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Evaluating Lexical Richness in Higher Education:

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dc.contributor.author Setiti Rania, Boulmokh Insaf Hadia
dc.date.accessioned 2025-10-20T08:38:10Z
dc.date.available 2025-10-20T08:38:10Z
dc.date.issued 2025-06
dc.identifier.uri https://dspace.univ-guelma.dz/jspui/handle/123456789/18397
dc.description.abstract The present research aims at highlighting the efficiency of artificial intelligence (AI) and Natural Language Processing tools (NLP) in text analysis and the assessment of students’ language proficiency. The study targets one dimension of language proficiency embodied in the lexical richness of students’ writings. It represents a study focused on measuring the density, sophistication, and diversity of students’ vocabulary. A descriptive-correlational research design was adopted while employing a quantitative method for data analysis. The participants involved 60 English as a Foreign Lnaguage (EFL) learners studying at the University of Guelma - 8 Mai 1945. The selected samples embodied two groups: 30 first-year and 30 third-year students from the English Departement. After assigning a writing task for students, the output was transcribed to promote the process of automated data analysis. The study employed the web-based Lexical Complexity Analyzer (LCA), introduced by Ai and Lu in 2010 for the examination of the concerned corpus. The findings showed that extensive exposure to English in academic settings does not necessarily increase the lexical density and diversity of vocabulary in students’ writing. Yet, extensive exposure appears to be a prominent factor in improving the lexical sophistication of students’ writings, which is considered the most important proxy measure of lexical richness. These latter findings were corroborated by the reported significant difference in the mean scores belonging to the two evaluated groups, as third-year students scored higher averages (Av. LS1= 0.83; Av. LS2= 0.69) in comparison to first-year students (Av. LS1= 0.72; Av. LS2= 0.59). The discrepancy in the mean values was statistically significant in relation to LS2 (p= .03) with a moderate to large effect size (LS1, d= 0.5; LS2= d= 0.6) suggesting that such a variation has practical meaningfulness, which in turn implies that the difference in the lexical sophistication of the two groups is likely noticeable an ordinary reader. Further research in the academic context is still needed to achieve a more comprehensive understanding of the trajectory of students’ vocabulary acquisition. en_US
dc.language.iso en en_US
dc.subject artificial intelligence, natural language processing, evaluation, language proficiency, lexical richness, students' writings, lexical density, lexical sophistication, lexical diversity. en_US
dc.title Evaluating Lexical Richness in Higher Education: en_US
dc.title.alternative A Comparative Study through the Use of AI en_US
dc.type Working Paper en_US


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