Comparative Study of Thematic Choice and Progression on Text Written by Humans and AI Machine

S. Suharsono, A. Ashadi, Titik Sudartinah
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Abstract

The development of AI technology has enabled machines to carry out tasks that previously could only be done by humans. Scientists of AI have recently launched a tool called ChatGPT. It is a tool that can do whatever is ordered by humans, including making academic writing like an abstract. Thus, this study aimed to compare thematic choice and thematic progression on the text of research abstracts of undergraduate students of Teacher College and those by ChatGPT (AI machine). To analyze the data, this study employed the thematic structure of Systemic Functional Linguistics developed by Halliday Matthiessen and thematic progression developed by Bloor Bloor. The thematic choice was analyzed by observing the variety of themes appearing in the two texts, as well as the level of complexity and diversity used. Thematic progression was evaluated by examining how the themes are arranged and developed along with the development of the texts. The results of this study show that AI machine has reached a level of proficiency allowing AI to rival humans. Even though there are fundamental differences in thematic progression patterns between texts written by undergraduate students and ChatGPT, this study concludes that the two are not significantly different. Therefore, the researchers suggest that further research in a similar field may explore issues such as quality, creativity, and originality. Afterwards, this study also suggests that English teachers use this thematic structuring knowledge and skills to improve students’ writing skill. This study provides valuable insight into the capabilities and limitations of AI machine in imitating the human creative process of writing. 
人类与人工智能机器撰写文本的主题选择和进展比较研究
人工智能技术的发展使机器能够执行以前只能由人类完成的任务。人工智能科学家最近推出了一款名为 ChatGPT 的工具。这是一个可以完成人类命令的任何事情的工具,包括制作摘要等学术写作。因此,本研究旨在比较师范学院本科生和 ChatGPT(人工智能机器)对研究摘要文本的主题选择和主题进展。为了分析数据,本研究采用了 Halliday Matthiessen 提出的系统功能语言学的主题结构和 Bloor Bloor 提出的主题递进法。通过观察两个文本中出现的主题的多样性,以及所使用的复杂性和多样性水平,对主题选择进行了分析。对主题发展的评估是通过研究主题是如何随着文本的发展而安排和发展的。研究结果表明,人工智能机器的熟练程度已经达到了可以与人类相媲美的水平。尽管本科生和 ChatGPT 所写的文本在主题发展模式上存在根本差异,但本研究得出结论,二者并无显著不同。因此,研究人员建议,类似领域的进一步研究可以探讨质量、创造性和原创性等问题。之后,本研究还建议英语教师利用这些主题结构知识和技能来提高学生的写作水平。本研究为人工智能机器模仿人类创造性写作过程的能力和局限性提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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自引率
0.00%
发文量
40
审稿时长
12 weeks
期刊介绍: Information not localized
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