Abstract
The aim of this study was to advance the analysis of written language transcripts by validating an automated scoring procedure using an automated open-access tool for calculating morphological complexity (MC) from written transcripts. The MC of words in 146 written responses of students in fifth grade was assessed using two procedures: (a) hand-coding of words containing derivational morphemes by trained scorers and (b) an automated analysis of MC using Morpholex, a newly developed web-based tool. Correlational analysis between the different MC calculations was examined to consider the relation between hand-coded derivational morpheme counts and the automated measures. Additionally, all MC measures were compared to a previously gathered rating of writing quality to consider predictive validity between the automated Morpholex score and teachers' ratings of writing quality. Automated measures of MC had a strong relation (r = .63) with hand-coding of the number of words with derivational morphemes. Additionally, the number of derivational and inflectional and derivational morphemes accounted for a significant amount of the variation in teachers' overall ratings of writing quality. Automated scoring of MC has potential utility as a valid alternative to hand-coding language samples, which may be valuable for progress monitoring of growth in complexity across repeated samples and measuring components that influence perceived quality of academic writing.
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