Bibliometric analysis of pedagogical content knowledge: Countries, authors, and fields of knowledge
David Santibáñez 1 * , Alejandro Vega 2 3 , Hernán Cofré 4 , Natalia Salas 1 , José Adsuar 5 6
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1 Centro de Investigación en Psicología, Educación y Familia CIPEF, Facultad de Educación, Psicología y Familia, Universidad Finis Terrae, Santiago, CHILE2 Centro de Investigación en Educación de Calidad para la Equidad, Universidad Central de Chile, Santiago, CHILE3 Facultad de Ciencias Empresariales, Universidad Arturo Prat, Iquique, CHILE4 Instituto de Biología, Facultad de Ciencias, Pontificia Universidad Católica de Valparaíso, Valparaíso, CHILE5 Faculty of Sport Sciences, University of Extremadura, Caceres, SPAIN6 Faculdade de Motricidade Humana, Universidade de Lisboa, Lisboa, PORTUGAL* Corresponding Author

Abstract

Pedagogical content knowledge (PCK) is a key construct that emerges as distinct from both pedagogical and disciplinary knowledge, essential for understanding how teacher training should be structured. Since its genesis, it has been the subject of thousands of studies, and although there are reviews within each disciplinary PCK area (e.g., PCK in mathematics), there are no bibliometric analyses that allow for the recognition of trends and gaps in productivity in the field of teaching in general. The aim of the present study was to identify such patterns through a review of high-impact specialized journals. For this purpose, 1,942 Web of Science articles were analyzed with various bibliometric parameters and digital visualization software. The results show a series of trends not described in previous literature. The implications for research on teacher training are discussed, considering the initial intent behind the construct's formulation and its relevance to contemporary educational challenges, and new lines of research are proposed.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Review Article

EURASIA J Math Sci Tech Ed, Volume 21, Issue 2, February 2025, Article No: em2583

https://doi.org/10.29333/ejmste/15953

Publication date: 13 Feb 2025

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Article Downloads: 141

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