Autor(es): Silvestre, Cláudia ; Bonacho, Fernanda ; Araújo, Susana ; Pina, Helena Figueiredo
Data: 2024
Identificador Persistente: http://hdl.handle.net/10400.21/17185
Origem: Repositório Científico do Instituto Politécnico de Lisboa
Assunto(s): Digital literacy; Data literacy; Higher education; Data journalism; MOOC; IPL/IDI&CA2023/MOOC-JorDt_ESCS
Data journalism is still an area worth investing in, both in newsrooms and in the curricula of communication and media courses in general, and journalism courses in particular. While it is true that journalists have always worked with quantitative data, the current volume of data available requires expert skills to rigorously examine and filter them, contributing to a better and critical understanding of social, political, and economic issues in our society. Additionally, these skills are essential for effectively communicating information through a clear and rigorous visual narrative, which may also require knowledge in the field of visual communication. To address this gap, we have chosen to develop a Massive Open Online Course (MOOC) that serves as an introduction to data journalism. This MOOC can be beneficial for communication students, especially those studying journalism, as well as professionals seeking training in this field. The choice of a MOOC is driven, on the one hand, by the need for digital pedagogical resources in education, particularly in many higher education institutions. On the other hand, a MOOC allows more people to access this training and knowledge regardless of their learning pace, availability, age, or geographic location. Meanwhile, we are also contributing to the Sustainable Development Goals (SDGs) of the Agenda 2030, specifically Goal 4, which aims to "ensure inclusive and equitable quality education and promote lifelong learning opportunities for all." In this paper, whilst justifying the choice for this learning tool, we will also present the underlying framework for the creation of this data journalism MOOC, which was based on a pedagogical approach grounded in a web-based personalized learning model.
