The field of educational technology is witnessing a significant shift towards AI-driven innovations, transforming the way students learn and interact with educational content. Recent developments suggest a strong focus on leveraging large language models (LLMs) to enhance student engagement, improve learning outcomes, and support teachers in their instructional endeavors. One of the key trends is the integration of LLMs into various educational settings, including formal methods courses, interactive molecular dynamics, and programming education, to provide personalized feedback, automate grading, and facilitate more effective learning pathways. Another notable direction is the development of AI-powered tools for improv actor training, classroom evaluation, and adaptive learning systems, which aim to make education more accessible, scalable, and equitable. These advancements not only demonstrate the potential of AI in enhancing educational experiences but also highlight the need for careful consideration of pedagogical principles and human-AI collaboration to ensure effective and sustainable integration of these technologies into educational practices. Noteworthy papers include: Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education, which introduces a novel pedagogical framework for LLM-driven feedback generation. Pensieve Grader: An AI-Powered, Ready-to-Use Platform for Effortless Handwritten STEM Grading, which presents an AI-assisted grading platform that leverages LLMs to transcribe and evaluate student work.