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Dense and Disconnected: Analyzing the Sedimented Style of ChatGPT-Generated Text at Scale.
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- Author(s): Markey, Ben1 (AUTHOR) ; Brown, David West1 (AUTHOR); Laudenbach, Michael2 (AUTHOR); Kohler, Alan1 (AUTHOR)
- Source:
Written Communication. Oct2024, Vol. 41 Issue 4, p571-600. 30p.- Subject Terms:
- Source:
- Additional Information
- Abstract: ChatGPT and other LLMs are at the forefront of pedagogical considerations in classrooms across the academy. Many studies have spoken to the technology's capacity to generate one-off texts in a variety of genres. This study complements those by inquiring into its capacity to generate compelling texts at scale. In this study, we quantitatively and qualitatively analyze a small corpus of generated texts in two genres and gauge it against novice and published academic writers along known dimensions of linguistic variation. Theoretically, we position and historicize ChatGPT as a writing technology and consider the ways in which generated text may not be congruent with established trajectories of writing development in higher education. Our study found that generated texts are more informationally dense than authored texts and often read as dialogically closed, "empty," and "fluffy." We close with a discussion of potentially explanatory linguistic features, as well as relevant pedagogical implications. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Written Communication is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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