Molinari, Irene
(2023)
Analysis of an interdisciplinary approach for teaching artificial intelligence in secondary schools through co-planning and co-teaching methodologies: a proposal for the open schooling model of the FEDORA project.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Physics [LM-DM270]
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Abstract
This thesis is part of the FEDORA project (Future-oriented Science EDucation to enhance Responsibility and engagement in the society of Acceleration and uncertainty), a three-year project funded by the EU that started in September 2020. The project involves 6 partner institutions from five European countries coordinated by the University of Bologna. The main objective of FEDORA is to develop a “model for science education for the society of acceleration and uncertainty” (https://www.fedora-project.eu/). To achieve this, the project partners established networks of schools at the European level, called "open schooling networks", to implement interdisciplinary STEM learning-teaching modules on emerging themes such as artificial intelligence, climate change, and quantum computers, and study the implementation of teaching practices. The actions and results of the project provide recommendations for anticipatory policies to promote visionary attitudes towards open schooling and guiding concrete institutional transformations1. The work of this thesis focused on following the implementation of the FEDORA module on artificial intelligence at the “Liceo Einstein” in Rimini and the subsequent laboratory between art, creativity, and artificial intelligence (AI Atelier), conceived by the school’s teachers themselves. The research work consists of the investigation of co-planning and co-teaching methodologies implemented in the two projects. This is accomplished by directly observing the courses and later interviewing the teachers, with the goal of highlighting the benefits of this type of teaching as well as the difficulties faced in implementing it within a real school context. The overarching objective is to suggest potential solutions for improving future courses and potentially raising awareness among policymakers about the necessary reforms to align education with the demands of a society characterized by acceleration.
Abstract
This thesis is part of the FEDORA project (Future-oriented Science EDucation to enhance Responsibility and engagement in the society of Acceleration and uncertainty), a three-year project funded by the EU that started in September 2020. The project involves 6 partner institutions from five European countries coordinated by the University of Bologna. The main objective of FEDORA is to develop a “model for science education for the society of acceleration and uncertainty” (https://www.fedora-project.eu/). To achieve this, the project partners established networks of schools at the European level, called "open schooling networks", to implement interdisciplinary STEM learning-teaching modules on emerging themes such as artificial intelligence, climate change, and quantum computers, and study the implementation of teaching practices. The actions and results of the project provide recommendations for anticipatory policies to promote visionary attitudes towards open schooling and guiding concrete institutional transformations1. The work of this thesis focused on following the implementation of the FEDORA module on artificial intelligence at the “Liceo Einstein” in Rimini and the subsequent laboratory between art, creativity, and artificial intelligence (AI Atelier), conceived by the school’s teachers themselves. The research work consists of the investigation of co-planning and co-teaching methodologies implemented in the two projects. This is accomplished by directly observing the courses and later interviewing the teachers, with the goal of highlighting the benefits of this type of teaching as well as the difficulties faced in implementing it within a real school context. The overarching objective is to suggest potential solutions for improving future courses and potentially raising awareness among policymakers about the necessary reforms to align education with the demands of a society characterized by acceleration.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Molinari, Irene
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
DIDATTICA E STORIA DELLA FISICA
Ordinamento Cds
DM270
Parole chiave
Artificial Intelligence,Interdisciplinarity,Co-planning,Co-teaching,Secondary Schools,FEDORA,Open Schooling
Data di discussione della Tesi
29 Settembre 2023
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Molinari, Irene
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
DIDATTICA E STORIA DELLA FISICA
Ordinamento Cds
DM270
Parole chiave
Artificial Intelligence,Interdisciplinarity,Co-planning,Co-teaching,Secondary Schools,FEDORA,Open Schooling
Data di discussione della Tesi
29 Settembre 2023
URI
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