This study examines the relationship between student perceptions and their
intention to use generative AI in higher education. Drawing on Expectancy-Value
Theory (EVT), a questionnaire was developed to measure students' knowledge of
generative AI, perceived value, and perceived cost. A sample of 405 students
participated in the study, and confirmatory factor analysis was used to
validate the constructs. The results indicate a strong positive correlation
between perceived value and intention to use generative AI, and a weak negative
correlation between perceived cost and intention to use. As we continue to
explore the implications of generative AI in education and other domains, it is
crucial to carefully consider the potential long-term consequences and the
ethical dilemmas that may arise from widespread adoption.

本研究使用期望 - 价值理论考察了学生对生成式人工智能的知识、知觉价值和成本的认知与其使用意向之间的关系。结果表明，学生对生成式人工智能的知觉价值与使用意向之间存在强烈的正相关性，而对其成本的知觉则呈现弱负相关。在探讨生成式人工智能在教育和其他领域应用的潜在后果和可能出现的伦理困境时，需要认真考虑其可能造成的长期影响。

应用期望 - 价值理论测量学生对生成式人工智能（GenAI）的认知

Deconstructing Student Perceptions of Generative AI (GenAI) through an  Expectancy Value Theory (EVT)-based Instrument

This study explores university students' perceptions of generative AI (GenAI)
technologies, such as ChatGPT, in higher education, focusing on familiarity,
their willingness to engage, potential benefits and challenges, and effective
integration. A survey of 399 undergraduate and postgraduate students from
various disciplines in Hong Kong revealed a generally positive attitude towards
GenAI in teaching and learning. Students recognized the potential for
personalized learning support, writing and brainstorming assistance, and
research and analysis capabilities. However, concerns about accuracy, privacy,
ethical issues, and the impact on personal development, career prospects, and
societal values were also expressed. According to John Biggs' 3P model, student
perceptions significantly influence learning approaches and outcomes. By
understanding students' perceptions, educators and policymakers can tailor
GenAI technologies to address needs and concerns while promoting effective
learning outcomes. Insights from this study can inform policy development
around the integration of GenAI technologies into higher education. By
understanding students' perceptions and addressing their concerns, policymakers
can create well-informed guidelines and strategies for the responsible and
effective implementation of GenAI tools, ultimately enhancing teaching and
learning experiences in higher education.

本研究探讨了大学生对生成式人工智能 (GenAI) 技术（例如 ChatGPT）在高等教育中的看法，关注对技术的熟悉程度、参与意愿、潜在好处和挑战以及有效整合。从对香港来自不同学科的 399 名本科生和研究生的调查结果显示，学生普遍对利用 GenAI 进行教学和学习持积极态度。学生们认识到个性化学习支持、写作和头脑风暴的辅助以及研究和分析能力的潜力。然而，他们也表达了对准确性、隐私、伦理问题以及对个人发展、职业前景和社会价值的影响的关注。根据 John Biggs 的 3P 模型，学生的看法显著影响学习方法和成果。通过了解学生的看法，教育工作者和政策制定者可以量身定制 GenAI 技术，以解决需求和关注点，同时促进有效的学习成果。本研究的发现可以指导有关将 GenAI 技术集成到高等教育中的政策制定。通过了解学生的看法并解决他们的关注点，政策制定者可以制定明智的指南和策略，以负责任且有效地实施 GenAI 工具，从而增强高等教育的教学和学习体验。