A didactic illustration of writing skill growth through a longitudinal diagnostic classification model.

ABSTRACT:

Introduction

Diagnostic classification models (DCMs) have received increasing attention in cross-sectional studies. However, L2 learning studies, tracking skill development over time, require models suited for longitudinal analyses. Growth DCMs offer a promising framework for such analyses.

Method

This study utilizes writing data from two learner groups: one receiving peer feedback (n = 100) and the other receiving no feedback (n = 100), assessed at three time points. It demonstrates the application of longitudinal DCM via the TDCM package to analyze growth trajectories in four writing subskills: Content, Organization, Grammar, and Vocabulary. The primary focus is on showcasing the package, but substantive findings can also be helpful.

Results

The multi-

SUBMITTER: Ravand H 

PROVIDER: S-EPMC11775902 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature