The application effect of the Rasch measurement model combined with the CRF model: An analysis based on English discourse

Yunxia Wang

PLOS ONE, 2024, vol. 19, issue 8, 1-19

Abstract: To analyze English discourse more accurately and provide more detailed feedback information, this study applies Rasch measurement and Conditional Random Field (CRF) models to English discourse analysis. The Rasch measurement model is widely used to evaluate and quantify the potential traits of individuals, and it has remarkable advantages in measurement and evaluation. By combining the CRF model, the Rasch model is employed to model the structural and semantic information in the discourse and use this model to carry out sequence labeling, to enhance the ability to capture the internal relations of the discourse. Finally, this study conducts comparative experiments on integrating the Rasch measurement and CRF models, comparing the outcomes against traditional scoring methods and the standalone CRF model. The research findings indicate that: (1) The discourse component syntactic analysis model on the Penn Treebank (PTB) database obtained Unlabeled Attachment Score (UAS) values of 94.07, 95.76, 95.67, and 95.43, and Labeled Attachment Score (LAS) values of 92.47, 92.33, 92.49, and 92.46 for the LOC, CRF, CRF2O, and MFVI models, respectively. After adding the Rasch measurement model, the UAS values of the four models on the PTB database are 96.85, 96.77, 96.92, and 96.78 for the LOC, CRF, CRF2O, and MFVI models, respectively, with LAS values of 95.33, 95.34, 95.39, and 95.32, all showing significant improvement. (2) By combining contextual information with CRF models, students can better understand their discourse expression, capture the connections between English discourse sentences, and analyze English discourse more comprehensively. This study provides new ideas and methods for researchers in English language education and linguistics.

Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0309001 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 09001&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0309001

DOI: 10.1371/journal.pone.0309001

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().