Answering patterns in SBA items: students, GPT3.5, and Gemini
While large language models (LLMs) are often used to generate and answer exam questions, limited work compares their performance across multiple iterations using item statistics. This study aims to fill that gap by investigating answering patterns of how LLMs respond to single-best answer (SBA) ques...
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| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/181959 |
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| Institution: | Nanyang Technological University |
| Language: | English |