Project Overview
Topic | Content |
---|---|
Project Titile | Topological Approach of Learning Games for Game Design Assistances |
Accronym | TALE4GDA |
Coordinator | Alexis LEBIS |
Funding | Agence Nationale de la Recherche (ANR) |
Evaluation Committee | CE38 Interfaces : mathématiques, sciences du numérique – sciences humaines et sociales |
Analytical Code | ANR-23-CE38-0001-01 |
Start date | 1er Octobre 2023 |
End date | 1er Septembre 2027 |
Abstract
The design of learning games for learning is a complex task. It involves a large number of challenges for the different stakeholders (e.g. institutions, teachers, technical designers, players, video game experts). Among these challenges, we can note the acculturation to the game, the difficulty to align pedagogical concepts with the game mechanics and diegesis, or the specific needs of communities of practice. Consequently, we observe in the TEL community a strong ad hoc aspect of the design of serious games, especially regarding the game elements used to address specific pedagogical intentions. However, this ad hoc character does not allow to capitalize efficiently on both the serious games created, nor the choices between pedagogical intentions and game elements to implement them. The expertise of the whole community is then difficult to share and to reuse, and it is difficult to efficiently assist the actors in this design stage.
Project Objective
The project TALE4GDA has two mains objectives :
- Capitalizing1 learning games in various scientific, social and industrial communities ;
- Assisting the stakeholders involved in the design phase of learning games with pioneering and innovative mechanisms for decision and design support.
The central research focus of the project will be the concept of alignment between a ludic entity and a pedagogical intention — referred to here as pedago-ludic alignment (abbreviated P-LA).
- Semantic in accordance to: Lebis A., Lefevre M., Luengo V., Guin N.Capitalisation of Analysis Processes : Enabling Reproducibility, Openess and Adaptability thanks to Narration. LAK ’18 – 8th International Conference on Learning Analytics and Knowledge, Mar 2018, Sydney, Australia. pp.245-254, ⟨10.1145/3170358.3170408⟩. ⟨hal-01714184⟩ ↩︎