ABSTRACT

Learning path and learning progression have received extensive attention from broad disciplines. The existing research In the field of learning path is rarely applied in curriculum learning and teaching. Learning progression is usually constructed through observations, interviews but not quantitative analyses. With 726 Grade 8 students’ mathematical knowledge in TIMSS-2015 as the research object, this research adopted a newly generated assessment theory – cognitive diagnosis assessment as the research tool and exploited methods such as K-means clustering analysis to construct learning path by combing the relationships among the attributes. We obtained the students’ ability θs for each classified group through the 3PL model in the Item Response Theory (IRT) and constructed the learning progressions based on the θs and the attribute relationships. From a data-driven approach, this method has provided a new perspective as well as the data support for the construction of the learning paths and the learning progressions.

摘要

学习路径和学习进度受到了广泛学科的广泛关注。现有的研究在学习路径领域很少应用于课程学习和教学。学习进展通常是通过观察、访谈而非定量分析来构建的。本研究以TIMSS-2015 726名八年级学生的数学知识为研究对象，采用新产生的评估理论——认知诊断评估为研究工具，利用K-means聚类分析等方法构建学习路径，结合属性之间的关系。我们得到了学生的能力θs通过项目反应理论 (IRT) 中的 3PL 模型对每个分类的组进行分析，并基于θs和属性关系构建学习进程。从数据驱动的角度来看，该方法为构建学习路径和学习进程提供了新的视角和数据支持。