Teaching Reflection and Route Reconstruction of Big Ideas under the Background of Original Innovation

The vigorous rise of large language models represented by DeepSeek and ChatGPT not only highlights the strategic value of original innovation capability, but also imposes higher demands on education and teaching for cultivating students’ original innovation ability. As fundamental support for developing students’ original innovation capability, big ideas have been widely recognized for their instructional value, yet prominent bottlenecks persist in their practical implementation. Accordingly, this paper conducts research following the logical thread of “background analysis—connotation retrospection—source divergence—theoretical reflection—route reconstruction”: First, grounded in the era background of cultivating original innovation capability, it analyzes the intrinsic connection between big ideas and original innovation capability. Then, it traces the teaching dilemmas of big ideas and sorts out the divergence in connotations between big ideas viewed as knowledge and those viewed as thinking. Subsequently, starting from divergence in the sources and extraction methods of big ideas, this paper explores the logical starting points for generating big ideas under the guidance of different ideas. After that, it carries out systematic reflections on the scientificity and integrity of big ideas and their teaching research, revealing that the root cause of unsatisfactory teaching effects of big ideas lies in the artificial separation of knowledge acquisition and thinking development. Finally, from the basic stance of “the inherent unity of knowledge and thinking”, this paper carries out the route reconstruction for big ideas and their teaching research. This paper proposes an instructional design idea centered on conceptual understanding and driven by essential questions, which can provide theoretical reference for resolving connotation divergence and overcoming practical obstacles in current big ideas teaching, and offer strong support for the development of students’ original innovation capability under the background of original innovation.