AI enhanced feedback: a systematic review to explore the current state of the art

Dataset documents the article selection process carried out for the systematic literature review entitled “AI enhanced feedback: a systematic review to explore the current state of the art.” It contains the complete screening log used to identify, assess, and include empirical studies focused on AI-based feedback in educational contexts, published between 2021 and 2025. The dataset includes the following information for each record: Authors and title Year of publication Source database (ERIC, Scopus) Relevance screening (Title/Abstract) Full-text eligibility assessment Inclusion/exclusion decisions Reasons for exclusion (when applicable) Final selection outcome The file reflects the application of the PRISMA methodology and provides full transparency of the selection workflow. It supports the reproducibility and rigour of the review process and may be used as a reference for future systematic reviews in the field of educational technology, feedback, and artificial intelligence.本数据集记录了题为《人工智能（AI）增强型反馈：探索当前研究现状的系统综述》的系统文献综述所采用的文献遴选流程。 本数据集包含完整的筛查日志，用于识别、评估并收录2021年至2025年间发表的、聚焦教育场景中基于人工智能的反馈的实证研究。本数据集为每条记录包含以下信息： - 作者与论文标题 - 出版年份 - 来源数据库（ERIC、Scopus） - 相关性筛查（标题/摘要阶段） - 全文资格评估 - 收录/排除决策 - 排除理由（如适用） - 最终遴选结果 本数据集采用了PRISMA方法学，完整公开了文献筛选工作流程，可保障综述流程的可重复性与严谨性，亦可作为教育技术、反馈领域及人工智能领域后续系统综述的参考范本。