基于人工智能的gpt在实验、实证和探索性研究方法中的应用

P. S. Aithal, Shubhrajyotsna Aithal
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引用次数: 0

摘要

目的:学术研究是建立在创造新知识或对已有知识进行新解释的基础上的系统研究。根据一个研究学派,学术研究使用三种通用方法,即实验研究、实证研究和探索性研究。最近开发的基于人工智能的GPTs的使用表明,它们能够提供来自全球来源的信息,而无需直接复制任何一个来源。因此,如何将基于ai的gpt应用于这三种研究方法是一个有趣的研究问题。方法论:这是概念性研究,利用从学术文章、基于人工智能的gtp等各种来源获得的信息,了解基于人工智能的gtp在实验研究、实证研究和探索性研究方法的各个阶段的使用情况。结果/分析:本文分析和评估了基于人工智能的GPTs如何帮助研究人员在实验研究、实证研究和探索性研究的各个阶段,通过支持研究人员应用各种更高层次的研究技能,包括设计、分析、比较、评估、解释和创造新知识。原创性/价值:本文讨论了最近发明的人工智能引擎(如GPTs)如何帮助研究人员提高其研究成果的价值。研究类型:概念研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of AI-Based GPTs in Experimental, Empirical, and Exploratory Research Methods
Purpose: Academic research is a systematic study based on the creation of new knowledge or new interpretations of existing knowledge. As per one school of studies, academic research uses three generic methods known as experimental research, empirical research, and exploratory research. The use of recently developed AI-based GPTs have shown their ability to provide information from global sources without directly copying from any one source. Thus, it is an interesting research problem on how AI-based GPTs can be used in all three types of research methods. Methodology: This is conceptual research and makes use of the information obtained from various sources like scholarly articles, AI-based GPTs to know the use of AI-based GTPs at various stages of experimental research, empirical research, and exploratory research methods. Results/Analysis: The paper analysed and evaluated how the AI-based GPTs help the researchers at various stages of experimental research, empirical research, and exploratory research by supporting the researchers to apply various higher-level research skills including design, analysis, comparison, evaluation, interpretation, and creation of new knowledge. Originality/Value: The paper discusses how recently invented artificial intelligence engines like GPTs help researchers to improve the value of their research outcomes. Type of Research: Conceptual research.
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