Characterization of Training Models in Data Literacy: Perspectives For Teacher Training

Abstract

Objective: This article presents the results of a study on training practices and models for data literacy at the university level. Theoretical Framework: Data literacy is an emerging and novel construct that provides the training required in a digital and digitized society. Method: To achieve this purpose, the training proposals based on courses, offered in the period from 2018 to 2022, and available in Spanish, English, Portuguese, French and Italian, were previously identified. Then, different categories were established that allowed the grouping of the data obtained, which were recorded in a file created for this purpose. Results and Discussion: The quantitative analysis carried out makes it possible to determine which country offers the most training in data literacy; the most common type of practice, the modality under which it is usually offered and the methodology applied; its cost and the target audience. It also confirms the existence of links between the different variables examined that characterize the type of training offered. Research Implications: It confirms the urgent need for a transversal training model in data literacy that responds to its main paradigms and parameters. Originality/Value: This study contributes to the literature by characterizing, for the first time, the training practices in data literacy, which will make it possible to detect the shortcomings and areas for improvement that these training scenarios present.