The integration of Artificial Intelligence (AI) in education has transformed learning environments, enabling more efficient and adaptive instruction. This study examines the impact of Microsoft Copilot, an AI-powered assistive technology, on student performance and engagement in blended learning. A mixed-methods approach was employed, combining pre-test/post-test analysis, LMS data, surveys, interviews, and focus groups. Results indicate that Copilot improves instructional efficiency, enhances engagement, and supports real-time assessment, although concerns about overreliance persist. The findings contribute to understanding AI's role in modern education and support the development of smarter digital learning systems.

This paper presents a design framework for integrating AI-generated visuals into blended and hybrid learning environments, based on the Cognitive Theory of Multimedia Learning and Dual Coding Theory. It emphasizes responsible AI practices following UNESCO guidelines. The framework was piloted in blended courses, showing notable benefits such as instructor time savings, enhanced student engagement, reduced cognitive load, and better comprehension. The study offers a validated and ethical method for employing text-to-image technologies in blended learning.

Achieving Sustainable Development Goal 4 (Quality Education) requires innovative and ethically grounded integration of emerging technologies in higher education. This study developed and empirically validated an ethics-by-design AI-in-Instructional-Design Framework integrating Microsoft Copilot and Google Gemini into university course development workflows. Using a mixed-methods developmental research design guided by the ADDIE model, the framework was piloted with 12 educators and 180 students across blended and online courses. Quantitative analyses revealed statistically significant improvements in instructional quality (+10.44), UDL compliance (+15.21), workflow usability (+20.78 SUS), and reductions in faculty preparation time (-3.13 hours/week). Student engagement, AI literacy, integrity compliance, and accessibility adoption also increased significantly (p<.001). Thematic analysis of qualitative feedback confirmed enhancements in workflow efficiency, alignment, inclusivity, and ethical governance while emphasizing the importance of human oversight. Findings indicate that structured, ethics-governed AI integration enhances instructional quality, equity, and responsible innovation in higher education, thereby advancing SDG 4.

The research work investigates the Cooperation Paradox, a situation wherein faculty members recognize the application of artificial intelligence (AI) in designing the curriculum but feel hesitant about cooperating with AI adoption due to ethical, identity, and equity-related concerns. A convergent parallel mixed-methods approach is adopted for the research, wherein qualitative research methods, such as interviewing, have been utilized to understand the complexity of the issue, whereas quantitative research methods, such as surveys, have been applied for data analysis purposes. A framework for determining the level of cooperation and resistance of the faculties to AI adoption has been designed, which differentiates among levels of cooperation, from passive to active cooperation.

Artificial Intelligence (AI) is reshaping teacher education by providing intelligent tools that enhance pedagogy, student learning, and accessibility. This study explores how Microsoft Copilot, an AI-powered learning assistant, supports both teachers and students in integrating accessibility-focused coding into IT education. By assisting with debugging, code recommendations, and inclusive design principles, Copilot strengthens teachers' digital competence and helps students gain confidence in developing equitable digital solutions. A quantitative survey of Filipino IT instructors and students assessed awareness, adoption, and confidence in using Copilot for accessibility-oriented coding. Statistical analyses, including correlation and confidence interval testing, validated the results. Findings suggest that Copilot not only improves coding efficiency but also supports teachers in embedding accessibility concepts into their instruction—contributing to inclusive and innovative teaching models.