Educación artística y formación de docentesAproximación bibliométrica

  1. FONTAL MERILLAS, OLAIA 1
  1. 1 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

Revista:
RIFOP : Revista interuniversitaria de formación del profesorado: continuación de la antigua Revista de Escuelas Normales

ISSN: 0213-8646 2530-3791

Año de publicación: 2024

Volumen: 38

Número: 99

Páginas: 207-230

Tipo: Artículo

DOI: 10.47553/RIFOP.V99I38.1.104424 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: RIFOP : Revista interuniversitaria de formación del profesorado: continuación de la antigua Revista de Escuelas Normales

Resumen

This article is dedicated to conducting a bibliometric analysis of international scientific production on "Art Education" and "Teacher Training" based on data obtained until December 2023. We analyze the most relevant sources, their temporal progression, and the most representative authors in the field, along with the historical progression of terms related to "Art Education" and "Teacher Training." Concerning the authors, we identify the most representative ones in the field, considering both the number of publications and various metrics of production quality. Additionally, we explore the progression of their scientific production and the institutions to which they belong. Regarding the conceptual structure, we analyze how the network of term co-occurrence is configured based on their presence in abstracts, keywords, titles, etc. We investigate the dimensions in which term clusters are distributed, their historical evolution, and the underlying structure of relevant terms obtained from titles, abstracts, and keywords. The results reveal a temporal evolution with a significant surge in the last decade, accompanied by Spain's leadership in scientific publications and media. Regarding term clusters, considering centrality, density, and network configuration, several distinctly differentiated clusters are identified, suggesting a broad thematic dispersion and breadth, along with clearly defined nodes in the thematic evolution of scientific production, where heritage emerges as one of the main emerging topics.

Referencias bibliográficas

  • Aguilera, D. y Ortiz-Revilla, J. STEM vs. STEAM Education and Student Creativity: A Systematic Literature. Education Sciences, 11, 331. https://doi.org/10.3390/educsci11070331
  • Akaike, H. (1973). Proceedings of the Second International Symposium on Information Theory. En B. N. Petrov y F. Csaki (Eds.), Information Theory and an Extension of the Maximum Likelihood Principle (pp. 267-281).
  • Aria, M. & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  • Bremmer, M., Heijnen, E. y Kersten, S. (2021). Teacher as conceptual artist. International Journal of Art & Design Education, 40(1), 82-98. https://doi.org/10.1111/jade.12318
  • Caeiro, M., Callejón, M. D. y Chacón, P. (2021). El diseño de métodos poéticos y autopoéticos en Educación Artística: articulando metodologías y metodografías. Arte, Individuo y Sociedad, 33(3), 769-790. https://doi.org/10.5209/aris.69263
  • Callon, M., Courtial, J. P., Turner, W. A. y Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191-235. https://doi.org/10.1177/053901883022002003
  • Conte, E., Habowski, A. C., Piedade, J. D. A. y Milbradt, C. (2021). Art-education and its developments in pedagogical training. Acta Scientiarum. Education, 43. https://doi.org/10.4025/actascieduc.v43i1.47923
  • Craven, P. y Wahba, G. (1978). Smoothing noisy data with spline functions. Numerische Mathematik, 31, 377-403.
  • Fontal, O. y Ibáñez, A. (2017). La investigación en Educación Patrimonial. Evolución y estado actual a través del análisis de indicadores de alto impacto. Revista de educación, 375, 184-214.
  • Gao, X. y Guan, J. (2009). Networks of scientific journals: An exploration of Chinese patent data. Scientometrics, 80(1), 283-302.
  • Glänzel, W. (2001). National characteristics in international scientific co-authorship relations. Scientometrics, 51(1), 69-115.
  • Guercia, C. U. y París, A. C. (2013). Formación de maestros en educación artística y formación artística de maestros. Los patrimonios migratorios en la enseñanza obligatoria. Educación artística: revista de investigación, 4, 301-316.
  • Güneş, N., Aksoy, Ş. y Özsoy, V. (2020). The role of the a/r/tography method in art teacher training. Universal Journal of Educational Research, 8(10). https://doi.org/10.13189/ujer.2020.081063
  • Hawari, A. D. M. y Noor, A. I. M. (2020). Project based learning pedagogical design in STEAM art education. Asian Journal of University Education, 16(3), 102-111. https://doi.org/10.24191/ajue.v16i3.11072
  • Huerta Ramón, R. V. (2020). Educación artística para formar docentes en derechos humanos y diversidad sexual. Pulso, 43, 119-136
  • Hurvich, C. M., Simonoff, J. S. y Tsai, C. L. (1998). Smoothing Parameter Selection in Nonpara-metric Regression Using an Improved Akaike Information Criterion. Journal of the Royal Statistical Society, 60, 271-293.
  • Kim, N. (2023). Reformulating Crafts in Art Education Curriculum. Art Education, 76(1), 44-49. https://doi.org/10.1080/00043125.2022.2131203
  • Kraehe, A. M. (2020). Dreading, pivoting, and arting: The future of art curriculum in a post-pandemic world. Art Education, 73(4), 4-7. https://doi.org/10.1080/00043125.2020.1774320
  • Leonard, N. (2020). Entanglement art education: Factoring ARTificial intelligence and nonhumans into future art curricula. Art Education, 73(4), 22-28. https://doi.org/10.1080/00043125.2020.1746163
  • Leonard, N. (2021). Emerging artificial intelligence, art and pedagogy: exploring discussions of creative algorithms and machines for art education. Digital Culture & Education, 13(1).
  • Marín-Viadel, R. y Roldán, J. (2019). A/r/tografía e Investigación Educativa Basada en Artes Visuales en el panorama de las metodologías de investigación en Educación Artística. Arte, Individuo y Sociedad, 31(4), 881-895. https://doi.org/10.5209/aris.63409
  • Marx, W., Bornmann, L., Barth, A. y Leydesdorff, L. (2014). Detecting the Historical Roots of Research Fields by Reference Publication Year Spectroscopy (RPYS). Journal of the American Society for Information Science and Technology, 65(4), 1-38.
  • McCain, K. W. (1991). Mapping economics through the journal literature: An experiment in journal cocitation analysis. Journal of the American Society for Information Science, 42(4), 290
  • Mullet, D. R., Willerson, A., Lamb, K. N. y Kettler, T. (2016). Examining teacher perceptions of creativity: A systematic review of the literature. Thinking Skills and Creativity, 21, 9-30. https://doi.org/10.1016/j.tsc.2016.05.001
  • Persson, O. (2011). BibExcel, v. 2011-10-12 [computer program]. Available at www.worldscientific.com/worldscibooks/10.1142/q0118
  • Pente, P., Adams, C. y Yuen, C. (2022). Artificial Intelligence, ethics, and art education in a posthuman world. En Global Media Arts Education: Mapping Global Perspectives of Media Arts in Education (pp. 197-211). Springer International Publishing.
  • R Core Team. (2021). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria.
  • Razi, A. y Zhou, G. (2022). STEM, iSTEM, and STEAM: What is next? International Journal of Technology in Education, 5(1), 1. https://doi.org/10.46328/ijte.119
  • Salido-López, P. V. (2021). La Educación Artística ante el reto de enseñar a aprender: un estudio de caso en la formación de docentes. Arte, Individuo y Sociedad, 33(4). https://doi.org/10.5209/aris.72439
  • SAS Institute Inc. (2023). SAS v. 9.4 User’s Guide. SAS Institute Inc. Shukshina, L. V., Gegel, L. A., Erofeeva, M. A., Levina, I. D., Chugaeva, U. Y. y Nikitin, O. D. (2021). STEM and STEAM education in Russian Education: Conceptual framework. Eurasia Journal of Mathematics, Science and Technology Education, 17(10).
  • Silva Díaz, F. R., Fernández-Ferrer, G., Vázquez-Vilchez, M., Ferrada, C., Narváez, R. y Carrrillo-Rosúa, J. (2022). Tecnologías Emergentes en la Educación STEM. Análisis bibliométrico de publicaciones en Scopus y WoS. (2010-2020), Bordón, 74(4), 25-44. https://doi.org/10.13042/Bordon.2022.94198 Song, B. y Koo, A. (2022). Paradigm shift: Artificial intelligence, contemporary art, and implications for gifted arts education. Journal of Gifted Education in Arts, 8, 5-38. https://doi.org/10.22752/KRIGA.2022.08.001
  • van Eck N. J. y Waltman L. (2010). Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping. Scientometrics, 84(2), 523–538.
  • Videla, R., Aguayo, C. y Veloz, T. (2021). From STEM to STEAM: An enactive and ecological continuum. In Frontiers in Education, 6, p. 709560. https://doi.org/10.3389/feduc.2021.709560
  • White, D. y McCain, K. (1998). Visualizing a discipline: An author co-citation analysis of information science. Journal of the American Society for Information Science, 49(4), 327-355. https://doi.org/10.1002/(SICI)1097- 4571(19980401)49:4<327::AID-ASI4>3.0.CO;2-4
  • Zhang, Q., Wu, Q., Jiang, K. y Shan, C. (2024). The arts in early childhood teacher education in China: a question of curriculum balance, Asia-Pacific Journal of Teacher Education, 52. https://doi.org/10.1080/1359866X.2023.2298302
  • Zhang, W., Shankar, A. y Antonidos, A. (2022). Modern art education and teaching based on artificial intelligence. Journal of Interconnection Networks, 22(Supp01), 2141005. https://doi.org/10.1142/S021926592141005X
  • Zhao, D. y Strotmann, A. (2008). Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic-coupling analysis. Journal of the American Society for Information Science, 59(1998), 2070-2086. https://doi.org/10.1002/asi.20910