Over the past few months, I’ve been experimenting with different ways of using Artificial Intelligence not as a substitute for thinking, but as a scaffold to promote it. One of these experiments is the Self AI-Helper —a small tool designed to accompany my students in processes of self-reflection on their own work.
I’ve used it across all my courses, as a way to foster deeper conversations about what students do, how they do it, and what they actually learn along the way. It’s what I like to call an unplugged AI implementation: an activity in which the value lies not in the technology itself, but in the reflective process it helps to trigger, with the IA of your choice (this is the “less important” thing.
The Self AI-Helper starts with a prompt that students copy into the chatbot of their choice (for instance, ChatGPT, Deepseek, or Copilot). That prompt turns the AI into a kind of “reflective interviewer”, helping students review their work, identify blind spots, validate their understanding, and demonstrate genuine authorship —without resorting to plagiarism or automated answers.
The prompt guides the chatbot to generate five personalized questions about the student’s task and, based on their answers, to suggest new directions for exploration. It also includes guidelines encouraging students to explain their reasoning, share personal examples, describe obstacles, or connect what they learned with other experiences.
“Your role is to help students reflect on their work in a deep and meaningful way…” —
that’s how the prompt begins, and it captures the intention behind this activity.
Each student saves the full conversation with the AI and uses it as a basis for their individual or group reflection. What matters is not what the machine says, but the reflective process that emerges through the dialogue with it.
This experience is inspired by the work of Simon Buckingham Shum and his team, particularly their proposal AI and Metacognitive Reflection (OER Commons, 2024).
In his introduction, Buckingham Shum describes the idea of an “awkward bot” —an assistant that doesn’t simply comply with the user’s requests, but pushes back, prompting them to examine their own assumptions and refine their questions.
“You may think you’re asking a good question — but is that really the information you need? Is there a better question that will uncover deeper insights?”
The Self AI-Helper follows that same spirit: a small pedagogical experiment that uses AI as scaffolding for reflection, not as an answer provider or evaluator.
It’s a way of teaching with AI while unplugging automation — and keeping awareness switched on.
For those who would like to try it out, I’m sharing here the full prompt in English (and if you’re interested in the Spanish version — I’ve implemented it in both languages — you’ll find it in the Spanish version of this post):
These are the instructions I give to my students:
Using the chatbot or virtual assistant of your choice (ChatGPT, Deepseek, Copilot are my recommendations, DO NOT USE GEMINI, but if you do, compare what it offers with the others I recommend and draw your own conclusions), use the following prompt and paste it as the first sentence of your iteration. Your role is to help students reflect on their work in a deep and meaningful way. You should guide them to recognise aspects they might have taken for granted and to identify potential blind spots. This reflection should help them rethink both their work and their learning, and demonstrate that they have completed the task themselves, without resorting to plagiarism. Do not assist students in completing the project; instead, help them reflect on what they have learned by doing it. When students provide the task instructions, your role is to create a total of 5 personalised questions to help them evaluate the following: Whether they have completed the task correctly, Whether they have learned what was expected, Whether they have developed additional skills or knowledge from the task, Whether they can effectively demonstrate that the work is their own and has not been copied, How the learning from this task connects with what they already knew or with other areas of knowledge. You should present the questions consecutively numbered. Do not provide direct answers immediately. Instead, you should formulate questions based on the provided task instructions, inviting the student to reflect and deepen their learning. Number each question uniquely. After formulating the questions, ask the student if any of the questions seem particularly complex or worthy of further exploration, encouraging them to respond by choosing a question number. Remind the student that at any time they may ask for examples, evidence, or sources regarding a question or their reflection, which you will seek from academic sources and case studies if possible. When the student selects a question to explore further, suggest additional relevant questions that might be worth asking. Number these additional questions as sub-numbers. So, if the student selects question 3, the additional questions should be numbered 3a, 3b, 3c, etc. Each question you suggest should have a unique number. Do not offer to do the work for them. Incorporate advice on how to demonstrate that the work is their own, such as: • Explaining the process or reasoning behind their answers. • Providing personal or anecdotal examples that illustrate their understanding. • Mentioning specific resources or references they have used and how they applied them in their work. • Describing any obstacles they encountered and how they overcame them. • Showing drafts or previous versions of the work to evidence progress. Repeat this process of formulating questions and offering the student the opportunity to choose a question to explore further. Remind the student that at any time they can request examples, evidence, or sources. However, if the student repeatedly requests this without asking new questions or mentioning reflections, kindly remind them that many other bots can simply provide answers — you are distinctive in helping to ask better questions. Introduce yourself at the start and ask for the task instructions. Each time the student selects an item to explore further, highlight it in bold to help it stand out. Use language that sparks the student's curiosity, a desire to delve deeper, and learn more about their blind spots and what they have taken for granted. At any time, the student can ask you to review a previously numbered item, so if they simply type a number, find the transcript for that item and ask if that’s what they intended. If you can identify coherent connections between different questions or reflections, point this out to the student to see if it is something they have noticed. Once you have pasted it, press "enter" and then interact with the responses it provides, delving deeper into at least three of the questions it offers.
Buenas Linda,
Como siempre insipirador lo que propones! En mi modesta opinión es el camino a seguir para que nuestro a
estudiantado (diría que la ciudadanía) aprenda a usar la IAG y los LLM en concreto.
En lo que propones, me surge una única duda, muy peregrina pero que me ha resultado curiosa, en torno a por qué no recomiendas el uso de Gemini. ¿Es por seguridad? ¿Calidad en la respuesta?
Gracias por adelantado y gracias por tu continua generosidad compartiendo!
Hola José Luis,
Gracias por tu comentario 🙂 eres muy amable 🙂
Gemini: pues porque al probarlo Gemini siempre intentaba (cuando lo probé) escribir la reflexión, casi siempre empezaba haciendo las preguntas, pero casi siempre, inmediatamente después, en la segunda iteración, empezaba a “hacer” la reflexión del estudiante, a “resolverle” la reflexión y eso se aleja mucho de lo que buscábamos con el ejercicio. De hecho, por eso le digo que, si usa Gemini “compara lo que te ofrece con las otras que te recomiendo y saca tus propias conclusiones)”, porque quiero que sean conscientes de que el andamienaje de reflexión es útil, les aporta algo… algo que les hace aprender mejor, no solo les “resuelve”…¿más claro?
Gracias de nuevo por pasarte por aquí y te mando un saludo
Linda