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Comparison of AI‐Generated and Instructor Feedback: No Significant Difference in Perceived Feedback Quality and Neither on Performance

形成性评价 印为红字的 控制(管理) 质量(理念) 同行反馈 感知 心理学 多媒体 显著性差异 过程(计算) 数学教育 计算机科学 治疗组和对照组 考试(生物学) 反馈调节 等价(形式语言) 医学教育 应用心理学 利克特量表 分级(工程) 非正面反馈 教学方法 反馈控制 教育技术 高等教育 质量管理 控制源 课程评价 工程教育 计算机辅助教学 元认知 定性研究
作者
Şeyma Çağlar Özhan,Perihan Tekeli,Selay Arkün‐Kocadere
出处
期刊:Journal of Computer Assisted Learning [Wiley]
卷期号:41 (5) 被引量:4
标识
DOI:10.1111/jcal.70134
摘要

ABSTRACT Background Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have difficulty allocating enough time to provide feedback. ChatGPT has the potential to deliver feedback more efficiently and effectively. Objective This study aims to investigate the effectiveness of ChatGPT‐generated feedback in students' project proposal development process. Therefore, ChatGPT‐generated and instructor's feedback are compared in terms of perceived feedback quality and performance of students. Method In the study, a post‐test control group experimental design was used. A total of 48 students enrolled in a blended course at a state university participated in the study for 6 weeks. The study was conducted using a randomised post‐test‐only control group experimental design. Students were asked to prepare a project proposal and feedback was given on each task. While the control group received instructor feedback, the experimental group received ChatGPT feedback. Data were collected via the Formative Feedback Perceptions Scale, and the students' project proposals were graded based on the rubric to evaluate their performance. Results and Conclusion According to the Mann–Whitney U test analysis, there was no statistically significant difference between the experimental and the control group regarding both students' perceived feedback quality and performance. In conclusion, it can be argued that when guided by the appropriate prompts and asked to examine assignments of similar complexity to those in this study, ChatGPT can provide feedback of similar quality and equivalence to the feedback provided by instructors. In this way, it seems possible to improve students' learning as much as an instructor with individualised feedback by ChatGPT. Finally, it should be noted that these findings are within the limitations of the specific context of project proposal development, reliance on self‐reported data, and the experimental nature of the study; it is recommended to evaluate the effectiveness of AI‐generated feedback in different contexts.
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