Abstract High school students commonly experience spatial cognitive barriers when learning about network crystals, and merely observing static physical objects or 3D virtual models is insufficient to break through this bottleneck. To address this issue, this paper utilizes Generative Artificial Intelligence (GenAI) to assist in the development of “scaffolded unit cell models” and constructs three types of teaching scaffolds:“spatial positioning and quantitative analysis” “element deconstruction and viewpoint focusing”, and “structural evolution and knowledge transfer”. By designing structured prompts, abstract teaching intentions are transformed into lightweight interactive functions on the web end. Taking diamond and monocrystalline silicon as examples, this paper analyzes the implementation process of core teaching functions such as fractional coordinate conversion, dynamic tracking of specific six-membered rings, and structural evolution. On this basis, a visual teaching resource library covering more than 20 types of crystals has been established. Teaching practice shows that this model can effectively help students overcome core cognitive difficulties and make accurate judgments even when faced with complex variations.
LIU Xiao-Jia, HAN Xue, LING Yi-Zhou. Development of Scaffolded Unit Cell Models Using Generative Artificial Intelligence and Construction of Teaching Resource Library[J]. Chinese Journal of Chemical Education, 2026, 47(19): 65-71.
