AI Literacy, Ethics and Human-Centred Innovation for Undergraduate Students: A Challenged-Based Learning Approach

AI Literacy, Ethics and Human-Centred Innovation for Undergraduate Students is a Blended Intensive Programme (BIP) grounded in UNESCO’s AI Competency Framework for Students. It addresses four interconnected dimensions: human-centred mindset, ethics of AI, AI techniques and applications, and AI system design.

The programme combines online preparation modules, interactive synchronous sessions, and a 5-day face-to-face intensive week. Students explore AI as a social, ethical, and civic phenomenon — not only as a technical tool but as a learning partner. Particular emphasis is placed on human agency, accountability, responsible use, inclusion, sustainability, transparency, and the critical evaluation of AI outputs.

Students complete individual and group tasks throughout, culminating in a group prototype or concept for a responsible AI-supported solution addressing a real-world challenge, and an individual reflective portfolio.

Challenge-Based Learning is employed as the main pedagogical approach to deliver the programme. Rather than presenting AI literacy as a sequence of isolated topics, students work collaboratively on a real-world challenge connected to the responsible, ethical, and meaningful use of AI. Through the CBL phases of Engage, Investigate and Act, students move from broad societal concerns to concrete solutions, supported by inquiry, collaboration, ethical reflection and iterative design.

General learning outcomes

• Explain key AI concepts, including machine learning, generative AI, data, algorithms, bias, automation and AI-supported decision-making.
• Discuss the importance of human agency, accountability, transparency and citizenship in the AI era.
• Analyse ethical and social issues related to AI, including bias, misinformation, privacy, surveillance, academic integrity, environmental impact and overreliance.
• Apply AI tools responsibly to support inquiry, creativity, communication, learning and problem-solving.
• Develop guiding questions and research strategies to investigate a real-world AI-related challenge.
• Evaluate AI-generated outputs using criteria such as accuracy, relevance, fairness, transparency, inclusiveness and reliability.
• Collaborate in interdisciplinary teams to design a responsible AI-supported solution to a real-world challenge.
• Create a prototype, concept, campaign, workflow, chatbot design, policy proposal or educational intervention that responds to the selected challenge.
• Reflect on their own AI use, team contribution, ethical decision-making and learning process.
• Communicate their solution clearly to peers, educators and potential stakeholders.