A Cognitive Model for Preschool Analogical Reasoning: Development and Validation Using Internet of Things (IoT) Technology

Analogical reasoning is fundamental to early cognitive development, supporting knowledge transfer and academic achievement across domains including scientific reasoning, language acquisition, and mathematics. However, the underlying cognitive processes remain inadequately understood due to limitations in existing assessment approaches. This study developed and validated a cognitive diagnostic model for preschool analogical reasoning through a three-phase mix-methods design. Phase One: literature review to establish a preliminary theoretical framework. Phase Two: pilot study (n = 20) to refine the model and develop an IoT-enhanced assessment system. Phase Three: large-scale empirical validation (n = 220). Research Findings: The validated model identified four hierarchical cognitive attributes: (A1) rule understanding, (A2) relational inference and application, (A3) two-dimensional problem-solving, and (A4) multi-dimensional problem-solving, which followed a linear developmental trajectory. Practice or Policy: Integration of Optical Identification (OID) technology enabled real-time, unobtrusive data collection and developmentally appropriate interactive task design. Psychometric analyses confirmed strong model validity and reliability, providing an empirically grounded framework for assessing and fostering analogical reasoning in early childhood with implications for both research and educational practice.