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Teaching Where Algorithms End

Nemat KushvaktovTermez University of Economics and Service, Termez, UzbekistanR. N. RavikumarMarwadi University, Rajkot, IndiaIlmira JumaniyazovaS. AarthiMarwadi University, Rajkot, IndiaBeknazarova Khadicha SuyunovnaShakhrisabz State Pedagogical Institute, Shakhrisabz, UzbekistanBaykunusova Gulmira YuldibayevnaTashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent, Uzbekistan
2026
ABI

Аннотация

Vocational education and apprenticeship systems are now becoming more and more automated and data-driven to aid in the evaluation, feedback, and skill acquisition process through Artificial Intelligence. Although AI will improve efficiency, scaling, and personalization, it will be weak when it comes to contextual judgment, ethical reasoning, and relational learning. The current chapter analyzes the AI-mediated apprenticeships not only in humanistic context but also contends that teachers are not being substituted, but that they are also being re-defined. The concept of apprenticeships is presented as both skill acquisition and formation processes that comprise professional identity, values, and belonging. Based on the interdisciplinary understanding of the vocational education, learning sciences, and the interaction between humans and Artificial Intelligence, the chapter puts educators in the position of interpreters and ethical intermediaries that contextualize recommendations provided by an algorithm in the context of real work.

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