Generative AI has had a profound impact on various sectors since mid-2022. The rapid adoption by students poses challenges for student assessment and raises concerns about student development. This thesis delves into the subject and proposes a positive implementation in education through play-based learning. The project uses a human-centred iterative design approach, consisting of co-design workshops with children, teachers and expert interviews. The research shows that teaching children about AI and generative AI can be done from a young age using play-based learning.

The study captures the diverse perceptions of elementary school children and teachers regarding generative AI. Key findings highlight children’s concerns and needs with regards to generative AI. Cooperatively formulated design criteria point towards children’s main interests for products or services with generative AI or AI to have a play-based nature, foster creativity and inspiration, safeguard their privacy and security and help them achieve their goals.

The research in this thesis also explores educators’ perceived challenges and interests in classroom integration of generative AI. Key findings include the perceived necessity for both teachers and students to learn about generative AI, the interest across different levels of education and that the age deemed appropriate for students to be introduced to generative AI is often considered to be at the end of primary school or at the start of secondary school.

From the research several design principles are proposed to create an engaging, ethical and human-centred AI learning experience. To facilitate this experience and to spearhead the integration of generative AI into education, a company named “PLAI” is conceptualised. The company aims to implement generative AI in education in a positive way by providing learning material which stimulates engagement, creativity and social learning while safeguarding privacy and security by offering play-based and scaffolded learning in workshops. Future recommendations and plans include the development of a multi-modal generative AI model which can run locally on school servers and is alignable with their curriculum.

Limitations of this study include a lack of direct interaction and research with high school students, a need to explore text based generative AI interactions with students, and a need to assess generative AI’s long-term effects on student well-being.