https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/517 2026-07-04T13:56:36Z 2026-07-04T13:56:36Z Kim, Sung-Yeon https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212774 2026-05-20T06:00:10Z 2026-07-01T00:00:00Z

Title: Developing pre-service English teachers’ critical and ethical AI literacy in writing with generative AI Authors: Kim, Sung-Yeon Abstract: This mixed-methods study explored the effects of AI literacy (AIL) training on pre-service English teachers’ writing proficiency and Al literacy development. Employing a quasi-experimental design (n = 60), the study compared an AIL training group (G1), a just-writing group (G2), and a control group (G3). All groups completed surveys measuring critical and ethical AI literacy, while G1 and G2 (n = 43) also completed writing tests. Qualitative data were collected from G1 through reflection journals and follow-up interviews (n = 7). A one-way analysis of covariance (ANCOVA), using pretest scores as a covariate to control for cohort effects, revealed that the AIL group significantly outperformed the just-writing group in post-intervention writing proficiency ( F (1, 40) = 13.29, p < .001). While self-reported surveys showed no significant shifts in critical or ethical AI competence ( p > .05), qualitative data substantiated the behavioral manifestation of AI competence. Students in the AIL group demonstrated critical competence through behaviors such as cross-checking AI-generated sources, and limiting AI use to brainstorming after experiencing hallucinations. Based on these findings, the study proposes two conceptual frameworks. The TPEC (Technological, Pedagogical, Ethical, and Critical) framework is presented as a theoretical expansion of existing AI integration models for teacher education. The TDCE model (comprising Technological, Dialogical, Critical, and Ethical dimensions) outlines a developmental trajectory of AI literacy from awareness to competence across the four dimensions. These models suggest that structured AIL training supports the responsible integration of generative AI into writing instruction, even when changes in attitudes and competencies are not immediately captured by self-reported questionnaires.

2026-07-01T00:00:00Z Kim, Minjoo Chon, Yuah V. https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/207387 2026-02-01T10:35:27Z 2025-07-01T00:00:00Z

Title: The impact of self-revision, machine translation, and ChatGPT on L2 writing: Raters’ assessments, linguistic complexity, and error correction Authors: Kim, Minjoo; Chon, Yuah V. Abstract: This study explores how learners in a South Korean high school English as a Foreign Language (EFL) context can effectively use neural machine translation (MT) and ChatGPT to enhance their L2 writing. While recent AI tools offer significant potential for supporting human writing feedback, a comparative analysis of how these tools impact writing outcomes—compared to when L2 writers independently proofread and revise their writing—has not been fully examined. To address this gap, a controlled experiment was conducted using three distinct proofreading interventions—self-proofreading (SP), MT-assisted proofreading (MAP), and ChatGPT-assisted proofreading (CAP). Learners were encouraged to first compose their texts in their L2 and then use either MT through inverse translation or ChatGPT through a structured proofreading process. The findings revealed that learners using MAP and CAP demonstrated substantial improvements in overall writing quality compared to those relying solely on SP. CAP users, in particular, produced longer texts, exhibited greater lexical diversity, and constructed more complex sentences, although this was accompanied by reduced verb cohesion. Both MAP and CAP significantly reduced grammatical errors, but did not affect prepositional errors. These findings provide practical recommendations for integrating MT and ChatGPT into L2 writing pedagogy.

2025-07-01T00:00:00Z 김성연 정남숙 https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/207152 2026-02-09T10:05:35Z 2025-02-01T00:00:00Z

Title: ChatGPT 활용 특수목적 영어(ESP) 교육: ESP 학습자의 독해력과 인식을 중심으로 Authors: 김성연; 정남숙 Abstract: This study examined effects of ChatGPT on Korean college students’ business English reading comprehension and their perceptions of the AI tool. Fourteen college students enrolled in a business English course completed ESP reading tasks using ChatGPT as a learning aid over ten weeks. They were asked to take reading tests twice: a pre-test at the beginning of the semester and a post-test at the end of the semester. They also responded to questionnaires designed to measure their perceptions of ChatGPT and their affective satisfaction. Data were analyzed using paired sample t-tests with SPSS 25.0. Results showed that students significantly improved their reading skills over the semester. Furthermore, they regarded ChatGPT as a valuable tool for enhancing their reading proficiency. Most students expressed high levels of satisfaction with ChatGPT in their learning process. These positive effects have meaningful pedagogical implications for ESP teachers and learners, as ChatGPT can effectively support the teaching and learning of field-specific contents.

2025-02-01T00:00:00Z Lee, Sangmin-Michelle Kim, Sung-Yeon https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213124 2026-06-09T00:00:20Z 2025-01-01T00:00:00Z

Title: Preservice teachers' learning by design through space construction in the metaverse Authors: Lee, Sangmin-Michelle; Kim, Sung-Yeon Abstract: Teachers who know what, how and why to teach are essential for successful student learning. However, many preservice teachers (PSTs) lack teaching experience and the ability to integrate theory and practice. To help bridge this gap, this study employed a learning-by-design project approach in which 22 Korean PSTs developed lesson plans for middle school English classes, constructed virtual classrooms in the metaverse based on their English lesson plans, and conducted microteaching in the virtual classrooms. The study used a qualitative research method and focused on an emic perspective with multiple data sets, including the PSTs' reflection papers and post-interviews as primary data, and their lesson plans, virtual classrooms and recordings of microteaching as secondary data. The results showed that the project supported learning by design, and that it also helped PSTs understand learners and learning, redefine the teacher's role as a designer and facilitator, connect theories to practice and improve their teaching skills. The findings can be used as a reference for future teacher training.

2025-01-01T00:00:00Z