This study evaluates the impact of generative artificial intelligence (GenAI) on students' learning experiences and perceptions through a master's-level course in instructional design. The research used an action research methodology, including pre- and post-course surveys, reflective assignments, class discussions, and a questionnaire. The AI-Ideas, Connections, Extensions (ICE) Framework was used to assess students' cognitive engagement with GenAI. Findings revealed that incorporating GenAI increased students' comfort with the technology and their understanding of its ethical implications. Most students were at the initial engagement level, with growing awareness of GenAI's limitations and ethical issues. Course reflections highlighted themes of improved teaching strategies, personal growth, and the practical challenges of integrating GenAI responsibly. Research limitations include a small sample size, which may affect the generalizability of results. The study is original in integrating GenAI into a master's-level instructional design course, assessing both practical and ethical implications. The AI-ICE Framework provides insights into how GenAI influences learning experiences and perceptions, bridging the gap between theoretical understanding and real-world application. The study suggests that responsible GenAI use in education requires strategies and best practices to ensure effective and ethical integration. The course design included project-oriented tasks, hands-on experiential learning, and reflection to enhance students' understanding of GenAI. Data collection was qualitative, including reflective assignments, class discussions, and surveys. The AI-ICE Framework was used to analyze students' cognitive engagement with GenAI, emphasizing the process rather than just the output. Results showed a significant increase in students' comfort with GenAI and understanding of its ethical implications. Course reflections highlighted themes of enhanced teaching strategies, personal and professional growth, and challenges in GenAI integration. The study's findings suggest that integrating GenAI into educational contexts can enhance learning experiences and perceptions. However, it also highlights the need for ethical considerations and responsible use of GenAI. The study recommends strategies for integrating GenAI into educational settings, emphasizing ethical considerations and responsible use. Future research should aim to recruit a larger cohort to validate and expand upon initial observations. The study contributes to the growing body of knowledge on GenAI practices in educational settings, offering insights into how GenAI influences learning experiences and perceptions.This study evaluates the impact of generative artificial intelligence (GenAI) on students' learning experiences and perceptions through a master's-level course in instructional design. The research used an action research methodology, including pre- and post-course surveys, reflective assignments, class discussions, and a questionnaire. The AI-Ideas, Connections, Extensions (ICE) Framework was used to assess students' cognitive engagement with GenAI. Findings revealed that incorporating GenAI increased students' comfort with the technology and their understanding of its ethical implications. Most students were at the initial engagement level, with growing awareness of GenAI's limitations and ethical issues. Course reflections highlighted themes of improved teaching strategies, personal growth, and the practical challenges of integrating GenAI responsibly. Research limitations include a small sample size, which may affect the generalizability of results. The study is original in integrating GenAI into a master's-level instructional design course, assessing both practical and ethical implications. The AI-ICE Framework provides insights into how GenAI influences learning experiences and perceptions, bridging the gap between theoretical understanding and real-world application. The study suggests that responsible GenAI use in education requires strategies and best practices to ensure effective and ethical integration. The course design included project-oriented tasks, hands-on experiential learning, and reflection to enhance students' understanding of GenAI. Data collection was qualitative, including reflective assignments, class discussions, and surveys. The AI-ICE Framework was used to analyze students' cognitive engagement with GenAI, emphasizing the process rather than just the output. Results showed a significant increase in students' comfort with GenAI and understanding of its ethical implications. Course reflections highlighted themes of enhanced teaching strategies, personal and professional growth, and challenges in GenAI integration. The study's findings suggest that integrating GenAI into educational contexts can enhance learning experiences and perceptions. However, it also highlights the need for ethical considerations and responsible use of GenAI. The study recommends strategies for integrating GenAI into educational settings, emphasizing ethical considerations and responsible use. Future research should aim to recruit a larger cohort to validate and expand upon initial observations. The study contributes to the growing body of knowledge on GenAI practices in educational settings, offering insights into how GenAI influences learning experiences and perceptions.