A Comparison of Human-Written Versus AI-Generated Text in Discussions at Educational Settings: Investigating Features for ChatGPT, Gemini and BingAI

IF 3.6 3区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH European Journal of Education Pub Date : 2025-01-31 DOI:10.1111/ejed.70014
Hatice Yildiz Durak, Figen Eğin, Aytuğ Onan
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Abstract

Generative artificial intelligence (GenAI) models, such as ChatGPT, Gemini, and BingAI, have become integral to educational sciences, bringing about significant transformations in the education system and the processes of knowledge production. These advancements have facilitated new methods of teaching, learning, and information dissemination. However, the widespread adoption of these technologies raises serious concerns about academic ethics, content authenticity, and the potential for misuse in academic settings. This study aims to evaluate the linguistic features and differences between AI-generated and human-generated articles in educational contexts. By analysing various linguistic attributes such as singular word usage, sentence lengths, and the presence of repetitive or stereotypical phrases, the study identifies key distinctions between the two types of content. The findings indicate that human-generated articles exhibit higher average singular word usage and longer sentence lengths compared to AI-generated articles, suggesting a more complex and nuanced language structure in human writing. Furthermore, the study employs ensemble learning models, including Random Forest, Gradient Boosting, AdaBoost, Bagging, and Extra Trees, to classify and distinguish between AI-generated and human-generated texts. Among these, the Extra Trees model achieved the highest classification accuracy of 93%, highlighting its effectiveness in identifying AI-generated content. Additionally, experiments using the BERTurk model, a transformer-based language model, demonstrated a classification accuracy of 95%, particularly in distinguishing human-generated articles from those produced by Gemini. The results of this study have significant implications for the future of education, as they underscore the critical need for robust tools and methodologies to differentiate between human and AI-generated content.

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在教育环境下讨论中人类书写的文本与人工智能生成的文本的比较:调查ChatGPT、Gemini和BingAI的特征
ChatGPT、Gemini和BingAI等生成式人工智能(GenAI)模型已经成为教育科学不可或缺的一部分,给教育系统和知识生产过程带来了重大变革。这些进步促进了教学、学习和信息传播的新方法。然而,这些技术的广泛采用引发了对学术道德、内容真实性以及在学术环境中滥用的可能性的严重担忧。本研究旨在评估教育语境中人工智能文章和人工文章的语言特征和差异。通过分析各种语言属性,如单字用法、句子长度、重复短语或刻板短语的存在,该研究确定了两种类型内容之间的关键区别。研究结果表明,与人工智能生成的文章相比,人工生成的文章平均单字使用量更高,句子长度更长,这表明人类写作的语言结构更复杂、更微妙。此外,该研究采用集成学习模型,包括随机森林、梯度增强、AdaBoost、Bagging和Extra Trees,对人工智能生成的文本和人类生成的文本进行分类和区分。其中,Extra Trees模型的分类准确率最高,达到93%,突出了其在识别人工智能生成内容方面的有效性。此外,使用BERTurk模型(一种基于变压器的语言模型)进行的实验表明,分类准确率达到95%,特别是在区分人工生成的文章和Gemini生成的文章方面。这项研究的结果对未来的教育具有重要意义,因为它们强调了对区分人类和人工智能生成内容的强大工具和方法的迫切需要。
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来源期刊
European Journal of Education
European Journal of Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
4.50
自引率
0.00%
发文量
47
期刊介绍: The prime aims of the European Journal of Education are: - To examine, compare and assess education policies, trends, reforms and programmes of European countries in an international perspective - To disseminate policy debates and research results to a wide audience of academics, researchers, practitioners and students of education sciences - To contribute to the policy debate at the national and European level by providing European administrators and policy-makers in international organisations, national and local governments with comparative and up-to-date material centred on specific themes of common interest.
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