Providing academic writing feedback assisted by Generative Artificial Intelligence in initial teacher education contexts
Autor
Ossa, Carlos
Willatt, Carlos
Resumen
This paper presents the implementation of Generative Artificial Intelligence (GAI) for providing descriptive feedback on 578 responses to pedagogical cases written by a cohort of students (n = 347) from seven initial teacher education programs at a Faculty of Education in Chile. To deliver feedback on these responses, a process called RECaP-GPT was developed, which incorporates human action and utilizes ChatGPT-4 as a teaching support tool. The feedback provided is based on pre-established criteria known to the students. The feedback generated by the GAI was validated and delivered to the students to enhance their evidence of learning throughout a semester of classes. The paper discusses the capacity of this tool to offer formative and extensive feedback on students' written work in a short period of time. Furthermore, it raises limitations observed in the implementation process that necessitate further research.
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