In today’s learning ecology, shaped by artificial intelligence, prompts have become a distinct genre of educational action. They’re far more than technical instructions—they’re linguistic mediators that translate pedagogical intent into cognitive experience. Designing an educational prompt means recognizing that every word steers mental, emotional, and ethical processes, prompting learners to think, create, question, and solve in specific ways. In this sense, writing prompts is a contemporary form of discursive pedagogy: teaching how to think, starting from how questions are framed.
Over recent months, I’ve worked at the intersection of prompt design, the pedagogy of questioning, and specific conceptual frameworks. From this convergence, I developed a set of content presented in tables that link prompts to three complementary frameworks: an expanded version of Bloom’s cognitive domains for the digital era, emerging educator profiles (rural, STEAM, researcher, new teachers), and the competencies of the European Digital Competence Framework for Educators (DigCompEdu 2.0).
As I advanced through each integration, iterating and applying ideas, I noticed how every prompt should evoke pedagogical intent, suggest real uses, indicate possible extensions (sometimes complex but necessary), and be associated with a digital cognitive domain. This way, when revisiting a prompt, the educator isn’t simply using it—they’re able to interpret its structure and formative purpose.
My aim is to present an adaptable, scalable, and reflective repertoire that enables smooth movement between levels of thought and technological environments while always keeping sight of the human dimension of teaching. Like any effective didactic act, a well-designed prompt doesn’t replace the educator—it amplifies their mediation: extending their voice in digital settings, inspiring students to build knowledge more autonomously, and unlocking new forms of co-authorship between people and intelligent systems.
Below, I share a selection of prompts—intended as practical units of pedagogical innovation, integrating cognitive, digital, and ethical competencies in a single act of writing.
I. Prompts by Core Cognitive Domains
1. Identify and Explain Key Concepts in Your Discipline Using Generative AI
Prompt:
“Identify the three foundational concepts in [your subject area] and, for each: (a) provide a brief explanation (max 40–50 words), (b) two contextualized examples relevant to [elementary/secondary/higher education] students, and (c) suggest a practical way to share these in class (choose: ‘text’, ‘outline’, ‘comparison chart’, ‘infographic’). Respond with a numbered, subtitled list.”
Pedagogical intent: Activate and reinforce discipline-specific vocabulary; facilitate teaching through transferable examples.
Possible use: Initial diagnostics, glossary creation, peer explanations.
Cognitive domain: Remember / Understand / Apply
2. Summarize a Scholar’s Contributions or a Theory with AI Assistance
Prompt:
“State the [author/theory] and educational level [level]. Ask AI for a critical summary (200–250 words) including: (a) central thesis, (b) two significant contributions to teaching, and (c) an analogy or didactic example aimed at [level] students. Deliver in distinct paragraphs with suggested references (at least 2).”
OR
“Get to know [author/theory]: [name]. Develop five critical questions a teacher should consider before teaching this theory (e.g., scope, assumptions, applications, limitations). For each question, suggest sources or forms of evidence to address it.”
Pedagogical reasoning: Avoid generic summaries; encourage identification of assumptions, limits, and evidence, preparing educators for critical instruction.
Classroom procedure: AI generates questions → teacher/students select 3 → investigate and answer → small group discussion.
Pedagogical intent: Synthesize theoretical knowledge into accessible teaching materials; promote critical faculty reflection.
Possible use: Lesson planning, reference cards, theoretical mini-units.
Cognitive domain: Understand / Analyze
3. Compare Academic Definitions of a Concept
Prompt:
“Specify [concept] and request three academic definitions (with source) from AI. Also ask for: (a) a comparative table with rows for ‘definition’, ‘author/source’, ‘pedagogical implication’, (b) a concluding paragraph (80–100 words) with a recommended operational definition for your [level] students.”
OR
“Specify the [concept]. Have AI generate four questions about the pedagogical and policy consequences of adopting each definition. Ask for context examples where each works or fails.”
Pedagogical reasoning: Go beyond comparing—evaluate practical consequences.
Procedure: AI proposes questions → students respond, apply to a local case → derive a consensus operational definition.
Pedagogical intent: Foster capacity to contrast frameworks, select effective definitions.
Possible use: Theory-building for courses, guided debates.
Cognitive domain: Analyze / Evaluate
4. Apply a Concept to a Real Educational Case
Prompt:
“Briefly describe a real situation in your educational context (max 100 words) and ask the AI for three practical interventions that apply [concept]. For each intervention, request: (a) a clear objective, (b) 3–5 procedural steps, (c) required materials, and (d) an assessment method (evidence). Present the response as a list.”
Pedagogical intent: Foster the transfer of theory into concrete and scalable classroom practices.
Possible uses: Intervention planning, classroom projects, practical guides for teachers.
Cognitive domain: Apply / Create
5. Design a Brief Instructional Sequence with AI Support
Prompt:
“Specify: [topic], [educational level], number of sessions, duration per session [minutes], and learning objective [state]. Ask the AI to provide: (a) a title for the sequence, (b) a general objective, (c) for each session: specific objective, main activity (steps), resources, and formative assessment (criteria). Deliver in table format (one column per session).”
Pedagogical intent: Enable clear, coherent, and implementable instructional planning.
Possible uses: Designing micro-units, substitute plans, hands-on workshops.
Cognitive domain: Apply / Create
6. Critically Analyze an Academic Text and Generate a Commentary
Prompt:
“Paste a fragment of the text (max 800 words) and ask the AI to: (a) identify the central thesis, (b) list 3 key arguments, (c) point out 2 methodological or conceptual limitations, and (d) suggest 2 questions for pedagogical discussion. Format: bullet points or otherwise.”
OR
“Paste the fragment. Have the AI develop five probing questions about the text (regarding assumptions, evidence, and implications). Respond to three, then write a 150–200 word meta-text on what you reconsidered or confirmed in your original interpretation.”
Pedagogical reasoning: Make AI a critical interlocutor; encourage justification and revision.
Procedure: AI asks → student responds → meta-text → discussion.
Pedagogical intent: Strengthen critical reading and academic discussion among students and teachers.
Possible uses: Seminars, academic reading clubs, peer analysis activities.
Cognitive domain: Analyze / Evaluate
7. Generate Hypotheses from Data or Simulated Situations
Prompt:
“Supply a data set or describe an educational scenario (max 150 words). Ask the AI for four plausible hypotheses explaining the phenomenon, and for each hypothesis, request observable variables and a brief method for testing it (evidence design). Deliver in table format: hypothesis / variables / brief method.”
OR
“Provide the data/situation. Ask the AI to generate four heuristic questions for turning observations into hypotheses (e.g., What variables could explain X? What evidence is missing?). For each question, indicate what data would be needed to test it.”
Pedagogical reasoning: Teach the transformation of observations into robust research questions and hypotheses.
Procedure: AI proposes questions → student designs hypotheses based on those questions → data collection plan.
Pedagogical intent: Encourage scientific thinking and experimental design in educational contexts.
Possible uses: Methodology workshops, classroom projects, action research.
Cognitive domain: Analyze / Create
8. Assess the Validity of Arguments or Evidence Generated by AI
Prompt:
“Act as an expert in [discipline, field] and provide an argument about [topic]. Carry out a critical analysis including: (a) implicit assumptions, (b) types of evidence required to validate the claim, (c) two contrasting sources, and (d) recommendations for teaching informed by those conclusions. Respond in clearly separated sections. Conclude by posing questions that deepen understanding of the topic.”
OR
“Paste the statement or argument. Ask the AI to generate three critical questions for checking its validity (e.g., What empirical evidence supports it? What counterexamples exist?). Ask for sources or methods to check each question.”
Pedagogical reasoning: Shift from validating claims to understanding what and how to validate—build critical literacy.
Procedure: AI generates → student substantiates two questions with sources → presents findings.
Pedagogical intent: Foster epistemological assessment of sources and automated statements.
Possible uses: Fact-checking activities, media literacy exercises.
Cognitive domain: Evaluate / Analyze
9. Create a Rubric or Assessment Instrument with AI
Prompt:
“Given the following learning objective [insert text], type of product [essay/project/presentation], and evaluation weight [e.g., 20%], prepare an analytic rubric with 4 criteria, 5 levels (numbered 1 to 5), and clear descriptors for each level. Present as a ready-to-use table.”
Pedagogical intent: Clarify expectations; make evaluation replicable and formative.
Possible uses: Summative and formative assessment, peer evaluation.
Cognitive domain: Create / Evaluate
10. Develop a Learning Activity Based on an Authentic Problem
Prompt:
“Describe the authentic problem in your community [briefly] and specify: target audience [level and group], available resources [list], and estimated time [hours].
Next, provide this prompt: ‘Act as an expert in problem-based learning or [specific active methodology], and based on the following problem [brief description], give me an activity plan that includes: objective, student roles, phases, final product, and evaluation criteria. Present the steps in a numbered list.’”
Pedagogical intent: Advance situated learning, community engagement, and practical application.
Possible uses: PBL, community projects, service learning.
Cognitive domain: Apply / Create
11. Draft an Argumentative Text with AI as Co-Author
Prompt:
“Write an initial draft of [max 300 words] on [topic] or specify your main idea. Then present this prompt:
‘Based on this initial draft [insert draft], act as an expert in [draft’s topic] and prepare (a) 3 well-founded counterarguments, (b) suggested pieces of evidence to reinforce your thesis, and (c) a revised version of the text integrating improvements. Provide the original text, then your revised version, and end with a list of verifiable sources. Finish by posing questions on my proposal’s content to check the clarity of my arguments.’”
OR
“Before writing, ask the AI for four strategic questions that challenge your stance. Answer each, use those answers to draft your introduction and counter-argument, and finally have the AI point out three remaining weaknesses to help improve your conclusion.”
Pedagogical reasoning: Promote anticipation of objections and argument reinforcement; write with authentic critique.
Procedure: AI questions → answers → drafting → AI follow-up → revision.
Pedagogical intent: Practice academic writing and human/AI collaborative authorship.
Possible uses: Writing workshops, guided feedback, collaborative assignments.
Cognitive domain: Create / Evaluate
12. Design an Infographic or Concept Map Using AI
Prompt:
“Act as an expert in [topic], and based on the following text [provide source or topic, max 400 words], prepare: (a) a concept map structure with nodes and relationships in list format (markdown or compatible with mapping tools), (b) a suggested title, (c) a short text for each node (20–30 words), and (d) design suggestions for visuals (colors, icons, prioritization). Deliver as [hierarchical list, outline, markdown, etc.].”
Pedagogical intent: Enable visual representations that promote understanding and retention.
Possible uses: Class materials, presentations, study aids.
Cognitive domain: Understand / Create
13. Produce an Expanded Summary of a Lesson or Reading
Prompt:
“Act as an expert in [summary topic]. Given the following transcript [paste transcript or text, max 1,000 words], prepare: (a) an executive summary (150–200 words), (b) three key ideas with pedagogical implications, and (c) two quick follow-up activities for [the next meeting, a class on, or a related learning opportunity]. Present in [separate blocks, structured template, etc.].”
OR
“Paste the class or reading. Ask the AI for three questions about the text’s assumptions and omissions (‘the unspoken’). Pick one, write a 100-word reflection, then have the AI react to your reflection.”
Pedagogical reasoning: Counter superficial summaries; encourage critical reading and identification of gaps.
Procedure: AI questions → student reflects → AI responds → final synthesis.
Pedagogical intent: Consolidate learning and prepare for continued instruction.
Possible uses: Teacher journals, study support, student feedback.
Cognitive domain: Understand / Apply
14. Generate Critical Reflection Questions for Group Discussion
Prompt:
“Act as an expert in [discussion topic]; using [state the text/topic], prepare [five, or desired number] open-ended questions designed to foster: (a) critical thinking, (b) connection to local context, and (c) follow-up research activities. Provide them as a [list, dialogue, etc.] and label as [‘debate questions’, ‘project questions’, etc.].”
Pedagogical intent: Stimulate academic dialogue and active inquiry.
Possible uses: Forums, seminars, discussion groups.
Cognitive domain: Evaluate / Create
All prompts emphasize process over mechanical completion, aiming to model intentional thinking and practical skill-building for educators in digitally mediated contexts. The goal is not for teachers to “use prompts,” but to understand their function: how the structure and wording of each prompt activate cognitive processes, configure pedagogical aims, and make dialogue with AI a space for ethical, critical growth.
Each of these examples can be found in full at Escrituradigital.net, as part of our ongoing exploration into language, thinking, and technology in education. Teaching, after all, always begins with a well-posed question.
