大型语言模型在教育领域的机遇与挑战
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1.湖南省振兴科普教育服务中心;2.湖南省教育生产装备处;3.长沙市教育考试院学业考试部;4.北京信息科技大学

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Opportunities and Challenges of Large-Scale Language Models in the Field of Education
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    摘要:

    大型语言模型代表了人工智能领域的重大进步。这项基础技术是进一步创新的关键,尽管在国际上部分地区遭到批评甚至禁止,但作为一项基础技术,大型语言模型有望成为未来创新的基石,且将长期存在。这篇论文从学生和教师的角度出发,介绍了大型语言模型在教育应用中可能带来的机遇和挑战。简要讨论了大型语言模型的当前状态及其应用。接着强调了如何使用大语言模型来创造教育内容,提高学生参与度和互动,以及增强个性化学习体验。关于大语言模型带来的挑战,我们认为教育中的大型语言模型需要教师和学习者发展相应的能力和素养,以理解这项技术、了解其限制以及此类系统的劣势。此外,本文还强调了强调批判性思维和事实检查,是整合并充分利用大型语言模型在学习环境和教学课程中的必要条件。本文还探讨了大语言模型在教育领域所带来的其他挑战,如模型输出可能存在的偏见,需要持续的人工监督,以及可能的滥用等问题,其实并不仅限于人工智能在教育中的应用。然而,我们坚信,如果处理得当,这些挑战可以在教育场景中提供洞见和机会,使学生在早期就能熟悉人工智能应用可能带来的社会偏见、关键性和风险。在文章的结尾,我们提出了如何解决这些挑战,以及确保大型语言模型以负责任和道德的方式应用于教育的建议。

    Abstract:

    Large language models(LLMs) represent significant advances in the field of artificial intelligence. This fundamental technology is key to further innovation. Despite criticism and even prohibition in some parts of the world, as a fundamental technology, large-scale language models are expected to be the cornerstone of future innovation and will exist in the long term. This paper, from the perspective of students and teachers, introduces the opportunities and challenges that large-scale language models may bring in educational applications. It briefly discusses the current status of large-scale language models and their applications. It then emphasizes how to use large language models to create educational content, increase student engagement and interaction, and enhance personalized learning experiences. Regarding the challenges brought by large language models, we believe that large-scale language models in education require teachers and learners to develop corresponding abilities and literacy to understand this technology, understand its limitations and the disadvantages of such systems. In addition, this paper also emphasizes critical thinking and fact-checking, which are necessary conditions for integrating and fully utilizing large-scale language models in learning environments and teaching courses. This paper also explores other challenges brought by large language models in the field of education, such as possible biases in model output, the need for ongoing human supervision, and possible misuse, which are not limited to the application of artificial intelligence in education. However, we firmly believe that if handled properly, these challenges can provide insights and opportunities in educational scenarios, enabling students to familiarize themselves with the social biases, criticality, and risks that may be brought by artificial intelligence applications at an early stage. At the end of the article, we propose how to address these challenges and ensure that large-scale language models are applied to education in a responsible and ethical manner.

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  • 收稿日期:2023-09-21
  • 最后修改日期:2023-09-21
  • 录用日期:2023-09-22
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