ChatGPT as a reflection tool to promote the lesson planning competencies of pre-service teachers

Link:
Autor/in:
Verlag/Körperschaft:
University of Bari Aldo Moro
Erscheinungsjahr:
2024
Medientyp:
Text
Schlagworte:
  • artificial intelligence
  • chatGPT
  • lesson planning
  • teacher competencies
  • pre-service teachers
Beschreibung:
  • In our study, set against the backdrop of rapidly advancing AI technology, we examine how ChatGPT, can support pre-service teachers (PSTs) in creating lesson plans and contribute to the improvement of university mathematics teacher education. We implement various prompting techniques that help PSTs cultivate digital professional competencies when interacting with ChatGPT in AI-assisted lesson planning. We evaluated the AI-generated lesson plans and the PSTs' modifications to these plans. Our initial results indicate that the quality of both the AI-generated lesson plans and the PSTs' modifications to them can vary and interact with each other. Overall, our findings suggest that effective prompting techniques can aid PSTs in enhancing their lesson planning competencies.
  • In our study, set against the backdrop of rapidly advancing AI technology, we examine how ChatGPT,
    can support pre-service teachers (PSTs) in creating lesson plans and contribute to the improvement
    of university mathematics teacher education. We implement various prompting techniques that help
    PSTs cultivate digital professional competencies when interacting with ChatGPT in AI-assisted
    lesson planning. We evaluated the AI-generated lesson plans and the PSTs' modifications to these
    plans. Our initial results indicate that the quality of both the AI-generated lesson plans and the PSTs'
    modifications to them can vary and interact with each other. Overall, our findings suggest that
    effective prompting techniques can aid PSTs in enhancing their lesson planning competencies.
Lizenz:
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsinformationssystem der UHH
Interne Metadaten
Quelldatensatz
oai:www.edit.fis.uni-hamburg.de:publications/361e7c1c-f90c-404d-a15f-e93cf67e2e98