A strategic approach to information literacy: data literacy. A systematic review

María Pinto, David Caballero-Mariscal, F.-J. García-Marco, Carmen Gómez-Camarero
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Abstract

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.
信息素养的战略方法:数据素养。系统回顾
本研究通过数据扫盲(DL)从教育角度探讨了数据日益增长的社会重要性,并试图将其纳入更广泛的信息扫盲(Infolit)运动。为此,我们对《科学网》(Web of Science)主要收录的包含这两个概念(DL 和 Infolit)的论文进行了系统性审查,并将其编入了截至 2023 年 3 月的索引。外部因素,如研究的发展以及作者的身份、国籍、专业范围和工作效率等,都被考虑在内。此外,还分析了内部因素,如背景(理论、框架、定义、模型和相关学科)、目标、方法、结果、结论和建议,以获得所采用的科学研究过程的详细视角。本文对所选文章的语料库进行了同步和异步分析,重点关注上述方面。研究人员一致认为,迫切需要在不同学科、语言、环境和层次中普遍和具体地开展数据培训。尽管学生和许多专业人员在培训方面的局限性显而易见,但人们注意到数据扫盲作为信息素养的一部分所具有的新兴性、多部门性和跨学科性,它正被应用于不同层次的学生,即专业人员和公民的教育中。因此,必须将数字语言纳入课程和培训计划,以促进在不同领域获得和发展这些能力。为此,教师、图书馆员、研究人员和其他专业人员的共同努力势在必行。有必要深化理论、实践和应用领域,并达成一个共同的定义,在 Infolit 中形成数字图书馆能力的基本模式,并创建考虑到各应用领域特质的子模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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