マイケル バー   Michael BARR   マイケル・バー    所属   京都外国語短期大学  キャリア英語科    職種   准教授
発表年月日	2024/05/19
発表テーマ	Teacher Approaches Towards using ChatGPT to Analyze a Corpus of Student Writing Samples
会議名	JALTCALL 2024
主催者	JALT - Japan Association of Language Teachers
学会区分	国際学会
発表形式	口頭（一般）
単独共同区分	共同
国名	日本
開催地名	Meijo University, Nagoya Dome Campus
開催期間	2024/05/17～2024/05/19
発表者・共同発表者	Michael Barr, Jeanette Dennisson
概要	AI tools such as ChatGPT can be used to great advantage by teachers, classes, and individual students to improve the quality of Academic English writing skills while providing superior and more customized feedback within the parameters of specific writing assignments. The authors intend to showcase the various ways ChatGPT could support best teaching practices and successful methodologies for writing tasks based on the analysis of a corpus of student writing samples collected before the arrival of ChatGPT. Three academic years of student writing samples were analyzed. Undergraduate EFL students of different CEFR levels were instructed to write 100+ words within 10 minutes according to a specific writing theme or prompt. These writing samples were then collected, digitized, and anonymized before they were separately analyzed by each author using ChatGPT. The results of each analysis were compared and interpreted in order to understand trends in student writing which could direct future coursework. Such an objective analysis of student work using ChatGPT can be extremely beneficial in (1) identifying areas that need improvement, (2) evaluating individual student progress, and (3) directly informing ChatGPT-based methodology in the teaching process.