A Multivariate Probit Model for Learning Trajectories: A Fine-Grained Evaluation of an Educational Intervention.

ABSTRACT: Advances in educational technology provide teachers and schools with a wealth of information about student performance. A critical direction for educational research is to harvest the available longitudinal data to provide teachers with real-time diagnoses about students' skill mastery. Cognitive diagnosis models (CDMs) offer educational researchers, policy makers, and practitioners a psychometric framework for designing instructionally relevant assessments and diagnoses about students' skill profiles. In this article, the authors contribute to the literature on the development of longitudinal CDMs, by proposing a multivariate latent growth curve model to describe student learning trajectories over time. The model offers several advantages. First, the learning trajectory space is high-dime

SUBMITTER: Chen Y 

PROVIDER: S-EPMC7495794 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature