A strategic approach to information literacy: data literacy. A systematic review
DOI:
https://doi.org/10.3145/epi.2023.nov.09Keywords:
Data literacy, Information literacy, DA, Infolit, Research data management, Quantitative literacy, Systematic reviewsAbstract
This research addresses the growing social importance of data from an educational perspective through data literacy (DL), seeking to integrate it into the broader information literacy (Infolit) movement. For this purpose, a systematic review was carried out of the papers in the main collection of the Web of Science that contain both concepts (DL and Infolit) and that were indexed up until March 2023. External aspects, such as the growth of the research and the identity, nationality, professional scope, and productivity of the authors, were taken into account. In addition, internal aspects, such as context (theory, frameworks, definitions, models, and related disciplines), objectives, methodology, results, conclusions, and recommendations, were analyzed to obtain a detailed perspective of the scientific research process adopted. A synchronic and diachronic analysis of the corpus of selected articles is offered, focusing on the aforementioned aspects. The researchers’ consensus on the urgency of addressing data training both generally and specifically in the different disciplines, languages, environments, and levels is evident. The emergent, multisectoral, and interdisciplinary nature of data literacy as part of Infolit, which is being applied in the education of students at different levels, viz. professionals and citizens, is noted, although the training limitations of students and many professionals are evident. Consequently, it is imperative to include DL in curricula and training programs to contribute to the acquisition and development of these competencies in different areas. To this end, the joint work of teachers, librarians, researchers, and other professionals is imperative. There is a need to deepen the theoretical, practical, and applied fields, as well as to reach a common definition, form a basic model of DL competencies within Infolit, and create submodels that take into consideration the idiosyncrasies of each area of application.
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