The recent developments in the research area of educational technology and AI applications in education highlight a significant shift towards leveraging AI to enhance learning experiences, reduce teacher workload, and provide personalized feedback to students. A common theme across the studies is the exploration of how AI and information technology can be tailored to meet specific educational needs, from generating topic-controlled questions to offering real-time, personalized learning support. Innovations in scalable and automatic question generation, affordably fine-tuned large language models for educational purposes, and AI-driven tools for student writing development are particularly noteworthy. These advancements not only promise to make education more accessible and efficient but also aim to bridge the gap between technology and personalized learning experiences. Additionally, the integration of AI literacy courses into university curricula reflects a growing recognition of the importance of preparing students and educators for the AI-driven future. The studies collectively underscore the potential of AI to transform educational practices, making them more adaptive, inclusive, and effective.

Noteworthy Papers

• A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education: Introduces a scalable solution for generating high-quality, topic-focused questions, significantly reducing teacher workload and supporting personalized tutoring systems.
• Affordably Fine-tuned LLMs Provide Better Answers to Course-specific MCQs: Demonstrates that smaller, textbook-based fine-tuned models outperform larger generic ones, making LLMs more accessible for educational purposes.
• CyberMentor: AI Powered Learning Tool Platform to Address Diverse Student Needs in Cybersecurity Education: Presents an open-source platform that provides personalized, real-time learning support, enhancing equity and sustainability in higher education.