Learn to Machine Learn (LearnML)
Topic/ Area
Robotics – Machine Learning
Date released
1/9/2019 – 31/8/2022
Type of Best Practice
PD/ Training Programme
Partners/ network
Project Coordinator
University of Malta
Consortium Members
- NTUA – National Technical University Athens
- KORAIS EDUCATIONAL ENTERPRISES SA (PALLADIO)
- SCIENCE CENTER Malta
- NTNU – Norwegian University of Science and Technology (NTNU)
Description of the methods/ approach
The collection of different games and software tools that can be used to support AI and ML in primary, secondary and tertiary education was done by searching various libraries and search engines such as Google and scientific publications (e.g., Google Search, ACM Digital Library, IEEE Xplore, Science Direct, Google Scholar).
The search string used during the search covers three main terms content (“AI Education”, “ML Education”, “CS Education”) and the medium (“Game-Based Learning”, “Games for Learning”).
Purpose/Aim
LearnML project transfers the notion of AI literacy to primary and secondary education and aims to introduce students to the core principles of AI and ML through a uniquely designed game-based educational toolbox.
Evaluation (results) of its effectiveness
The project is ongoing, so there is no conclusive evidence on its effectiveness.
Overview of the lessons learned which are relevant to the project
Supporting material for students and educators is an extremely useful resource that can enhance the attainment of the learning objectives. AI and ML are still a new topic in pre-college education; therefore, students and teachers require more than an educational game to approach, understand and be able to discuss the relevant concepts.
The effectiveness of a game-based curriculum in schools relies upon multiple context-related factors such as game literacy of the students, technological skills of the teachers, class schedule restrictions, the computers available and their specifications, and the available bandwidth.
