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.

Gamification has come up as a powerful tool in increasing learning engagement and motivation in online education. As a proposal in this article, the designing and developing of AI-powered game modules in GameMaker for STEM education with adaptive learning capabilities in a gamified setup is ideal. The proposed model can regulate AI in a controlled manner to personalize learning experiences based on game gameplay with adaptive difficulty levels, immediate feedback, and analysis of performance data of learners. Based on developing a game using GameMaker, this research utilizes AI analytical capabilities for achieving learning outcomes in STEM education by aligning game targets with learning in STEM education. A quasi-experimental design was utilized to assign 60 purposively sampled STEM students into experimental and control groups in equal measures. The data gathering methods used in this study include pre and post-tests, in-game engagement metrics and usability surveys based on SUS and TAM. Salient findings show that the AI-enhanced module produced significantly greater learning gains (M=19.80) than the non-adaptive module (M =11.10). Improvements within both groups were significant (p < 0.001), while between-group comparison favored the experimental group (p=0.002). Engagement metrics further revealed that the AI-adaptive group exhibited longer time-on-task, higher level-completion rates, and more active use of hints-indicating sustained engagement and effective utilization of adaptive support.

The rapid adoption of e-learning platforms in higher education has introduced significant cybersecurity risks affecting the confidentiality, integrity, and availability (CIA) of academic data. This study investigates cybersecurity awareness and the adoption of secure e-learning practices among educators and students using the CIA Triad and STRIDE threat model. A mixed-methods approach was employed, combining survey data and semi-structured interviews. Quantitative findings reveal moderate awareness and adoption levels, while qualitative insights highlight behavioral and institutional factors influencing security practices. Results indicate that awareness alone is insufficient; behavioral intention and institutional support are stronger predictors of secure behavior. The study proposes a cybersecurity awareness and practice framework tailored for higher education to enhance digital resilience.

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.

As cybersecurity threats increasingly impact business operations, equipping future managers with foundational digital security skills is essential. This study presents the design and evaluation of an AI-personalized gamified website aimed at enhancing cybersecurity awareness among business management students. The platform integrates intelligent agents to adapt content difficulty, provide real-time feedback, and personalize learning paths based on user behavior. Gamification elements, including scenario-based challenges, progress badges, and interactive simulations, are embedded to improve engagement and retention. A pilot implementation across two higher education institutions measured learning outcomes, engagement metrics, and usability. Results indicate significant improvements in students’ cybersecurity knowledge, decision-making accuracy, and motivation compared to traditional instruction. The study contributes a scalable framework for integrating AI and gamification into business education, aligning with the evolving demands of digital business environments.