간행물
영어교육 KCI 등재 SCOPUS English Teaching
- 발행기관 한국영어교육학회
- 자료유형 학술지
- 간기 계간
- ISSN 1017-7108 (Print)
- 수록기간 1968 ~ 2025
- 주제분류 인문학 > 언어학 인문학 분류의 다른 간행물
- 십진분류KDC 374DDC 375
권호리스트/논문검색
Vol.80 No.5 (2025년 12월) 10건
1.
2025.12
구독 인증기관 무료, 개인회원 유료
This special issue of English Teaching commemorates the momentous 60th anniversary of the Korea Association of Teachers of English (KATE), reflecting on the evolution of English education and envisioning its future amid rapid advancements in artificial intelligence (AI) and digital technologies. English education in Korea has undergone significant theoretical, pedagogical, and technological transformations, and AI now presents new opportunities and complex challenges for instruction, assessment, equity, and ethics. The articles explore AI integration across all four language skills: reading material generation, career-integrated listening activities, AI feedback in writing, and AIbased speaking systems versus peer activities. A meta-analysis affirms AI’s positive effects on writing instruction. Other contributions examine English for Specific Purposes (ESP) and critically discuss the important ethical challenges of AI adoption, including data privacy, bias, and academic integrity. These studies collectively argue that AI is a powerful tool whose value depends on thoughtful, ethical integration that supports humanistic educational values.
4,000원
2.
2025.12
구독 인증기관 무료, 개인회원 유료
This study investigates how artificial intelligence (AI)-generated and instructor-provided feedback interact within process-based, collaborative EFL writing to influence learners’ affective engagement, motivation, self-efficacy, and attitude toward writing. Semistructured group interviews with nine pre-service English teachers were analyzed using NVivo 14. Among the three categories, attitude, encompassing both positive and negative factors, was the most frequently observed, followed by self-efficacy and motivation. Positive attitude was linked to the convenience, immediacy, and personalization of AI feedback, and to the collaborative course design that supported iterative revision and peer learning. Negative attitude reflected concerns about AI overreliance, inaccuracies, and limited contextual appropriateness, particularly in ESPfocused writing. Regarding self-efficacy, instructor feedback provided deep, contextaware guidance, whereas AI feedback offered rapid, mechanical accuracy and motivational support. Confidence improved through safer drafting, metacognitive insight, and gradual mastery of AI utilization skills. Motivation was reinforced by the process-oriented structure, targeted instructor feedback, collaborative activities, and peer support that fostered engagement and improvement.
6,900원
3.
2025.12
구독 인증기관 무료, 개인회원 유료
This study investigated the impact of artificial intelligence (AI) and peer interactions on the speaking performance and attitudes of EFL university students using a withinsubjects design. Thirty-nine participants engaged in both AI-based and peer-based speaking activities over 14 weeks and completed pre- and post-speaking tests, as well as pre-, mid-, and post-questionnaires. At the end of the semester, they also submitted reflective essays describing their experiences. Results revealed significant improvements in both speaking performance and self-perceived speaking skills from pre- to post-test. However, students’ attitudes toward AI and peer interactions diverged. Engagement, interest, and participation in AI interactions declined over time, whereas these affective dimensions in peer interactions remained stable or improved. Enjoyment and concentration were also consistently higher in peer interactions than in AI interactions. Overall, the findings suggest that although AI can enhance EFL learners’ speaking performance through repetitive practice and timely feedback, peer interactions play a more enduring role in supporting engagement, enjoyment, and meaningful language learning over time.
6,400원
4.
2025.12
구독 인증기관 무료, 개인회원 유료
The purpose of this study is to develop and implement a customized AI-based speaking diagnosis, learning, and assessment system, SpeakMaster, in order to overcome the lack of systematic evaluation and practice opportunities in school English speaking class. This system integrates automated speaking scoring to provide students with feedback on their speaking abilities across pronunciation, conversation, and presentation. This study adopts a design-based research methodology, demonstrating the development and implementation process. 1,451 students and eight teachers in elementary, middle, and high schools participated in the experiment. Data were collected through learning logs, teacher journals, interviews, and post-surveys. The findings indicate that the system design is appropriate for English class, promoting students’ flow in engaging speaking practice. Students showed motivation and satisfaction while teachers found the system valuable for monitoring student progress and facilitating speaking assessments. Despite the challenges of improving chatbot performance and enhancing scoring reliability, the results suggest that SpeakMaster shows potential to enhance English speaking education.
6,600원
5.
2025.12
구독 인증기관 무료, 개인회원 유료
This study investigates how AI feedback learning activities in English writing classes affect university students’ English achievement and writing motivation. It examines both cognitive and affective outcomes in EFL contexts using generative AI tools such as ChatGPT. A total of 244 first-year university students completed four writing tasks incorporating AI feedback during the revision process. Pre- and post-tests were conducted along with the Oxford Placement Test (Syndicate, 2001) and a modified version of Payne’s (2012) Academic Writing Motivation Questionnaire. Quantitative analyses revealed significant improvement in English achievement and three motivational subcomponents—enjoyment, recognition, and effort—while instrumentality showed no significant change. Qualitative analysis of open-ended questionnaire responses indicated that students valued AI feedback for error detection, coherence, and self-directed learning, yet recognized limitations such as unnatural expressions, misinterpretations, and overreliance on AI. The findings highlight the importance of AI literacy and propose a hybrid feedback model integrating AI and teacher guidance to enhance learner autonomy and writing competence.
6,000원
6.
2025.12
구독 인증기관 무료, 개인회원 유료
This study aims to develop and evaluate a GPT-based English learning system that creates reading materials tailored to the Korean middle school first-grade English curriculum. To this end, this study adopted OpenAI’s MyGPTs platform and created the AI system through eight different developmental versions by iterating prompts and uploading relevant knowledge files. To evaluate its linguistic appropriateness, this study generated reading passages at three difficulty levels (low, medium, high) and compared them with eight textbook texts using seventeen key indices from Coh-Metrix 3. The results show that GPT-generated texts at the medium level most closely resembled actual textbook passages in sentence count, syntactic simplicity, lexical familiarity, and overall readability. Low-level outputs achieved the highest readability and concreteness scores, indicating suitability for beginner EFL learners, while high-level outputs featured greater syntactic complexity, longer sentences, and richer lexical diversity. The study also identified limitations in GPT’s consistent adherence to prescribed difficulty parameters, text-type variety, and adaptive difficulty adjustment based on learner performance.
7,000원
7.
2025.12
구독 인증기관 무료, 개인회원 유료
This study presents a career-integrated English education model incorporating generative AI through two tracks: (1) content development, where English education majors in four career-oriented groups (teaching vs. non-teaching; decided vs. undecided) created TOEIC-format listening materials aligned with their interests; and (2) classroom application, where the AI-generated content was implemented in first-year general classes with 103 students. Career maturity was measured by a 30-item scale, and content effectiveness by ratings of difficulty, appropriateness, usefulness, and effectiveness. Results showed that content-related factors, not learner background, best predicted overall satisfaction. Although no statistically significant differences were found, education majors tended to rate the materials as slightly more useful and slightly less difficult. Pre–post tests showed improved decisiveness, suggesting that AI-integrated, career-oriented instruction enhanced students’ confidence in career decision-making and demonstrated the potential of generative AI in fostering professional competence and career readiness.
6,400원
8.
2025.12
구독 인증기관 무료, 개인회원 유료
This meta-analysis synthesizes evidence on the effects of ChatGPT-assisted instruction on English writing in Korean EFL contexts. A systematic search in RISS yielded 401 records; after screening under PRISMA procedures, 12 studies reporting writing outcomes were included and analyzed. Effect sizes were computed as Hedges’ g and pooled using random-effects models. The random-effects mean indicated a medium-tolarge improvement in writing (g = 0.6867). Mixed-effects subgroup analyses detected no statistically significant differences by experimental design (pre-experimental vs. quasiexperimental), educational level (tertiary vs. secondary), or region (metropolitan vs. others). Meta-regression trends for duration (weeks, positive) and weekly intensity (sessions/week, negative) were suggestive but not statistically significant. Overall, ChatGPT-supported writing instruction yields meaningful gains and shows consistent effects at both secondary and tertiary levels; in practice, it is well suited to complement teacher feedback. Future studies should expand samples in secondary and nonmetropolitan settings and employ stronger designs to clarify how duration and intensity shape outcomes.
5,400원
9.
2025.12
구독 인증기관 무료, 개인회원 유료
This study examines the development of English for Specific Purposes (ESP) education in Korea and the emerging role of artificial intelligence (AI) within this context. Three datasets were analyzed to provide a comprehensive perspective: 890 international ESP articles and 30 Korean ESP studies to identify research trends; 1,386 AI-assisted English Language Teaching (ELT) studies—1,021 international and 365 domestic—to compare AI applications in general English and ESP education; and a subset of 340 AI-ESP studies (332 international, 8 domestic) to explore their intersection. The findings reveal that international ESP research has evolved toward genre-based writing instruction, corpus-informed pedagogy, and teacher identity, whereas Korean ESP studies remain focused on occupational English (e.g., nursing, military) with limited discourse-based approaches. AI integration in ELT is rapidly expanding for personalized learning, feedback, and automated assessment, yet remains underexplored in Korean ESP contexts. The study calls for interdisciplinary, pedagogically grounded, and ethically informed integration of AI in future ESP education.
8,000원
10.
2025.12
구독 인증기관 무료, 개인회원 유료
The primary purpose of this study is to critically examine ethical challenges arising from integrating AI into language education. While tools such as large language models, machine translation, automated writing feedback, and speech recognition offer gains in personalization, language development, and efficiency, their rapid adoption raises several ethical concerns. Six challenges are discussed: data privacy and security, academic integrity, overreliance on AI, algorithmic bias, and widening educational divides tied to access and digital literacy. Drawing on recent empirical findings and theoretical insights, this paper also underscores risks such as the erosion of critical thinking, challenges to academic honesty, exclusion of diverse linguistic identities, and exacerbation of inequities. To address these challenges, the study proposes a multi-faceted framework comprising robust data protection, bias-aware language practice, human-AI collaboration, process-oriented instruction, and teacher training. These measures aim to foster a responsible and ethical approach to AI use, ensuring that AI supports equitable, inclusive, and effective language learning and teaching while preserving the inherently social and humanistic nature of language education.
5,500원
