As social engineering threats continue to evolve, equipping learners with the skills to recognize and respond to digital manipulation has become a critical component of digital citizenship education. This paper explores the use of Microsoft Copilot—an AI-powered assistant—as a tool for generating instructional content that enhances awareness of social engineering tactics within digital learning environments. By integrating Copilot into the instructional design process, educators can rapidly produce scenario-based learning modules, phishing simulations, ethical discussion prompts, and adaptive assessments tailored to diverse learner profiles. The study presents a framework for human-AI collaboration in content creation, emphasizing pedagogical alignment, personalization, and scalability. Through case examples and prototype lesson plans, the paper demonstrates how Copilot can support educators in developing engaging, context-aware materials that foster critical thinking and digital resilience. This approach not only streamlines curriculum development but also positions generative AI as a strategic partner in advancing cybersecurity education across formal and informal learning contexts).

Cybersecurity literacy is increasingly vital in higher education, yet traditional teaching methods often fail to sustain student engagement. This paper introduces Aegis Academy, an AI-driven gamified learning platform that uniquely integrates adaptive feedback mechanisms with game-based elements to enhance cybersecurity awareness and skills. Unlike existing systems, Aegis Academy combines real-time personalization, rolebased analytics, and modular gamification tailored for academic settings. A pilot study involving 100 students and 20 instructors demonstrated significant improvements in phishing awareness (+22 %), overall scores (+18 %), and module completion rates (87% vs. 64%). Students rated the platform highly for engagement and learning impact, while instructors reported strong pedagogical alignment and usability. The platform supports Sustainable Development Goal 4 (SDG 4) by promoting inclusive, equitable, and engaging digital education. These findings suggest that Aegis Academy offers a scalable and effective model for cybersecurity instruction in higher education.

The rapid advancement of large language models (LLMs) such as ChatGPT, Claude, and Gemini presents new opportunities for personalized education. These AI systems are capable of tailoring learning experiences, providing instant feedback, and supporting self-paced study. However, questions remain regarding their pedagogical effectiveness, ethical implications, and alignment with educational goals. This study explores the opportunities and challenges of integrating LLMs into personalized learning environments in higher education. Using a mixed-method approach that combines experimental use of LLM-based tutoring with surveys and interviews of students and educators, the research evaluates their impact on engagement, learning outcomes, and inclusivity. Findings are expected to contribute to the discourse on AI in education while supporting the United Nations’ Sustainable Development Goal 4 (Quality Education), particularly in promoting inclusive and equitable access to learning opportunities through emerging technologies.

As generative AI continues to reshape educational landscapes, prompt-to-image technologies offer new possibilities for enhancing visual pedagogy. This study investigates the integration of NanoBanana a lightweight, prompt-driven image generation tool, into higher education settings to support multimodal learning and cognitive scaffolding. Grounded in Dual Coding Theory and Cognitive Load Theory, the research explores how AI-generated visuals derived from student and instructor prompts can improve comprehension, engagement, and retention in complex subjects such as ICT, Game Studies, and Systems Analysis. Using a mixed-methods approach, the study analyzes student performance data, visual rubric evaluations, and qualitative feedback from learners and educators. Findings reveal that NanoBanana-generated images significantly aid in conceptual clarity, reduce extraneous cognitive load, and foster learner autonomy. The paper proposes a practical framework for integrating prompt-to-image tools into curriculum design and instructional workflows, offering actionable insights for educators seeking to advance AI-enhanced teaching practices in line with SDG4 and the evolving demands of the AI era.

With the upcoming changes brought about by Artificial Intelligence (AI) to the field of education, teaching AI literacy and digital competency to educators has emerged as an imperative. Based on proposed and empirically-supported research, this paper outlines a multi-level training model that is aligned to Sustainable Development Goal 4: Quality Education and where the AI awareness and pedagogical integration is placed as a basis. Through this proposed model that adopts a multimethodological approach comprising a review of relevant literature and surveys and interviews among educators, major milestones regarding the implementation of vital training competencies among teachers before and after being hired have been discovered. These facts reveal that when it comes to awareness of tools available, high-level awareness has been discovered to exist among them but when it comes to confidence and preparedness in ethical practices, poor awareness has been observed.