Sanat ve Sosyal Bilimler Fakültesi
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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.
- ItemProblems and opportunities of artificial intelligence(İnönü Üniversitesi, 2022) Gürsakal, Necmi; Çelik, Sadullah; Batmaz, Bülent; 16040This article reviews Artificial Intelligence (AI)’s challenges and opportunities and discusses where AI might be headed. In the first part, it was tried to reveal the differences between Symbolic AI and Deep Learning approaches, then long promises but short deliveries of AI were mentioned. The problems of AI are that the media has high expectations about artificial intelligence and keeps the problems and restrictions it creates low. Today, while AI is stuck with issues such as deepfake applications and carbon footprints that create moral and climatologic problems; on the other hand, it is struggling with problems such as deep learning models requiring huge amounts of data. Another problem with deep learning is that deep learning models are a blackbox and not open to improvements because it is not known where mistakes were made. Among the new paths ahead of AI are Hierarchical Temporal Memory (HTM) models and hybrid models that generally try to bridge the gap between Symbolic AI and Connectionist AI. If we consider that the most important leaps in AI have been made with the features of the brain that AI can imitate, then the developed HTM models may also be a new opportunity for AI.
- 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.