rewriting.
- Recommend it for the whole life of a piece of work, from choosing an experience to checking anonymity — not just at the end.
- Start with low-stakes use, such as a practice reflection, before any assessed task.
- Tell students they can say “I’m stuck” and the tutor will slow down and help them find a next step.
- Tell students they can disagree with the AI; reflective judgement is theirs, and a tutor’s feedback is not a verdict.
Which library to recommend
Use Reflective Foundations for general reflective skills, Reflective Frameworks when a named model is required, and the specialist libraries (NHS & healthcare, medical, US academic) when students must meet a professional standard. The specialist libraries build the standard in, so they ask fewer setup questions.
When to use the deployment check
Before you recommend a tool to a class, or whenever the platform, plan, model or toolkit version changes, run the deployment check on the setup your students will actually use. It takes about ten minutes and confirms the tool still behaves like a tutor and refuses to ghost-write.
This toolkit is not affiliated with the NMC, GMC, any royal college or any university, and it cannot guarantee anonymity. Your course, placement, employer and regulator rules always take precedence — verify regulator-specific details against current official guidance.