Summary of The Application Of Gpt-4 in Grading Design University Students’ Assignment and Providing Feedback: An Exploratory Study, by Qian Huang et al.
The application of GPT-4 in grading design university students’ assignment and providing feedback: An exploratory study
by Qian Huang, Thijs Willems, King Wang Poon
First submitted to arxiv on: 26 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study explores the effectiveness of GPT-4 in grading design assignments for university students, providing constructive feedback, and achieving reliable results. Design education often involves subjective open-ended problems, leading to inconsistent grades between raters. The research employs an iterative approach to develop a Custom GPT, testing its reliability and ability to provide useful feedback. Key findings include the development of a Custom GPT with high inter-reliability (0.65-0.78) with human raters, indicating consistent scoring results. This study demonstrates that a Custom GPT can be developed to adhere to the rules of consistency and comparability, making it a reliable complement to human raters. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at whether a special AI model called GPT-4 can help grade design projects for university students and give them useful feedback. Design projects are often open-ended and subjective, which makes grading tricky because different people might give different grades. The researchers wanted to see if they could make the AI model more reliable by teaching it how to provide consistent feedback. They found that with some training, the AI model can be used to grade design projects reliably and give students helpful feedback. |
Keywords
» Artificial intelligence » Gpt
