Naoya Shibata

This exploratory case study investigates Japanese English-as-a-foreign-language university students’ beliefs about text and suggestions produced by generative artificial intelligence (GenAI). Qualitative data were collected from questionnaire responses from 83 upper-beginner and lower-intermediate students and semi-structured interviews with 46 volunteers at a private university in central Japan. Results showed that a substantial proportion of students had a strong belief that GenAI output would be appropriate and trustworthy for their writing development due to their limited knowledge, low writing self-efficacy and perceived native-like writing norms. However, some comments highlighted the dilemma that learners understand the overuse of GenAI functions should be avoided, but they still rely on its accessibility because they believe GenAI technology produces linguistically ideal writing models. A few reported that they doubted its linguistic reliability and appropriateness even though their writing self-efficacy was low. Based on these findings, these learner belief patterns are conceptualised as generative artificial intelligence writerism (GenAI-Writerism). Although GenAI-Writerism is not necessarily negative, strong GenAI-Writerism can foster overreliance on GenAI technology and hinder students’ writing skill development. To avoid these risks, the importance of critical artificial intelligence literacy education is discussed. Finally, future research foci on GenAI-Writerism are proposed whilst considering research limitations.

Theme-based instruction (TBI) is one of the models of content-based instruction, in which learners study topics that are interesting and relevant to them (Brinton & Snow, 2017; Snow & Brinton, 2023). Although this approach is well-known in many English-as-a-second/foreign-language (ES/FL) educational contexts (Brown & Lee, 2015; Curtis, 2017; Yugandhar, 2016), research on the effects of TBI on students’ writing performance is still scarce (Ostovar-Namaghi & Nakhaee, 2019). To address this research issue, the authors conducted a one-shot model of a quantitative study with 86 first-year university students in Japan over a 15-week semester. The course covered four thematic units. The authors collected students’ perceptions of each theme before learning the unit content and their pre-/post-timed writing papers about each theme. The Wilcoxon signed-rank tests were conducted to analyze their writing samples from two perspectives (the number of tokens and syntactic complexity). Regardless of assigned themes, statistical test results revealed that the number of word tokens increased significantly, whereas syntactic complexity did not. Based on these findings, TBI does not appear to be a practical approach for facilitating learners' writing abilities to use grammatically complex sentences. Hence, other teaching approaches need to be explored and integrated with TBI when syntactic complexity development is a teaching and learning objective in writing courses.

本研究は、生成AIの発達が著しい状況において、現職英語教員及び英語教員志望学生が、第二言語ライティング指導、その専門知識、並びに当該指導法を扱う教職科目の必要性をどのように認識しているかを明らかにした。中部地区の教職経験5年以内の英語教員115名と英語教員志望の大学4年生110名を対象に、6件法による質問紙調査と半構造化面接を実施し、量的・質的データを統合して分析した。その結果、参加者は第二言語ライティング指導の必要性を概ね肯定的に評価し、指導に関する専門知識及び当該指導法に焦点を置く教職科目については、より高い必要性を認識していた。また、現職教員と教員志望学生、中学校と高等学校の各群の間に統計的に有意な差は確認されなかった。質的分析からは、自己表現、思考力の育成、資格・入学試験への対応がライティング指導の意義として挙げられる一方、授業時間の不足、教員の専門知識及び実践力の不足、生成AIの普及に伴う教員の役割の不明確さが指導上の阻害要因として示された。以上を踏まえ、理論的知識の習得と模擬授業等の実践を統合した「第二言語ライティング指導法」に関する教職科目を整備する必要性を論じた。