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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.14769 |
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| _version_ | 1866913399726669824 |
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| author | Zaphir, Luke Lodge, Jason M. Lisec, Jacinta McGrath, Dom Khosravi, Hassan |
| author_facet | Zaphir, Luke Lodge, Jason M. Lisec, Jacinta McGrath, Dom Khosravi, Hassan |
| contents | Generative AI such as those with large language models have created opportunities for innovative assessment design practices. Due to recent technological developments, there is a need to know the limits and capabilities of generative AI in terms of simulating cognitive skills. Assessing student critical thinking skills has been a feature of assessment for time immemorial, but the demands of digital assessment create unique challenges for equity, academic integrity and assessment authorship. Educators need a framework for determining their assessments vulnerability to generative AI to inform assessment design practices. This paper presents a framework that explores the capabilities of the LLM ChatGPT4 application, which is the current industry benchmark. This paper presents the Mapping of questions, AI vulnerability testing, Grading, Evaluation (MAGE) framework to methodically critique their assessments within their own disciplinary contexts. This critique will provide specific and targeted indications of their questions vulnerabilities in terms of the critical thinking skills. This can go on to form the basis of assessment design for their tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_14769 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | How critically can an AI think? A framework for evaluating the quality of thinking of generative artificial intelligence Zaphir, Luke Lodge, Jason M. Lisec, Jacinta McGrath, Dom Khosravi, Hassan Artificial Intelligence Generative AI such as those with large language models have created opportunities for innovative assessment design practices. Due to recent technological developments, there is a need to know the limits and capabilities of generative AI in terms of simulating cognitive skills. Assessing student critical thinking skills has been a feature of assessment for time immemorial, but the demands of digital assessment create unique challenges for equity, academic integrity and assessment authorship. Educators need a framework for determining their assessments vulnerability to generative AI to inform assessment design practices. This paper presents a framework that explores the capabilities of the LLM ChatGPT4 application, which is the current industry benchmark. This paper presents the Mapping of questions, AI vulnerability testing, Grading, Evaluation (MAGE) framework to methodically critique their assessments within their own disciplinary contexts. This critique will provide specific and targeted indications of their questions vulnerabilities in terms of the critical thinking skills. This can go on to form the basis of assessment design for their tasks. |
| title | How critically can an AI think? A framework for evaluating the quality of thinking of generative artificial intelligence |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2406.14769 |