Smartphone-Based Game Development to Introduce K12 Students in Applied Artificial Intelligence


  • Sara Guerreiro-Santalla University of Coruna, Spain
  • Alma Mallo University of Coruna, Spain
  • Tamara Baamonde University of Coruna, Spain
  • Francisco Bellas University of Coruna, Spain



Applied Artificial Intelligence, Supervised Learning Teaching, Smartphone App Development, Artificial Collective Intelligence, AI Education For K12


This paper presents a structured activity based on a game design to introduce k-12 students in the topic of super-vised machine learning from a practical perspective. The activity has been developed in the scope of an Erasmus+ project called AI+, which aims to develop an AI curriculum for high school students. As established in the AI+ principles, all the teaching activities are based on the use of the student's smartphone as the core element to intro-duce an applied approach to AI in classes. In this case, a smartphone-based game app is developed by students that includes a neural network model obtained with the "Personal Image Classifier" tool of the MIT App Inventor software. From a didactic perspective, the students dealt with supervised learning to solve a problem of image classification. The main learning outcome is the under-standing of how relevant is to develop a reliable machine learning model when dealing with real world applications. This activity was tested during 2021 with more than 50 students belonging to six schools across Europe, all of them enrolled in the AI+ project.




How to Cite

Guerreiro-Santalla, S., Mallo, A., Baamonde, T., & Bellas, F. (2022). Smartphone-Based Game Development to Introduce K12 Students in Applied Artificial Intelligence. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12758-12765.