Browsing by Organisation Author "Yavuz, Fatih"

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Publication
    Enhancing reading strategies through literature selection in EFL classrooms
    (CV. Yudhistt Fateeh, 2024-04) Durak, Ayşegül; Yavuz, Fatih; 392831; 131069
    This study presents a detailed examination of how to enhance reading strategies with selected literary genres using the library research method. In addition to library resources, the information collection process has been monitored through various academic publications, articles and books, the data obtained has been analysed and the results have been evaluated. Discovering the efficacy of authentic texts demonstrates that it enhances reading comprehension and fosters the abilities of learners. The study also identifies key strategies such as skimming, scanning, guessing, and distinguishing implied and literal meaning strategies. These techniques play a significant role in learners’ capability of understanding authentic text. Drawing on theoretical frameworks, the study underscores the importance of integrating the strategies mentioned above into teaching reading to enrich deeper understanding and critical engagement with literature. As a result, using the selected strategies and literary sources can effectively equip EFL learners to understand the unknown parts of complex texts. Language acquisition and proficiency improvement in authentic text are facilitated by navigating.
  • No Thumbnail Available
    Item
    Integrating technology into English language teaching at Indonesian high schools: Teachers’ reflections
    (Universitas Syiah Kuala, 2025-05) Anwar, Choiril; Hartono, Hartono; Yavuz, Fatih; 131069
    English Language Teaching (ELT) is something that has changed dramatically in recent times due to technology. Even though it could potentially reshape ELT, appropriate implementation remains a challenge for most teachers who are often uncertain as to how to use technology to improve learning. This article looks into the experiences and reflections of Indonesian high school English teachers integrating technology into their ELT pedagogical practices, from making lesson plans, having classroom activities, to setting up the assessment. Quantitative and qualitative data were collected and analyzed through a mixed-methods approach. It involved an online survey distributed to 20 diverse Indonesian high school English teachers as well as semi-structured interviews conducted with 10 teachers. The results indicated that there is an increasing use of technology for ELT purposes, particularly to facilitate language reception, language production, and interaction. The results also found some challenges and limitations, including technical issues, training and support, and access equity. These insights can help guide the future development of Indonesian high school ELT practices, inform investment in technology infrastructure, and support targeted professional development initiatives focused on technology integration. The findings are discussed in the context of existing research on ELT and technology integration, with particular emphasis on their significance for high school English teachers in Indonesia. The results provide implications for ELT policymakers, practitioners, and researchers in Indonesia and evidence the importance of context-sensitive solutions to provide meaningful integration of technology in the variability of Indonesian high school settings.
  • No Thumbnail Available
    Item
    Utilizing large language models for EFL essay grading: an examination of reliability and validity in rubric-based assessments
    (Wiley, 2025-01) Yavuz, Fatih; Çelik, Özgür; Yavaş Çelik, Gamze; 131069
    This 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.