Core Insights - The article emphasizes the need for transformation and innovation in educational research (教研) to enhance the quality of basic education in China, particularly in the context of increasing AI applications [1] Group 1: Quality Improvement in Regular Classes - Regional educational research plays a crucial role in enhancing the quality of regular classes by integrating research, teaching, learning, and assessment [2] - The development of a competency-based classroom is essential, focusing on gradual and continuous competency cultivation rather than immediate learning outcomes [2] Group 2: Data-Driven Transformation - Smart education is identified as a significant growth line for large-scale transformation in regional educational research, utilizing big data for comprehensive classroom analysis and evidence-based research [3] - The integration of human-machine collaboration in educational research allows for a shift from traditional experience-based analysis to data-driven insights [4] Group 3: Organizational Change - The transformation of educational research must also include changes in organizational structures, moving away from fragmented approaches to a more collaborative ecosystem [6] - Strengthening the collaboration between educational research and scientific research is vital for driving innovation and practical support in basic education [6] - Enhancing cross-level and cross-domain collaboration is necessary to improve research quality and create a resource hub for regional education [7]