Research on the Construction and Application of the Mechanism Model of Interaction Behavior on Idea Depth in a Knowledge-Building Learning Community

Based on knowledge-building theory, this study examines the impact of interactive behaviors on the depth of opinions within knowledge-building learning communities. Focusing on a third-grade Chinese language class in Xinjiang, China, this manuscript per the authors developed and validated coding systems for interactive behaviors and opinion depth through classroom observations and content analysis of students' artifacts. These tools were applied to analyze interactions and opinion depth in the community. Correlation and regression analyses, complemented by interview results, reveal how specific interactive behaviors significantly influence the depth of students' opinions. This research clarifies the current state of interactions and deepens our understanding of effective learning environments that promote deeper perspectives among learners.