İngiliz Dili ve Edebiyatı Bölümü Koleksiyonu
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- ItemFashioning the self in Jean Rhys’s voyage in the dark and good morning, midnight(Çankaya Üniversitesi, 2024-04) Koç, Nesrin; 13778Jean Rhys held a deep passion for fashion and stylish attire. Her perspective on fashion, as an instrument of adopting “a second skin” finds expression in her focus on fashioning the self, a recurring motif in Rhys’s oeuvre. The physical difficulty Rhys’s female characters, whose lives bear strong similarities to her own, have in obtaining fashionable clothes represents the broader struggles they go through as the objects of the patriarchal and colonial gaze, in their voyages through the physical and metaphorical darkness of urban spaces like Paris and London in the early 1900s. Focusing on two of these women, Anna of Voyage in the Dark and Sasha in Good Morning, Midnight, for whom fashionable clothing appears to be the only way of navigating the modern society which marginalizes them, this study explores Rhys’s multilayered portrayal of fashion as a reflection of the near impossibility of attaining a cohesive sense of self, mirroring the characters’ struggles in fashioning their inner and outer selves.
- ItemUtilizing large language models for EFL essay grading: an examination of reliability and validity in rubric-based assessments(Wiley, 2024-05) Yavuz, Fatih; Çelik, Özgür; Yavaş Çelik, Gamze; 131069This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style & expression and mechanics. The results revealed that fine-tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine-tuning and adjustment are needed for a more nuanced understanding of non-objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research.
