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Triangulating Natural Language Processing (NLP)-Based Analysis of Rater Comments and Many-Facet Rasch Measurement (MFRM): An Innovative Approach to Investigating Raters' Application of Rating Scales in Writing Assessment
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Huiying Cai; Xun Yan – Language Testing, 2024
Rater comments tend to be qualitatively analyzed to indicate raters' application of rating scales. This study applied natural language processing (NLP) techniques to quantify meaningful, behavioral information from a corpus of rater comments and triangulated that information with a many-facet Rasch measurement (MFRM) analysis of rater scores. The…
Descriptors: Natural Language Processing, Item Response Theory, Rating Scales, Writing Evaluation
Korean Syntactic Complexity Analyzer (KOSCA): An NLP Application for the Analysis of Syntactic Complexity in Second Language Production
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Haerim Hwang; Hyunwoo Kim – Language Testing, 2024
Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides…
Descriptors: Korean, Natural Language Processing, Syntax, Computer Graphics