Summary of Dr.academy: a Benchmark For Evaluating Questioning Capability in Education For Large Language Models, by Yuyan Chen et al.
Dr.Academy: A Benchmark for Evaluating Questioning Capability in Education for Large Language Models
by Yuyan Chen, Chenwei Wu, Songzhou Yan, Panjun Liu, Haoyu Zhou, Yanghua Xiao
First submitted to arxiv on: 20 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computers and Society (cs.CY)
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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 Large language models (LLMs) are being explored for their potential to educate students through personalized learning. While LLMs have shown promise in comprehension and problem-solving, their ability to teach remains largely unexplored. This study focuses on evaluating the questioning capability of LLMs as educators by assessing their generated educational questions using Anderson and Krathwohl’s taxonomy across general, monodisciplinary, and interdisciplinary domains. Four metrics – relevance, coverage, representativeness, and consistency – are used to evaluate the educational quality of LLM outputs. The results show that GPT-4 demonstrates potential in teaching general, humanities, and science courses, while Claude2 appears more suited for interdisciplinary education. Additionally, automatic scores align with human perspectives. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how well large language models (LLMs) can teach students. LLMs are like super smart computers that can help learn new things. Right now, we’re not sure if they can actually teach students effectively. So, this study tested how well LLMs can generate educational questions using a special way of organizing knowledge called Anderson and Krathwohl’s taxonomy. The results show that some LLMs are better at teaching certain subjects than others. This is an important area of research because it could help us use computers to make learning more personalized and fun. |
Keywords
» Artificial intelligence » Gpt
