Linguistic Features of Writing Quality
Abstract
In this study, a corpus of expert-graded essays, based on a standardized scoring rubric, is computationally evaluated so as to distinguish the differences between those essays that were rated as high and those rated as low. The automated tool, Coh-Metrix, is used to examine the degree to which high- and low-proficiency essays can be predicted by linguistic indices of cohesion (i.e., coreference and connectives), syntactic complexity (e.g., number of words before the main verb, sentence structure overlap), the diversity of words used by the writer, and characteristics of words (e.g., frequency, concreteness, imagability). The three most predictive indices of essay quality in this study were syntactic complexity (as measured by number of words before the main verb), lexical diversity (as measured by the Measure of Textual Lexical Diversity), and word frequency (as measured by Celex, logarithm for all words). Using 26 validated indices of cohesion from Coh-Metrix, none showed differences between high- and low-proficiency essays and no indices of cohesion correlated with essay ratings. These results indicate that the textual features that characterize good student writing are not aligned with those features that facilitate reading comprehension. Rather, essays judged to be of higher quality were more likely to contain linguistic features associated with text difficulty and sophisticated language.
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MTLD is a well-established measure of lexical diversity that is less sensitive to text length differences than TTR.
“We identify vocabulary richness by using a well-established measure of textual, lexical diversity (MTLD)46 which is often used in the field of automated essay grading25,45,47. It takes into account the number of unique words but unlike the best-known measure of lexical diversity, the type-token ratio (TTR), it is not as sensitive to the difference in the length of the texts.”
From A large-scale comparison of human-written versus ChatGPT-generated essays (2023) · cites this paper as [45]
Lexical, syntactic and discourse complexities correlate with essay gradings in prior work.
“Weiss et al.25 observe the correlation between measures of lexical, syntactic and discourse complexities to the essay gradings of German high-school examinations while McNamara et al.45 explore cohesion (indicated, among other things, by connectives), syntactic complexity and lexical diversity in relation to the essay scoring.”
From A large-scale comparison of human-written versus ChatGPT-generated essays (2023) · cites this paper as [45]
McNamara et al. found no indication that the use of cohesion indices such as discourse connectives correlates with high- and low-proficiency essays.
“McNamara et al.45 also find no indication that the use of cohesion indices such as discourse connectives correlates with high- and low-proficiency essays.”
From A large-scale comparison of human-written versus ChatGPT-generated essays (2023) · cites this paper as McNamara et al.45
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References 59 · Cited by 570
- Authors
- McNamara, D. S., Crossley, S. A., & McCarthy, P. M.
- Affiliations
- University of Memphis (US)
- Mississippi State University (US)
- Corresponding author
- McNamara, Danielle S.
- Venue
- Written Communication
- Publisher
- SAGE Publications
- Published
- 2009-11-24
- Volume
- 27
- Issue
- 1
- Pages
- 57-86
- ISSN
- 0741-0883 (ISSN-L)
- 1552-8472
- OpenAlex
- W2001833328
- Cited by
- 570
- References
- 59
- Citations by year
- 2026: 44 · 2025: 35 · 2024: 36 · 2023: 60 · 2022: 40 · 2021: 45 · 2020: 42 · 2019: 34 · 2018: 34 · 2017: 23 · 2016: 41 · 2015: 31 · 2014: 32 · 2013: 27 · 2012: 20
- FWCI
- 296.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Written Communication (publishedVersion)
- Funders
- Mississippi State University
- University of Memphis
- Topics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Text Readability and Simplification
- Keywords
- writing quality, essay scoring, Coh-Metrix, cohesion, coreference, connectives, syntactic complexity, lexical diversity, word frequency, concreteness, text complexity, reading comprehension, student writing
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