Authors
- Mnatsakanyan Vilen V.
- Stesik Ivan A.
Annotation
This article proposes and empirically tests a model for preparing future computer science teachers that shifts the focus of assessment from learning outcomes to the process of students’ interaction with artificial intelligence, based on process-related evidence such as prompt logs, revision trajectories, screencasts, and reflective commentaries.
An experimental study conducted in a pedagogical college demonstrated improvements in prompt quality, higher success rates in tasks resistant to outcome substitution, and increased professional and ethical awareness among students.
How to link insert
Mnatsakanyan, V. V. & Stesik, I. A. (2026). ARTIFICIAL INTELLIGENCE IN ASSESSING LEARNING ACHIEVEMENTS IN COMPUTER SCIENCE: PREPARING FUTURE TEACHERS TO USE AI TUTORS AND AUTOMATED ASSESSMENT SYSTEMS Bulletin of the Moscow City Pedagogical University. Series "Pedagogy and Psychology", № 1 (75), 33. https://doi.org/10.24412/2072-9014-2026-175-33-41
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