Teachers training to integrate hypermediatic languagesat school: A case study comprising three public Federal Universities in Brazil
International Journal of Development Research
Teachers training to integrate hypermediatic languagesat school: A case study comprising three public Federal Universities in Brazil
Received 28th April, 2021; Received in revised form 29th May, 2021; Accepted 30th June, 2021; Published online 25th July, 2021
Copyright © 2021, Lucila Pesce et al. 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.
This article derives from an inter-institutional research developed with the economic support of CNPq (a national research funding agency), toinvestigate the initial training of teachers for the pedagogical use of Information and Communication Technologies (ICT). The qualitative methodology adopted the comparative case studyof three pedagogy courses from federal public universities in Brazil. The research informants were students, teachers, and course coordinators. The research developed a thematic analysis of the answers to the interviews. Thisresearch also developed a document analysis of course syllabus that discuss “Education and Technology”, as well aspedagogical programs of these courses. The discussion indicates that there are substantial differences in the symbolic capital amassed by different higher education institutions related to teacher preparation to integrate ICT to social practices at school. Considering this finding, it is important to ensure that PUPs offer one mandatory course specifically aimed at providing theoretical discussion of and practical experience with “Education and ICT”. However, a mandatory course on “Education and ICT” is not enough. Universities must also provide the infrastructure (hardware, software, internet connection) to enable those classes to go beyond theoretical considerations, an issue raised during data analysis.