AI 中文总结
本文探讨AI辅助物理实验报告评估的潜力与局限，提出将AI作为补充资源支持评估组织、反馈提供及识别学生常见困难的策略。
AI 中文摘要
将AI纳入物理实验报告的评估中，为支持学生作业的审阅和反馈的提供提供了机会。本文回顾了一项涉及使用ChatGPT模型分析实验报告的经验，并考察了影响其在教学实践中实用性的条件。分析考虑了AI模型的演变、文档处理流程以及不同的交互模式，特别关注学生报告中证据的有效可用性。研究结果表明，AI生成评估与教师评估之间的差异可能不仅与模型能力有关，还与检索和解释方程、图表、表格、单位及其他视觉元素的困难有关。本文还探讨了系统化处理成组报告的可能性，以及针对需要更集中分析的案例进行对话式审阅的方式。基于这些观察，提出了一种工作策略，其中AI作为补充资源，用于组织评估、支持反馈以及识别学生作业中反复出现的困难。分析强调了文档处理条件和证据可用性的重要性，以及教师在解释AI生成信息并做出评估和教学决策中的作用。
英文摘要
The incorporation of AI into the assessment of physics laboratory reports offers opportunities to support the review of student work and the provision of feedback. This article revisits an experience involving the use of ChatGPT models to analyze laboratory reports and examines the conditions that influence their usefulness in teaching practice. The analysis considers the evolution of AI models, document-processing procedures, and different modes of interaction, with particular attention to the effective availability of evidence contained in student reports. The findings indicate that differences between AI-generated and teacher assessments may be related not only to model capabilities but also to difficulties in retrieving and interpreting equations, graphs, tables, units, and other visual elements. The possibilities of systematic processing of sets of reports and conversational review of cases requiring more focused analysis are also examined. Based on these observations, a working strategy is proposed in which AI serves as a complementary resource for organizing assessment, supporting feedback, and identifying recurring difficulties in student work. The analysis highlights the importance of document-processing conditions and evidence availability, as well as the teacher's role in interpreting AI-generated information and making evaluative and pedagogical decisions.
