The fields of engineering education research, artificial intelligence in education, and systems engineering and design are witnessing significant transformations, driven by a common theme of embracing complexity, nuance, and interdisciplinary collaboration. A key trend in engineering education research is the recognition of the intricate relationships between curriculum structure, student performance, and external factors. Research has underscored the importance of considering structural constraints, such as rigid curricula and strict regularity rules, in predicting student dropout rates. The application of agent-based simulation environments and causal analysis has emerged as a critical approach in identifying effective policy interventions to mitigate these issues. Notably, the CAPIRE Intervention Lab presents an innovative agent-based simulation environment for testing policy interventions, while the concept of 'Regularity as Structural Amplifier, Not Trap' challenges traditional notions and suggests that regularity rules can exacerbate pre-existing student vulnerabilities. In parallel, the integration of Artificial Intelligence (AI) and machine learning (ML) techniques is revolutionizing systems engineering and design. Developments in this area are focused on leveraging AI to enhance various aspects of systems engineering, including requirements engineering, failure mode and effects analysis, and design validation. The proposal of the Creative Intelligence Loop (CIL) framework for human-AI co-creation and the development of REACT and SemaLens components for assuring AI-enabled safety-critical systems are particularly noteworthy. Furthermore, the field of artificial intelligence in education is moving towards a more synergistic relationship between teachers and AI systems, with research focused on developing frameworks and tools that enable more effective collaboration and automation of educational tasks. The introduction of a novel multi-agent framework for automating slide adaptation and the development of MicroSims, a framework for creating lightweight, interactive educational simulations using artificial intelligence, are examples of innovative work in this area. These interconnected advancements across engineering education research, artificial intelligence in education, and systems engineering and design signal a significant shift towards more nuanced, effective, and responsible approaches to complex problem-solving and knowledge creation. As these fields continue to evolve, it is essential to recognize the potential for mutual reinforcement and the broad implications of these developments for education, engineering, and beyond.