Artificial Intelligence and Formative and Shared Assessment in Teacher Education

(1) AI is increasingly being used in teacher education (TE), but there seem to be gaps and deficits regarding how to make good use of AI to enhance learning processes. One possibility comes from the integration of AI in formative and shared assessment (F&SA) processes. Therefore, the purpose of this study was to analyse the results found after the implementation of learning activities that combined the use of AI and F&SA. (2) Methods: A double case study was carried out on two learning tasks applied in TE. The data collection techniques were as follows: activity reports (students), teacher observations, dialogical interviews, focus groups and students’ reflective video diaries. Quantitative and qualitative data were combined. (3) Results: In relation to Case 1, the results show that there was a considerable variety of students’ competences in using AI and that the students managed to improve some aspects of their theoretical frameworks with AI (writing, links between paragraphs and generating new relationships between the topics covered). In addition, the main learnings pointed out by the students were as follows: to be aware of the need to review what AI offers slowly, as it may contain important mistakes, and that using it well can help them to improve their work. In relation to Case 2, the integration of an AI simulator in an F&SA protocol improved the students’ communication skills and the formative power of the assessment protocol created was proven; the students found the integrated AI simulator, the complementary feedback from the teacher and the self-assessment carried out through reflective video diaries on the experience useful. (4) Conclusions: The proper integration of AI with F&SA processes seems to favour the learning and competences of TE students, but teachers are shown to be a key part in making them literate in the appropriate use of AI. More research seems to be needed on this topic.