Mapping the Usage of Definite and Indefinite Articles in Student and ChatGPT Essays: A Stylometric-Cartographic Approach
Keywords:
AntConc; ChatGPT-generated discursive essays; Deleuzian-Guattarian cartographic mapping; English definite and indefinite articles; student-written discursive essays; usage frequencies; stylometryAbstract
This study set out to investigate, analyse, and compare the usage frequencies of two English articles, the definite article, the, and the indefinite article, a, in two discursive essay sets. One set was written by first-year, English second language, undergraduate students (SWDEs), while the other set was generated by ChatGPT (CGDEs). Both essay sets responded to the same essay topic at different times (2023 and 2024). Each set comprised 50 essays, with the SWEDE set consisting of 27,183 tokens, whereas the CGDE set had 25,010 tokens. SWDEs were selected using convenience sampling, and all the 50 CGDEs were generated individually. The study employed a Deleuzian-Guattarian cartographic mapping and stylometry as its theoretical framing. In addition, it utilised AntConc to analyse its data. Some of the findings of this study are as follows. Pertaining to SWDEs, the definite article, the, had more usage frequencies than the indefinite article, a. A similar pattern was observed concerning CGDEs. Across the two essay sets, SWDEs recorded more usage frequencies of these two articles than CGDEs, with the definite article, the, having the most occurrence frequencies than the indefinite article, a, in both sets. With reference to cartographic representations of these two articles in the two essay sets, the study observed that these two articles can have multiple and varying representations that foreground their unfixed, indeterminate, fluid, and impermanent nature. This particular ephemeral nature, results in the cartographic deterritorialisation of these two articles across the two essay sets. This view inherently perceives student writing as being in a state of flux and negates the orthodox framing of student writing as predictable, linear, and stable. The study ends with recommendations and caveats regarding the use of these two English articles by English L2 students and by LLMs such as ChatGPT.
https://doi.org/10.26803/ijlter.24.12.34
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