A Large Language Model Supported Synthesis of Contemporary Academic Integrity Research Trends

• URL: http://arxiv.org/abs/2401.03481v1
• Date: Sun, 7 Jan 2024 13:23:29 GMT
• Title: A Large Language Model Supported Synthesis of Contemporary Academic Integrity Research Trends
• Authors: Thomas Lancaster
• Abstract summary: This paper reports on qualitative content analysis undertaken using ChatGPT, a Large Language Model (LLM) The analysis identified 7 research themes and 13 key areas for exploration.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper reports on qualitative content analysis undertaken using ChatGPT, a Large Language Model (LLM), to identify primary research themes in current academic integrity research as well as the methodologies used to explore these areas. The analysis by the LLM identified 7 research themes and 13 key areas for exploration. The outcomes from the analysis suggest that much contemporary research in the academic integrity field is guided by technology. Technology is often explored as potential way of preventing academic misconduct, but this could also be a limiting factor when aiming to promote a culture of academic integrity. The findings underscore that LLM led research may be option in the academic integrity field, but that there is also a need for continued traditional research. The findings also indicate that researchers and educational providers should continue to develop policy and operational frameworks for academic integrity. This will help to ensure that academic standards are maintained across the wide range of settings that are present in modern education.

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