调整和比较ChatGPT和人类作为学习促进者的价值:一种价值敏感的设计方法

IF 8.1 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Yuan Shen, Luzhen Tang, Huixiao Le, Shufang Tan, Yueying Zhao, Kejie Shen, Xinyu Li, Torsten Juelich, Qiong Wang, Dragan Gašević, Yizhou Fan
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引用次数: 0

摘要

自从人工智能(AI)给教育实践和系统带来巨大创新和挑战以来,伦理问题已成为教育领域的中心话题。价值观影响我们的道德信仰,并指导我们在不同情况下的道德行为。然而,关于提高技术中嵌入的价值观与学习者优先考虑的价值观之间的一致性的实证研究有限。利用价值敏感设计(VSD)的方法,本研究进行了一项实证调查,探讨:(1)学习者对在线学习促进者的道德价值观在在线学习环境中是如何表征的;(2)ChatGPT和作为在线学习促进者的人类专家的具体特征如何体现这些价值观;(3)在线学习环境中发生了什么价值紧张。为了解决研究问题,我们设计了一个关于ChatGPT-4和人类专家促进的在线写作和修改的比较实验。在实验结束后,我们对59名学习者进行了半结构化访谈,了解他们的学习经历和感受。结果表明,学习者在在线学习中优先考虑响应性、社交舒适性、自主性、免于偏见和隐私的价值。与人类专家相比,ChatGPT作为推动者在体现社会舒适和自主价值方面表现出不知疲倦、友好和支持独立决策的特点。然而,ChatGPT难以解读学习者的意图和情绪,存在信息泄露的风险,在体现响应性和隐私的价值方面存在不足。在学习者群体内部以及学习者与其他利益相关者(包括开发人员和研究人员)之间都出现了价值紧张关系。这些紧张关系源于在线学习环境中相互冲突的道德价值观和实用主义考虑。我们的研究结果强调了在在线学习环境中加强价值一致性的重要性。实现这一目标的策略包括开发对价值敏感的人工智能,利用人工智能工具在体现特定价值方面的优势,以及在人工智能的整个生命周期中扩展VSD方法。使用ChatGPT作为在线学习促进者已被证明具有各种优势,但它的使用也带来了道德挑战,特别是在使其功能与学习者的价值观保持一致方面。价值敏感设计(VSD)通过将涉众的价值嵌入到技术设计中来帮助改进价值一致性。然而,学习者对在线学习环境中辅导员的价值仍在调查中。我们进行了一项对比实验,以调查学习者的价值特征,比较人工智能和人类专家的体现特征,并确定潜在的价值观张力。我们发现,在在线学习环境中,学习者优先考虑响应性、社交舒适性、自主性、免于偏见和隐私的价值。我们发现,与人类专家相比,ChatGPT在体现特定价值观方面表现出优势,但在在线学习过程中仍然存在价值观紧张和错位。我们发现,价值紧张不仅出现在学习者群体中,也出现在学习者和其他利益相关者(如开发人员和研究人员)之间。教育技术开发人员应将利益相关者的价值观嵌入人工智能工具中,以增强价值观一致性,并在他们的价值观和学习者的价值观之间寻求平衡。教育工作者应积极利用人工智能作为一种强大的工具,最大限度地发挥其体现特定价值观的优势。研究人员应该考虑将VSD方法扩展到人工智能工具的整个生命周期,以适应价值动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Aligning and comparing values of ChatGPT and human as learning facilitators: A value-sensitive design approach

Aligning and comparing values of ChatGPT and human as learning facilitators: A value-sensitive design approach

Aligning and comparing values of ChatGPT and human as learning facilitators: A value-sensitive design approach

Ethical considerations have become a central topic in education since artificial intelligence (AI) brought both great innovation and challenges to educational practices and systems. Values influence what we believe is morally right and guide how we behave ethically in different situations. However, there is limited empirical research on improving the alignment between the values embedded in technology and the values prioritised by learners. Using the approach of value-sensitive design (VSD), this study conducted an empirical investigation to explore: (1) how ethical values of learners regarding facilitators were characterised in the online learning environment, (2) how specific features of ChatGPT and human experts as online learning facilitators embody these values and (3) what value tensions occur in the online learning environment. In order to address the research questions, we designed a comparative experiment about online writing and revision facilitated by ChatGPT-4 and a human expert. We conducted semi-structured interviews with 59 learners about their learning experiences and feelings after completing the experiment. The results showed that learners prioritised the value of responsiveness, social comfort, autonomy, freedom from bias and privacy during online learning. Compared with the human expert, ChatGPT as a facilitator presented features of tirelessness, friendliness and support for independent decision-making in embodying the value of social comfort and autonomy. However, ChatGPT struggled to interpret learners' intentions and emotions and posed risks of information leakage, thereby presenting a deficiency in embodying the value of responsiveness and privacy. Value tensions arose both within learners' groups and between learners and other stakeholders, including developers and researchers. These tensions emerged from conflicting ethical values and pragmatic considerations in the online learning environment. Our findings highlight the importance of enhancing value alignment in online learning environments. The strategies for achieving this include developing value-sensitive AI, leveraging the strengths of AI tools in embodying specific values, and expanding VSD methodology in AI's entire life cycle.

Practitioner notes

What is already known about this topic

  • Using ChatGPT as an online learning facilitator has been demonstrated to have various advantages, but its use also brings ethical challenges, particularly in aligning its features with the values of learners.
  • Value-sensitive design (VSD) helps improve value alignment by embedding the values of stakeholders into the technology design. However, the values of learners regarding facilitators in online learning environments remain under investigation.

What this paper adds

  • We conducted a comparative experiment to investigate the value characteristics of learners, compare embodied features of AI and human experts, and identify the potential tension of values.
  • We found that learners prioritised the value of responsiveness, social comfort, autonomy, freedom from bias and privacy in the online learning environment.
  • We found that ChatGPT has shown advantages in embodying specific values compared with the human expert, but value tensions and misalignment still emerged during online learning.
  • We found that value tensions not only arose within learner groups but also between learners and other stakeholders, such as developers and researchers.

Implications for practice and/or policy

  • Educational technology developers should embed stakeholders' values in AI tools to enhance value alignment and seek a balance between their values and the values of the learners.
  • Educators should actively utilise AI as a powerful tool and maximise its advantages in embodying specific values.
  • Researchers should consider expanding VSD methods to the entire life cycle of AI tools to accommodate value dynamism.
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来源期刊
British Journal of Educational Technology
British Journal of Educational Technology EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.60
自引率
4.50%
发文量
111
期刊介绍: BJET is a primary source for academics and professionals in the fields of digital educational and training technology throughout the world. The Journal is published by Wiley on behalf of The British Educational Research Association (BERA). It publishes theoretical perspectives, methodological developments and high quality empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.
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