TEACHING AND EVALUATION METHODOLOGIES-REIKIAVIK

In the age of artificial intelligence, success depends, more than ever, on the capabilities of the human being. (…) We must consider AI not as a shortcut, but as a context and a catalyst for deeper learning, and educators must play a central role in shaping that future.” – AI and the future of Pedagogy (2025); topical report on the impact and challenges presented by AI in education. Through a focus on practice and applicability, this course responds to the growing concern among educators for teaching and assessment methodologies that are able to respond to the problems that arise from the incorrect use of AI by students. To do this, we start from the idea of greater consensus at present: training in methodologies based on scientific evidence. Based on the latter, it is explored and worked on following 2 classes that, although opposed, must coexist and complement each other in current teaching: 1) “methodologies integrated with AI”, and 2) “methodologies resistant to AI”. In turn, this training organizes both classes of methodologies to be taught in response to 5 areas of consensus where AI is causing problems in the development of students. Internationally recognized areas by scientific literature, as well as by reference institutions such as UNESCO. These are:
Metacognition and autonomy. Analytical skills. Memory and creation of mind maps. Anxiety and dependence on AI. Intellectual isolation and homogenization. The final objective of the course is to provide teachers with the pedagogical tools necessary to navigate this cultural and technological transformation, all from the critical focus on the most affected areas among students due to the inappropriate use of AI. This work culminates with a final project in the form of a proposal for the pedagogical redesign of the teacher’s classes.