Earticle

초록

영어

This study examines how Korean research on AI-assisted English writing is represented at the level of publication abstracts by applying text-mining procedures to a bounded corpus of English-language abstracts indexed in RISS between 2015 and 2025. To this end, we analyzed a corpus of 180 English-language abstracts retrieved from peer-reviewed journal articles and graduate theses indexed in RISS. A sequential text-mining workflow was employed, combining word-frequency, TF–IDF, n-gram, co-occurrence, LDA, and CONCOR clustering to identify macro-level trends. The results show that ChatGPT, feedback, and learning constitute central semantic hubs, indicating an increased abstract-level emphasis on LLM-supported feedback and process-oriented writing support alongside continuing attention to automated evaluation and linguistic accuracy. In addition, CONCOR clustering identified four higher-order thematic domains: (1) language generation and translation support, (2) feedback structures emphasizing grammar and self-regulated revision, (3) AI-integrated instructional design in digital environments, and (4) collaborative learning and evaluationoriented empirical research. Across these domains, the abstracts recurrently foreground feedback, linguistic accuracy, learning processes, instructional support, and teacher mediation. Taken together, these findings provide a basis for cautious interpretive reflections on AI-assisted writing research and suggest directions for future corpus expansion, full-text analysis, and mixed-method validation.

목차

Abstract
1. Introduction
2. Theoretical Background
2.1 AI and English Writing
2.2 Science Mapping and Text Mining
3. Methodology
3.1 Data Collection Method
3.2 Preprocessing
3.3 Analytical Procedures
4. Results
4.1 Word-Frequency Analysis
4.2 TF-IDF Analysis
4.3 N-Gram Analysis
4.4 Co-occurrence Matrix Analysis
4.5 Topic Modeling
4.6 CONCOR Clustering
4.7 Integrated Interpretation Across Analytical Procedures
5. Discussion and Conclusion
5.1 Interpreting the Findings Within a Bounded Analytical Scope
5.2 Reframing the Contribution: From Comprehensive Synthesis to Discourse-Level Mapping
5.3 Methodological Implications and Limits of Text-Mining-Based Inference
5.4 Critical Interpretation in Relation to Existing Literature
5.5 Implications Repositioned as Interpretive Reflections
5.6 Limitations and Directions for Future Research
5.7 Conclusion
References

키워드

저자

• Hye Rang Om [ Adjunct Professor, Korea University ] First Author
• Yena Lee [ Assistant Professor, CHA University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  언어학연구 [Journal of Linguistic Studies]

• 간기

  연3회

• pISSN

  1226-9859

• 수록기간

  1996~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 700 DDC 400