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A personalized feedback system to support teacher training Cover

A personalized feedback system to support teacher training

Open Access
|Jan 2023

Abstract

This paper aims to illustrate an automated system developed to give formative and personalized feedback to teachers in training. It is an expert system (Paviotti, Rossi & Zarka, 2012) that uses concrete examples, cases and scenarios to guide the engaged learners (Leake, 1996). In this regard, this system is able to create questionnaires, deliver them, collect and analyze data, send feedback to the participants to provide information about their beliefs and behaviors about teaching and learning processes. Far from constituting an assessment of teaching practices, the automated feedback demonstrates its usefulness in identifying teachers’ mindframes at an early stage, so as to be able to implement more specific and personalized training. This allows its application to be extended to further training areas as well as constituting an effective approach for need analysis and a preparatory action for numerous training activities (guided discussion with experts, observation on practice, modeling, etc.).

DOI: https://doi.org/10.2478/rem-2023-0005 | Journal eISSN: 2037-0849 | Journal ISSN: 2037-0830
Language: English
Page range: 30 - 39
Published on: Jan 28, 2023
Published by: SIREM (Società Italiana di Ricerca sull’Educazione Mediale)
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2023 Marta De Angelis, Sergio Miranda, published by SIREM (Società Italiana di Ricerca sull’Educazione Mediale)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.