| Abstract [eng] |
The development of artificial intelligence in the context of general education is changing not only teaching and learning tools, but also the logic of knowledge construction, transmission, and assessment. It is becoming increasingly difficult for teachers to distinguish between knowledge constructed independently by the student, technological assistance, and algorithmically generated content. This tension is particularly evident in mathematics education, which is characterized by strong regulation of knowledge, clear assessment criteria, and an emphasis on procedural understanding. In this thesis, the work of mathematics teachers is analysed as knowledge gatekeeping — a process in which decisions are made about which forms of knowledge, solution methods, and justifications can be regarded as legitimate school knowledge. The research problem is formulated through the question: how are mathematics teachers’ epistemic orientations reconstructed in the context of artificial intelligence use in general education, and how do they become visible in didactic assessment dilemmas? The aim of the thesis is to reconstruct mathematics teachers’ epistemic orientations. The thesis consists of theoretical and empirical parts. In the theoretical part, knowledge gatekeeping is analysed through Bernstein’s theory of the pedagogic device, the meta-principles of classification and framing, and Chevallard’s anthropological theory of the didactic, especially the concept of praxeology. This theoretical approach makes it possible to analyse how teachers draw boundaries between legitimate and illegitimate mathematical knowledge, how they regulate the presentation of students’ solutions, and how they assess the relationship between technique, justification, and theoretical understanding. The empirical part applies a qualitative methodology based on vignettes and semi-structured interviews with mathematics teachers. The vignettes present hypothetical situations that are nevertheless close to school mathematics practice, in which students’ solutions are produced with the help of generative artificial intelligence. The empirical analysis revealed that AI does not eliminate the role of mathematics teachers as knowledge gatekeepers; rather, their epistemic orientations differ according to how they draw the boundaries and define the forms of legitimate mathematical knowledge. For some teachers, a legitimate solution is associated with the school curriculum, the technique taught, and the logic of examination-based assessment. For others, it is associated with the student’s ability to understand, explain, and justify the chosen method, even if that method was suggested by artificial intelligence. The study also showed that, in the context of AI, the framing of knowledge becomes an important mechanism of gatekeeping. |
