Toward a learning game on Computational Thinking Driven by Competencies


  • Malak KANAAN Sorbonne université, CNRS, LIP6, Paris, France
  • Sébastien MAILLOS Sorbonne université, CNRS, LIP6, Paris, France
  • Mathieu MURATET Sorbonne université, CNRS, LIP6, Paris, France; INSHEA, Suresnes, France



Serious Games, Computational Thinking, Didactic Engineering, Fundamental Education, Learning Game


There are many learning games related to the theme of programming and computational thinking (CT) that exist nowadays. However, the main problem currently in France is that teachers lack training to teach K-12 learners to modern computer concepts. Teachers understand the competencies of referential but are not comfortable with and don’t know how to develop teaching sessions for these competencies. Our proposition is: a learning game (LG) driven by competencies will assist teachers to develop teaching sessions with learners. Our main objective is to help teachers to appropriate learning games on CT. To do this, we conducted an analysis based on the PIAF (Pensée informatique et Algorithmique dans l’enseignement Fondamental - Computational Thinking in primary school) reference framework which aims at developing CT in elementary school. It lists a set of competencies related to the development of algorithmic thinking in fundamental education. We chose to analyse three existing learning games on CT with this framework. We selected these three learning games ("Blockly Maze", "Compute-it" and "Kodu") from 48 learning games identified on CT. These analyses show that many competencies aren’t present in the games. Then we study how to link the PIAF framework in a LG. We work on the learning game named SPY in which the player has to program an agent to escape a maze. Our contribution for this paper is double: (1) an analysis of existing learning games and (2) propositions how to express PIAF competencies in gameplay features.