Educational projects are always about competencies. Since our project is about Data Literacy, the consortium agreed to get inspired by a solid methodology for learning and teaching data driven skills. Dataninja suggested to use the methodology explained in “Data literacy on the road: Setting up a large-scale data literacy initiative in the DataBuzz project”, an article issued in the “Journal of Media Literacy Education” in late 2020. Basically, researchers applied the “Data Literacy Competence Model” (DLCM), developed by the Flemish Knowledge Centre for Digital and Media Literacy. DLCM identifies two different kinds of competencies for Data Literacy:
- Understanding Data: the knowledge, skills and attitudes to critically and consciously assess the role of data
- Using data: the knowledge, skills and attitudes to use data actively and creatively.
Those competencies are two strands that can help to identify the knowledge baseline of project learners and help them to scale it up to a higher level. At the same time this methodology will drive the creation of the educational content, which will be more simple in the part of “understanding data” teaching, and more difficult in the part of “using data” teaching. Both “Understanding Data” and “Using Data” have been divided into 4 sub-competencies, accordingly to the schema represented in the diagram. Following this methodology to create the educational content, we will allow teachers to learn Data Literacy and select what to learn at basic, medium or advanced level on the basis of their existing knowledge baselines.