A personalized feedback system to support teacher training
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, th...
Main Authors: | , |
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Format: | Article |
Language: | English |
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Sciendo
2023-06-01
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Series: | Research on Education and Media |
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Online Access: | https://doi.org/10.2478/rem-2023-0005 |
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author | De Angelis Marta Miranda Sergio |
author_facet | De Angelis Marta Miranda Sergio |
author_sort | De Angelis Marta |
collection | DOAJ |
description | 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.). |
first_indexed | 2024-04-10T17:13:01Z |
format | Article |
id | doaj.art-7d350608a46840408df9ccaa57d01b52 |
institution | Directory Open Access Journal |
issn | 2037-0849 |
language | English |
last_indexed | 2024-04-10T17:13:01Z |
publishDate | 2023-06-01 |
publisher | Sciendo |
record_format | Article |
series | Research on Education and Media |
spelling | doaj.art-7d350608a46840408df9ccaa57d01b522023-02-05T19:46:25ZengSciendoResearch on Education and Media2037-08492023-06-01151303910.2478/rem-2023-0005A personalized feedback system to support teacher trainingDe Angelis Marta0Miranda Sergio1University of Molise, ItalyUniversity of Salerno, ItalyThis 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.).https://doi.org/10.2478/rem-2023-0005teacher educationin-service teacher trainingfeedbacktechnologyteaching quality |
spellingShingle | De Angelis Marta Miranda Sergio A personalized feedback system to support teacher training Research on Education and Media teacher education in-service teacher training feedback technology teaching quality |
title | A personalized feedback system to support teacher training |
title_full | A personalized feedback system to support teacher training |
title_fullStr | A personalized feedback system to support teacher training |
title_full_unstemmed | A personalized feedback system to support teacher training |
title_short | A personalized feedback system to support teacher training |
title_sort | personalized feedback system to support teacher training |
topic | teacher education in-service teacher training feedback technology teaching quality |
url | https://doi.org/10.2478/rem-2023-0005 |
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