## 5 Conclusions  
The integration of generative AI into education signifies a transformative paradigm shift, offering unprecedented opportunities for personalized, real-time, and interactive learning experiences. Notably, the AI textbooks promoted by the Ministry of Education in Korea have predominantly targeted elementary, middle, and high school levels. This study, focusing on regular college courses, has uniquely explored the innovative potential and inherent challenges of implementing AI-based educational tools in higher education. It is particularly pioneering in its assessment of the applicability of generative AI to traditional university subjects, including assistive engineering--a national examination subject that demands a high degree of precision. The findings of this study are follows:  
First, this study has provided a comprehensive analysis of the integration of AI-driven digital textbooks into higher education, specifically focusing on their implementation in health sciences education. The comparison between traditional pedagogy and AI-enhanced self-regulated learning methods has yielded valuable insights into the opportunities and challenges posed by generative AI technologies in academic settings. This section synthesizes the key findings, implications, and recommendations derived from the research, offering a robust perspective on the role of AI in reshaping educational paradigms. Second, the quantitative results from the study indicated no statistically significant differences in academic achievement between the Traditional Learning Group (TLG) and the AI Learning Group (ALG). Although the AI-driven methods provided innovative approaches to learning, their immediate impact on measurable academic outcomes, such as test scores and project performance, was equivalent that of traditional methods. This neutrality in results underscores the importance of contextual and pedagogical adaptations to optimize AI tools for improved academic results. Third, the qualitative analysis revealed that AI textbooks offered substantial benefits in terms of fostering student engagement. Participants in the ALG expressed high levels of satisfaction with features such as real-time feedback, personalized learning pathways,and interactive content delivery. The adaptive nature of the AI platform allowed learners to explore the content at their own pace, contributing to a more engaging and self-directed educational experience. AI digital textbooks facilitate customized learning pathways, enhance engagement through adaptive content, and provide educators with data-driven insights. However, their effective integration necessitates a multifaceted approach that addresses technical, ethical, and practical dimensions. The key challenges include the development of robust frameworks to address digital disparities, ensuring the accuracy and reliability of AI-generated content, and mitigating the risks related to data privacy and security. Additionally, equitable access to technological resources remains a significant concern. The risks associated with algorithmic bias and over-reliance on AI tools highlight the need for human-centric educational strategies that preserve critical thinking and problem-solving skills. Furthermore, the financial burden of adopting and maintaining AI systems underscores the necessity for scalable, cost-effective solutions tailored to diverse educational contexts. Maximizing the potential of generative AI in education requires the establishment of a comprehensive management framework. This framework must encompass rigorous training programs for educators, ethical guidelines for data usage, and mechanisms for the continuous evaluation and improvement of AI systems. Collaborative partnerships among key stakeholders--educators, technologists, policymakers, and researchers--are vital to aligning technological capabilities with educational objectives and fostering an environment that prioritizes innovation and inclusivity.