COntent Personalization for skill-building on COmputational Thinking – COPCOT

Nowadays, Computational Thinking (CT) is is one of the major skills that learners must acquire and develop. It covers a set of cognitive abilities and skills that is challenging to learn and teach. Technology Enhance Learning (TEL) gives the opportunity to learners to enhance their CT skills and conceptual knowledge. The COPCOT project aims to (1) understand learners’ skills-building in CT through a TEL platform, and (2) facilitate skills-building in CT through content and feedback personalization. To reach our objectives, we will elaborate the competence and learner models that will allow personalization and feedback generation in relation with how learners build their comprehension of CT. To this end, we will use the Algorea platform developed by the France IOI association which aims to encourage French learners to progress in CT and which already has an important amount of data. We will integrate and test our models and personalization features in the platform. Our main target in experimentations will be university students, in Social Science and Science & Technology fields, who are novice in terms of CT skills. This multidisciplinary project will involve researchers in Educational Sciences (CIREL) and Computer Science (CRIStAL). As the CT is one of the 21st century skills and it has a key role to access to the labor market, the project will have an impact on society by: facilitating the CT learning at a large scale, increasing employability, and helping learners to understand social impacts of CT and having their own opinions on it as citizens.