Beyond the Black Box: Teacher Competence in Artificial Intelligence

Abstract

The emergence of Artificial Intelligence (AI) in the educational field makes it necessary to review the set of skills and knowledge that teachers should acquire to feel competent in this new area of expertise. The aim of this paper is to propose a conceptual and theoretical framework for the most relevant components that constitute what is known as AI literacy. To facilitate the interpretation of this competence, four theoretical and practical blocks have been identified: (I) What is AI?, (II) How does AI work?, (III) How should AI be used?, and (IV) How to apply this knowledge and these skills? Each block is further divided into operational descriptors to specify the key aspects of teacher competence in AI. The practical use of AI should follow three steps: instruction design, process supervision, and result evaluation. These steps require both knowledge of the first three theoretical blocks and the application of subject-specific competencies related to the content being developed. Although technological evolution enables more intuitive interfaces, it remains essential to define the real scope and limitations of AI to optimize its integration into education and ensure informed and effective use that can also be transmitted to students.