背景(考古学)
定性研究
生成语法
集合(抽象数据类型)
数据收集
教育研究
研究方法
计算机科学
数据科学
心理学
社会学
数学教育
人工智能
社会科学
古生物学
人口
人口学
生物
程序设计语言
作者
Cheryl Burleigh,Andrea Wilson
出处
期刊:Journal of Educational Technology Systems
[SAGE]
日期:2024-08-14
标识
DOI:10.1177/00472395241270278
摘要
With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular attention to the use of GAI in collecting new data for a doctoral dissertation. This study employed qualitative methodology examining how GAI, specifically ChatGPT, responded to interview questions from a previously published article by the researchers to determine how closely chatbots mimic responses from the actual study participants. The researchers found that data integrity in qualitative research may be at risk if higher education institutions do not set clear policies and specific parameters for how doctoral research data is obtained and validated in light of GAI.
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