This study investigates the effectiveness of integrating Text Generative AI as a supplementary teaching tool within a blended learning approach, aiming to provide educators with additional pedagogical flexibility and enhance classroom efficiency. Employing an experimental methodology with the 400 participants of control and experimental groups, the study utilized pre-test and post-test evaluations, stratified sampling, and impartial reviews of prepared scripts. The intervention incorporated AI tools like ChatGPT, Copilot, and Gemini as co-teaching assistants, applied only to the experimental group, with a unique integration strategy designed to seamlessly blend these tools into the instructional process. Findings revealed that the AI-integrated approach, that allows students to self-learn a portion of the academic contents using AI, enabled deeper learning, allowing physical teachers to cover 25 % more content, resulting in enhanced understanding, higher grades, and increased student satisfaction. The study, however, is limited to exploring cognitive and behavioral changes based on written assessments and decoy grades only. Future studies hold potential to explore more complex relationships and allow a geographically stratified sample for deeper insights. But regardless of the limitations, this research not only offers quantitative validation of AI's role in education, addressing gaps in previous studies by empirically assessing the effectiveness of AI integration and its impact on student satisfaction, but also works as a foundational study for future authors in exploring this phenomenon.
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