What skills are needed to engage meaningfully with artificial intelligence? Inspired by UNESCO’s competency framework, this article presents two complementary grids designed to guide both students and educators in progressively acquiring the knowledge, skills, and attitudes related to AI. From critical thinking to system design, and including ethical considerations, these competencies aim to foster responsibility, innovation, and pedagogical transformation. An essential resource for rethinking education in the algorithmic age.
Developing students’ AI skills
Developing AI competencies among students is essential to help them navigate and succeed in a world where these technologies are increasingly pervasive. According to UNESCO’s competency framework, these skills are organized into four key domains that combine ethical awareness with technical understanding. They aim to strengthen students’ critical thinking, grasp of technical concepts, and ability to design innovative systems. These competencies should be introduced progressively, moving from initial awareness to practical and creative application.
- Human-centered mindset Developing a critical approach to AI is a key competency. Students need to learn how to assess whether an AI-based solution truly benefits individuals and society.
- Applied example : A workshop might invite students to analyze automation applications—such as customer service chatbots—and debate their impact on jobs and human relationships.
- AI Ethics : Ethical issues related to AI—such as privacy and bias—should be addressed from an early age. This includes the ability to identify and critically assess problematic practices.
- Applied example : Students could work on a scenario where they identify the ethical implications of using facial recognition technology in a school setting, and then propose alternative solutions that respect individual rights.
- AI Techniques and Applications Understanding how algorithms work and how data is used is crucial for interacting intelligently with AI tools.
- Applied example: Through a hands-on exercise, students could program a simple model using Scratch or Python to understand how an AI system learns from data.
- Designing AI Systems Thinking about the design and optimization of AI systems requires both a systemic and creative approach.
- Applied example : As a project, students could design a basic prototype aimed at solving a real-world problem—for example, a recommendation system that suggests books tailored to users’ interests.
Summary of key skills
| Area of expertise | Description | Applied example |
| Human-centred mindset | Develop critical thinking skills and evaluate the appropriateness of using AI in various contexts. | Analyse the impact of automation on jobs using real-life examples. |
| AI Ethics | Understand the ethical dilemmas associated with AI, such as bias, privacy, and sustainability. | Discuss the controversies surrounding facial recognition and propose solutions. |
| Techniques and applications | Acquire knowledge about how algorithms work and how AI models are trained. | Introduce students to programming a simple model using Scratch or Python. |
| Designing AI Systems | Think systemically to design, test, and optimise AI systems tailored to specific problems. | Think systemically to design, test, and optimise AI systems tailored to specific problems. Develop a prototype to solve a specific problem using accessible tools. |
Developing teachers’ AI skills
To effectively support students in learning about AI, educators themselves need to develop specific competencies. These go beyond simply understanding AI tools—they involve critical thinking, pedagogical application, and a willingness to innovate. UNESCO’s framework outlines several key areas, each broken down into progressive levels to help guide teachers in their professional development
Before diving into the framework, it’s important to understand the underlying logic. Teachers must first master the basics—such as evaluating the impact of AI on their own subject area. They can then deepen their understanding by exploring specific educational use cases. Ultimately, they should be able to design and innovate by integrating AI in advanced ways into their teaching and collaborative practices.
- Human-centred mindset This skill aims to cultivate critical thinking about the impact of AI systems and encourage students to reflect on the appropriateness of their use.
- Applied example: Organise a workshop where students analyse the consequences of automation on jobs or everyday life, using real-life examples or simulated AI tools.
- AI Ethics Students should understand the ethical dilemmas associated with the use of AI, particularly on topics such as privacy, bias, and sustainability.
- Applied example: Study controversial use cases of AI (e.g., facial recognition) to discuss ethical issues and propose solutions that respect human rights.
- AI Techniques and Applications Operational knowledge, such as how algorithms work or how AI models are trained, enables students to interact with these technologies in an informed manner.
- Applied example: Use accessible tools such as Scratch or Python to introduce students to basic programming for an AI model.
- Designing AI Systems This field teaches how to approach the design, testing, and optimization of AI systems by adopting a systems thinking approach.
- Applied example: Propose a project in which students define a problem to be solved by an AI system and develop a simplified prototype.
These skills must be developed progressively to enable students to acquire a solid foundation while building their ability to apply and create AI solutions.
Summary of key skills
| Aspect | Description | Level: Acquire | Level: Deepening Understanding | Level: CreateLevel: Create |
| Human-centred mindset | Promote a critical and humanistic approach to AI. | Understanding AI impacts on education. | Analyse human-AI interactions in various educational contexts. | Designing human-centred educational models that integrate AI. |
| AI Ethics | Integrate ethical principles into the use of AI tools. | Identify ethical dilemmas related to AI. | Evaluate and adapt AI tools to educational values. | Contribute to the development of ethical rules tailored to teaching. |
| Foundations and applications | Understanding and applying the basic concepts of AI in teaching. | Apply validated AI tools in specific activities. | Integrate advanced techniques to meet educational needs. | Create and customise AI tools for innovative educational applications. |
| Teaching methods engaging AI | Develop educational strategies to integrate AI into teaching. | Use AI to support lesson preparation. | Design educational activities using appropriate AI tools. | Transforming teaching practices through advanced AI integration. |
| Professional development | Using AI for continuing education and professional collaborations. | Discover AI tools for your own training. | Using AI to collaborate and exchange teaching practices. | Designing AI-based continuing education programmes. |
Drawing on UNESCO’s AI competency framework for teachers, this table outlines how specific skills can be developed through three stages of progression: acquiring foundational knowledge, deepening understanding, and engaging in creative application.