The field of education is witnessing a significant shift towards personalized and intelligent learning systems, driven by the rapid advancements in Artificial Intelligence (AI) and Large Language Models (LLMs). Recent developments have focused on leveraging AI to enhance student engagement, improve learning outcomes, and provide scalable and reliable feedback for educator development. Noteworthy papers in this area include: A Closed-Loop Personalized Learning Agent Integrating Neural Cognitive Diagnosis, Bounded-Ability Adaptive Testing, and LLM-Driven Feedback, which presents an end-to-end personalized learning agent that integrates multiple components to provide fine-grained estimates of students' mastery and targeted study guidance. Measuring Teaching with LLMs, which demonstrates the potential of custom LLMs to achieve human-level performance in evaluating teaching quality and provides a viable methodology for AI-driven instructional measurement.