Flipped Classroom 2.0 Integration of AI Assistants into the Model of Student Independent Preparation

Artificial intelligence assistants are changing how students prepare before class. This shift raises questions about effort, depth, and independent reasoning. This study examines AI assistants within the flipped classroom preparation stage specifically. It aims to identify how preparation time, self-regulation, and understanding change under this influence. A qualitative doctrinal design guided the research, supported by document analysis. Materials included legal sources, institutional policies, and recent scholarly literature. Results show faster preparation, stronger self-regulation among weaker students, and reduced reasoning depth. They also reveal an emerging division of responsibility between students and AI tools. The study recommends structured task design that preserves independent judgment alongside efficiency gains. Institutions should require justification steps that reveal genuine student reasoning during preparation. These findings support balanced, rule-based integration rather than unrestricted or prohibited AI use. The research contributes a structural framework for responsible preparation design. Legal education particularly benefits from protecting reasoning practice within this evolving preparation model.

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