Data literacy: practices and training scenarios

Abstract

Data literacy is considered an emerging concept or a novel line of research that empowers the citizen in today's context of the data-driven society by providing the necessary training to solve real-world problems and make data-driven decisions. The data-literate individual is able to understand, explain, use, interpret, consume and disseminate - critically and effectively - data, and turn it into information and knowledge. This study is characterised as being primarily qualitative in nature. Firstly, an exploratory type of documentary research is carried out to identify and analyse the models and training practices that are being carried out in the university environment on data literacy. The search was carried out through the Google platform, under common research criteria ("data literacy" AND "university", "data literacy training" AND "university"), and in different languages (English, Portuguese, Italian and French). As inclusion criteria, the search was limited to the last 5 years (2018-2022) and priority was given to course-based training models and practices (MOOC, webinar, Blog, etc.). The sample consists of 82 types of training practices from Brazil, Spain, the United States, France, Italy, the United Kingdom and Switzerland. The information was compiled in a file with the following categories: country, name of the instruction (Expert Degree, MOOC, Seminar, etc.), modality (face-to-face, online, etc.) cost, methodology (expository or interactive); learning content, target group (undergraduate, graduate students or teaching and research staff) and duration. The resulting database was analysed quantitatively using SPSS.28 statistical software. The results show that 34.1% of the training options are provided in Spain, 22% in France and 19.5% in the United Kingdom. More than half of the training (53.7%) takes place through seminars, courses or workshops and almost three quarters of the internships are paid (70.7%). Face-to-face training is the most used modality (36.59%), followed by virtual training (34.1%). The main instruction is directed towards data science; data management and Big Data (25.1%; 22.6% and 12.3% respectively). 31.7% of the activities follow an interactive methodology and 30.5% develop an interactive and expository method. 20.7% of the training is aimed at graduates, diploma or degree holders, postgraduate students (17.9%) and other professionals (14.4%). The duration of training is mainly long, ranging from 13 to 24 months (24.39%). Finally, the categories examined offer different results depending on the country in which the apprenticeship is provided. Thus, for example, graduates in Spain, while bearing the cost of the training, have a wide training offer, characterised by face-to-face training, with an interactive/expositive methodology and an extensive duration.