Contextual Research-Empirical Research:Psychometric and Growth Modeling of Complex Patterns of Learning Resulting From the Interrelationships Between Multiple Learning Progressions

该项目旨在确定一套心理测量和成长模型，使研究人员和课程开发人员能够描述和测试学生在两个或两个以上学习进步过程中的相互关系。与目前该领域的思维不同，这些心理测量和成长模型不会假设学生学习的线性、连续性或单向度。该项目提出了三个目标：收集证明学习进展的分支的非线性学习模式存在的证据；收集证明平行学习进展的非线性学习模式存在的证据，并提出这些类型的学习进展的心理测量学和成长模型。心理测量学模型将被开发来估计复杂学习模式背后的认知模型。这项工作将分四个阶段进行：(1)从统计上探索来自NSF资助项目的现有数据集，这些数据集包含对不止一个学习过程的同时学习测量；(2)使用现有数据测试心理测量和成长模型；(3)收集和分析新数据；以及(4)使用新数据测试心理测量和成长模型。

The project aims is to identify a set of psychometric and growth models that will permit researchers and curriculum developers to describe and test the interrelationships between students' progress along two or more learning progressions. Unlike the current thinking in the field, these psychometric and growth models will not assume linearity, continuity, or unidimensionality of student learning. The project proposes three goals: gathering evidence for the existence of non-linear patterns of learning that demonstrate branching of the learning progressions; gathering evidence for the existence of non-linear patterns of learning that demonstrate parallel learning progressions, and proposing the psychometric and growth models for these types of learning progressions. The psychometric models will be developed to estimate the cognitive models underlying complex learning patterns. The work will progress in four phases: (1) exploring, statistically, existing datasets from NSF-funded projects containing simultaneous measures of learning on more than one learning progression; (2) testing the psychometric and growth models using the existing data; (3) collecting and analyzing new data; and (4) testing the psychometric and growth models using new data.