The emergence of Artificial Intelligence (AI) in the field of Higher Education is entailing a revolution that affects both the work of students and teachers. The use of tools based on natural language processing such as chatGPT requires a deep reflection on the way in which we face the teaching and learning processes with the help of these new resources. Specifically, this paper presents a project that focuses on assessment processes in order to analyse the changes that have occurred and the strategies that can be used to deal with them. The project is funded by the Vice-Rectorate for Quality, Teaching Innovation and Undergraduate Studies of the University of Granada and is being developed in the current academic year.

The focus of this work approaches the process of analysis of the new assessment scenarios from two different and complementary perspectives.

On the one hand, the aim is to investigate the design of strategies that enable the assessment of student competences, guiding them in the use of reliable sources and references that support and argue the productions that they can generate with the help of AI, encouraging critical thinking. Oral evidence and the ability to argue the work produced, as well as peer assessment, will also take on special relevance. In short, it is a question of adapting the design of continuous assessment strategies in such a way as to achieve an authentic assessment of learning, taking into account the use that students currently make of AI tools.

The second perspective is to use assessment tools as teachers that, with the support of AI, help us to improve the efficiency of our assessment processes. In this sense, we intend to experiment with the design of rubrics, the development of tests or personalised feedback with the support of AI, always supporting our decisions but without substituting them.

With this double perspective, the fundamental objective is to design these assessment strategies in order to be able to put them into practice in our subjects and evaluate their results. With all this, we will be able to draw up a series of recommendations on assessment strategies that coexist with the use of AI by students and take advantage of its benefits for teachers as well.

To this end, the project has been structured in five phases: analysis of the situation, design of assessment strategies, implementation of assessment strategies, evaluation of experiences and, finally, generation of training content on recommendations in relation to assessment and AI.

The main aim of this paper is presenting the main methodological approaches of the project as well as the progress made to date.

Keywords: Educational technology, Artificial intelligence, Assessment.