Education Sciences, Год журнала: 2025, Номер 15(2), С. 186 - 186
Опубликована: Фев. 5, 2025
Data science education is an interdisciplinary and multidisciplinary field, with curricula continually evolving to meet societal needs. This paper aims report a bibliometric analysis focused on the pedagogical aspects teaching/learning strategies employed in data curriculum design, emphasizing contributions from key authors, publication sources, affiliations, content, cited documents. The draws metadata documents published over 20-year period (2005–2024), encompassing total of 1245 sourced Scopus scientific database. Additionally, scoping review 20 articles was conducted identify skills, topics, courses education. findings reveal growing interest increasingly approach. Advances artificial intelligence related such as linked data, semantic web, ontologies, machine learning, are shaping development curricula. main challenges include creation up-to-date competitive curricula, integrating training at early educational stages (K-12, secondary schools, pre-collegiate), leveraging data-driven technologies, defining profile scientist. Furthermore, availability vast amounts open, linked, restricted along advancements significantly influencing research field
Язык: Английский