Dataset for ESP Teachers' Survey on Online Debriefing and AI Integration in Ukrainian Universities (2024–2025)

This dataset contains qualitative and quantitative data collected during a study on the integration of online debriefing and artificial intelligence (AI) in English for Specific Purposes (ESP) courses in Ukrainian higher education. The dataset documents ESP teachers’ attitudes, experiences, perceived benefits, and challenges related to debriefing practices, including AI-assisted feedback and reflection. Data were collected from 34 ESP teachers representing three Ukrainian universities during 2024–2025. The dataset includes: (S1) the full questionnaire with anonymized responses exported from Google Forms (PDF); (S2) an Excel file with Likert-scale data processed for descriptive analysis; (S3) screenshots of aggregated questionnaire results generated by Google Forms; (S4) anonymized open-ended responses used for qualitative analysis; and (S5) a structured codebook with themes, codes, and illustrative citations developed through thematic analysis. Quantitative data were analyzed using descriptive statistics, while qualitative interview and open-ended responses were analyzed following Braun and Clarke’s six-step thematic analysis framework. The dataset supports transparency, replication, and secondary analysis in research on ESP pedagogy, reflective teaching practices, online debriefing, and responsible AI use in higher education. All data were collected with informed consent and anonymized prior to sharing.本数据集收录了一项针对乌克兰高等教育阶段专门用途英语（English for Specific Purposes, ESP）课程中融入在线复盘与人工智能（Artificial Intelligence, AI）的研究所得的定性与定量数据。本数据集记录了ESP教师与复盘实践（含人工智能辅助反馈与反思环节）相关的态度、经历、感知收益与挑战。 数据采集于2024至2025年间，受访对象为来自乌克兰3所高校的34名ESP教师。本数据集包含以下内容：(S1) 从Google Forms导出的含匿名化作答数据的完整问卷（PDF格式）；(S2) 经处理用于描述性分析的李克特量表（Likert-scale）数据Excel文件；(S3) Google Forms生成的问卷汇总结果截图；(S4) 用于定性分析的匿名化开放式作答内容；(S5) 通过主题分析法构建的含主题、编码与示例引用的结构化编码手册。 定量数据采用描述性统计方法进行分析，定性访谈与开放式作答则遵循Braun与Clarke的六步主题分析法框架开展分析。本数据集可为专门用途英语教学法、反思性教学实践、在线复盘以及高等教育领域负责任人工智能应用等方向的研究提供透明度保障、可复现性支持与二次分析基础。所有数据均通过知情同意流程采集，并在共享前完成匿名化处理。