GenerationAI_IO1_Pedagogical Framework

www.generation-ai.eu/ The European Commission's support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. [Project Number: 2020-1- NL01-KA201-064712] structured based on that and that teachers need to know how they can make their students aware of this. They also propose a technology to enhance the computational thinking aspects of the game. Although it seemed that adding this technology caused an overload for both teachers and students, teachers were in fact comfortable engaging with these enhancements and students showed signs of great engagement. This overwhelming feeling from teachers and students was also evident from the presentation of the “Learn to Machine Learn (LearnML)” , an Erasmus+ Strategic Partnership project, which aims to implement a game-based learning approach for teaching and developing students’ digital literacy, computational thinking and AI and Machine Learning (ML). Greek educators only had a better idea of how AI and ML terms are defined, after the presentation from the facilitator. Furthermore, they developed their thoughts and understanding during a reflective discussion on how important AI and ML for themselves as educators are, not only to gain a better understanding of those terms but to be able to convey that knowledge to their students. One of the most important and urgent things which was under discussion was the ethics around AI and ML. Compared to educators, specialized doctors and general practitioners in Greece appeared to be more well informed about AI and ML. They also support that AI will have a crucial role and impact in the near future by changing our contemporary life, thus it important to be introduced to the students from an early age. Another game designed for teaching and developing students’ digital literacy, computational thinking and AI and Machine Learning (ML) is the “AutoThiking” (Hooshyar et al., 2021). In this game the player is a mouse who wants to collect all the cheese pieces, while simultaneously escape from two cats in the maze. The more computational thinking concepts or skills the player uses in solving the problem, the more