1. Dialogical Experiences in, for, and from Technologically Mediated Contexts in Teacher Education
- Author
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Taboada, María Beatriz and Álvarez, Guadalupe
- Abstract
This work proposes an analysis of pedagogical experiences developed in the context of university teacher education in dialogue with two different chronotopes: habitual face-to-face teaching modality and exceptional non-face-to-face teaching modality due to the COVID lockdown. We consider here two cases of Language and Literature teacher education courses in two universities in Argentina. Both experiences share the search for an equitable, dialogical interaction, in which there is a recovery of the students' opinions and criteria for the progressive and collaborative elaboration of knowledge. From a qualitative perspective, we resorted to autoethnographic narratives elaborated by the responsible teaching teams of the courses. In the approach we propose, there is a dialogue among different elements of our inquiry: a dialogue between the conceptions that we assume as teachers and researchers about teaching in face-to-face and virtual environments; a dialogue between the conceptualizations and concrete teaching-decisions; between the contexts of performance and the possibilities offered by virtuality; between the pedagogical experiences and the narratives; between the records and other materials that allow us to reconstitute these experiences; and between our voices and the voices of students and graduates who give us back evaluations and sustain the continuity of the dialogue. The analysis accounts for the definition of different chronotopes in the experiences and moments addressed. In both cases, the differences observed respond to contextual factors, particularities of the courses and the previous experiences that the teaching teams have had with ICT. Beyond the above-mentioned differences, for the exceptional non-face-to-face proposals, a greater stability in the proposed sequences and in the dynamics involved is observed in the two experiences, which seeks to generate greater predictability.
- Published
- 2022