Learn to Machine Learn: Designing a Game Based Approach for Teaching Machine Learning to Primary and Secondary Education Students
Iro Voulgari, Marvin Zammit, Elias Stouraitis, Antonios Liapis, Georgios N. Yannakakis
Abstract
With the ubiquitous role of Artificial Intelligence (AI) in everyday applications such as smartphones and social media, children need digital literacy skills to navigate the digital world, critically view, and reflect on the social and ethical implications of the design and architecture of AI systems. To address this increasing need for AI literacy skills, particularly for younger students, this paper presents the rationale of the LearnML project which aims to develop a framework and game-based educational material for promoting AI literacy among primary and secondary education students. We also describe the design and initial assessment of the game “ArtBot”, developed as part of the LearnML project. We review existing literature, discuss the educational game design and development of “ArtBot” and describe the initial feedback of students and teachers. Our goal is to provide insights and suggest guidelines for the implementation of game-based learning environments for supporting AI literacy skills of students.