Spatial ability refers to the ability of individuals to recognize,encode,store,represent,decompose,combine and abstract objects or spatial figures in their minds,which is the cognitive foundation for understanding one's environment and solving problems.Building an accurate,convenient and effective assessment system of spatial ability is of great significance to the enhancement of STEM education and the quality of talent cultivation.Due to the complex,multi-dimensional and implicit nature of spatial ability,it is difficult to evaluate spatial ability via computer-based assessments.This study aims to accurately,effectively,and massively evaluate spatial ability by using multimodal learning analytics methods to explore the characteristic behavioral expressions of learners'spatial cognition,and by developing key technologies and tools for spatial ability stealth assessment based on video game environments.The specific contents include:1)Construct a framework for the intrinsic representation of spatial ability and an evaluation index system;2)Constructing a learner spatial ability behavior performance model based on multimodal learning analysis;3)Explore the key factors that influence spatial ability in video games,and use game engines to develop game-based assessment tools;4)Use evidence-centered design frameworks and Bayesian network models to develop and deploy assessment algorithms capable of inferring and predicting spatial abilities;5)Conduct empirical research in laboratory and real classroom settings to verify the effectiveness of evaluation tools.The research findings will contribute to a better understanding of human spatial cognition processes and behavioral performance,expand and enrich theories related to spatial abilities,and provide key technical support for large-scale digital assessment.
国家科技期刊平台
NSTL
万方数据
