Przykładowa nazwa metody
Method short description supporting line text — lorem ipsum dolor sit amet, consectetur.
AI-supported teaching
Brainstorming with AI
Tools: AI Chatbot, whiteboard or Padlet
Best for: stimulating creativity and problem-solving
Why Use It
AI-supported brainstorming is a way to gather a wide range of ideas quickly and then select the most promising ones. Tools such as ChatGPT or Gemini help students generate, organise, and refine ideas. They can also reduce anxiety about being judged, giving less confident students more space to contribute and making classroom discussions more dynamic.
In teaching, AI can simulate real innovation practices such as iterative concept development, testing assumptions, and the rapid comparison of alternatives. As in start-ups, consulting, or research and development teams, students work in small groups and ask a tool such as ChatGPT to suggest answers to a specific question, for example: How can small businesses reduce emissions in transport and deliveries? AI generates a range of possible solutions, after which students begin to collaborate. They discuss the ideas, select the most promising ones, group them into categories, and refine those that are too general or unrealistic. As a result, students move quickly from initial ideas to concrete proposals that can be described, justified, and defended.
The method can be adapted to suit the aim of the class. In one version, students first generate ideas independently and then compare them with AI-generated suggestions. In another, the group evaluates and improves the responses produced by the tool.
A comparative variant can also be introduced, with different groups working with different prompts or tools and then analysing the differences in their results. Another useful option is constrained brainstorming, where AI generates ideas within specific criteria, such as budget, time, or regulations, making the proposed solutions more realistic
Practical Example
Course: Innovation Management
Topic: Searching for New Revenue Models
Students work in small teams to develop innovative business models for a digital banking application. Using AI as a creative partner, they move from defining the problem and generating ideas to evaluating solutions and delivering a short final presentation.
Warm-Up (10 min)
Present the challenge: How can digital banks develop new revenue models in the era of artificial intelligence and blockchain technology?
Students discuss trends such as sustainability, data monetisation, and personalisation in pairs or small groups. They then identify three to five barriers or opportunities. Examples should be specific, for instance focusing on the European market, Generation Z users, or green finance.
AI Brainstorming (10 min)
Each group selects one specific challenge and prepares a short prompt for AI, for example:
- Generate at least 10 innovative business models for a digital banking application using
blockchain technology.
Teams then create a long list of ideas.
Filtering (15 min)
Students analyse and group the generated ideas using a shared board (Padlet, Miro, or a traditional whiteboard). They discuss which ideas have the greatest potential and select the most promising ones using simple criteria such as impact × feasibility or the ICE model
In-depth Analysis (20 min)
Each team selects its strongest idea and develops it further by considering questions such as:
- Who will benefit from this idea, and why now?
- What are the key resources or risks associated with it?
- How could the idea create unique value for both customers and the company?
Students complete a short Innovation Card summarising:
- the problem;
- the proposed solution;
- the value proposition;
- the business model;
- the next steps.
Presentation and Reflection (15 min)
Each group records or delivers a two-minute presentation proposing its solution. Participants then vote for the most creative and feasible idea using Mentimeter or paper voting slips. (Impact, Confidence, Ease).
When It Works Best
- At the beginning of a course or project, when the aim is to spark curiosity and overcome the so-called “blank page” problem.
- In large groups, where AI can help balance participation and encourage more reserved students to contribute through writing rather than speaking.
When It Should Be Avoided
- When students lack basic knowledge, as they may copy AI-generated answers uncritically.
- In tasks where originality and authorship are central to assessment.
Challenges
- Students may copy AI-generated answers without reflection → encourage critical discussion.
- Maintaining ethical standards, including plagiarism and fabricated data → introduce clear, explicit rules on academic integrity.
- Participants may feel overwhelmed by the rapid flow of ideas → introduce time limits, use visual idea boards, and provide written guidance to make the process more predictable.
Adjust the Level
Easier → Provide structured prompts and pre-prepared topics. Ask the strongest group to present an example.
More Challenging → Ask students to compare AI-generated ideas with their own and explain the differences in a short reflective note.
Tips
- Keep the pace high and set clear time limits.
- Visualise ideas using online tools or sticky notes for grouping and ranking.
- Reward originality. During presentations, recognise unusual combinations of ideas.
- Ask students to generate ideas first and refine them afterwards.
How to Assess
Formative Assessment
Observe how teams discuss and filter AI-generated suggestions. Pay attention to collaboration, reasoning, and students’ ability to justify why certain ideas were accepted while others were rejected. A short reflective activity at the end can help consolidate learning.
Summative Assessment
A short final project (individual or group-based). Students prepare a one-page Innovation Canvas summarising their final idea, feasibility analysis, and proposed next steps.
Techniques
Students ask AI to generate multiple ideas on a given topic and deliberately refrain from judging their quality or relevance for a set period of time. To encourage variety, they ask for several versions of the list from different perspectives, such as a realistic version, an exaggerated version, or a competitive-advantage version, and then combine the responses into a single cloud of inspiration. Only in the second step do they select the three most promising ideas from the full pool and justify their choice in two or three sentences, explaining what makes them valuable and how they could be improved. This technique teaches students that creativity begins with abundance, helps them overcome the fear of the blank page, and shows that AI can accelerate idea generation, while humans give ideas meaning and direction.
Use it for generating ideas, warm-up activities, or when teams reach an impasse.
Students receive a set of paper or digital cards called Prompt Cards, each introducing a specific variation to working with AI, for example: explain this to a 10-year-old, or add a sustainability perspective, or compare it with another country. Students run the same prompt several times, modifying it each time according to the instruction on a randomly selected card. They then compare the results and discuss what has changed, such as the language, assumptions, examples, conclusions, and, in some cases, hidden simplifications or biases. This activity helps students practise conscious prompt design and develop the ability to recognise misleading or distorted information.
Use it between more demanding activities to refresh students’ attention and stimulate creativity.
A quick critical-thinking exercise in which students ask AI to explain or summarise a given topic, then check each statement against real data, such as Eurostat, OECD, or company reports. Students classify the facts as accurate (green), incomplete (yellow), or misleading (red). This simple exercise helps them become more sceptical readers and strengthens their ability to work with data.
It is particularly effective in courses related to economics, politics, or management, where the ability to distinguish facts from opinions is essential.
Present students with a short AI-generated text or chart containing subtle errors, logical gaps, outdated data, ethical bias, or inaccurate interpretation. Students identify, correct, and justify each error. In a finance class, for example, the text might use the term EBITDA incorrectly or confuse net margin with gross margin. Students correct the errors using reliable sources. The task helps develop accuracy, critical thinking, and a deeper understanding of key concepts.
It is particularly useful for revision sessions.
This technique involves combining seemingly distant fields in order to generate new concepts. Students use AI to create proposals based on the juxtaposition of two areas, then select one and develop it into a coherent, concise concept. The process requires quick analysis, selection, and refinement. As a result, it develops associative thinking, the ability to work at the intersection of different perspectives, and the skill of presenting ideas succinctly, all of which are important in innovation design.
It works best in creative modules, start-up laboratories, or courses focused on research and development strategy.
Downloads
Everything you need to run this method next week in your classroom.
Related methods