对高等教育中大语言模型教育反馈的评估：潜力、限制及对教育实践的影响
Evaluation of Large Language Models' educational feedback in Higher Education: potential, limitations and implications for educational practice
AI总结：
本研究评估了大语言模型在高等教育中的教育反馈潜力，发现其能生成结构良好的反馈，但需明确指导以提升教育实践效果。
摘要：
在高等教育中管理反馈实践的重要性已被广泛认可，因为它们在提高教学、学习和评估过程方面起着关键作用。在当今的教育环境中，反馈实践越来越受到技术进步的影响，特别是人工智能（AI）。理解AI对反馈生成的影响对于识别其潜在好处和建立有效的实施策略至关重要。本研究探讨了AI生成的反馈如何通过一个已确立的分析框架支持学生学习。具体而言，不同大语言模型（LLMs）生成的反馈被评估与训练课程中学生设计的项目相关联。评估过程涉及将七个LLMs提供一个由大学讲师开发的结构化评分表，该评分表定义了特定的标准和表现水平。LLMs被要求根据此评分表生成定量评估和定性反馈。AI生成的反馈随后使用Hughes、Smith和Creese的框架进行分析，以评估其结构和促进形成性学习经验的有效性。总体而言，这些发现表明，LLMs可以生成结构良好的反馈，并且在有明确上下文信息和明确指导的情况下，具有作为可持续和有意义的反馈工具的巨大潜力。
英文摘要：
The importance of managing feedback practices in higher education has been widely recognised, as they play a crucial role in enhancing teaching, learning, and assessment processes. In today's educational landscape, feedback practices are increasingly influenced by technological advancements, particularly artificial intelligence (AI). Understanding the impact of AI on feedback generation is essential for identifying its potential benefits and establishing effective implementation strategies. This study examines how AI-generated feedback supports student learning using a well-established analytical framework. Specifically, feedback produced by different Large Language Models (LLMs) was assessed in relation to student-designed projects within a training course on inclusive teaching and learning. The evaluation process involved providing seven LLMs with a structured rubric, developed by the university instructor, which defined specific criteria and performance levels. The LLMs were tasked with generating both quantitative assessments and qualitative feedback based on this rubric. The AI-generated feedback was then analysed using Hughes, Smith, and Creese's framework to evaluate its structure and effectiveness in fostering formative learning experiences. Overall, these findings indicate that LLMs can generate well-structured feedback and hold great potential as a sustainable and meaningful feedback tool, provided they are guided by clear contextual information and a well-defined instructions that will be explored further in the conclusions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
