[论文解读] What Explains Teachers' Trust of AI in Education across Six Countries?

Olga Viberg, Mutlu Cukurova+10 more|arXiv (Cornell University)|Dec 4, 2023

Online Learning and Analytics被引用 12

一句话总结

本研究在六个国家对 508 名 K-12 教师进行调查，旨在识别感知利益、关注点、AI 自我效能、AI 理解、文化价值以及地理位置如何影响教师对 AI-EdTech 的信任。

ABSTRACT

With growing expectations to use AI-based educational technology (AI-EdTech) to improve students' learning outcomes and enrich teaching practice, teachers play a central role in the adoption of AI-EdTech in classrooms. Teachers' willingness to accept vulnerability by integrating technology into their everyday teaching practice, that is, their trust in AI-EdTech, will depend on how much they expect it to benefit them versus how many concerns it raises for them. In this study, we surveyed 508 K-12 teachers across six countries on four continents to understand which teacher characteristics shape teachers' trust in AI-EdTech, and its proposed antecedents, perceived benefits and concerns about AI-EdTech. We examined a comprehensive set of characteristics including demographic and professional characteristics (age, gender, subject, years of experience, etc.), cultural values (Hofstede's cultural dimensions), geographic locations (Brazil, Israel, Japan, Norway, Sweden, USA), and psychological factors (self-efficacy and understanding). Using multiple regression analysis, we found that teachers with higher AI-EdTech self-efficacy and AI understanding perceive more benefits, fewer concerns, and report more trust in AI-EdTech. We also found geographic and cultural differences in teachers' trust in AI-EdTech, but no demographic differences emerged based on their age, gender, or level of education. The findings provide a comprehensive, international account of factors associated with teachers' trust in AI-EdTech. Efforts to raise teachers' understanding of, and trust in AI-EdTech, while considering their cultural values are encouraged to support its adoption in K-12 education.

研究动机与目标

• 调查教师对 AI-EdTech 的信任如何受到对 AI-EdTech 的感知利益与关注的影响。
• 考察教师人口统计学特征、职业特征、AI 自我效能以及 AI 理解的作用。
• 评估文化价值（霍夫斯泰德维度）对信任、利益和关注的影响。
• 评估六个国家（Brazil, Israel, Japan, Norway, Sweden, USA）之间信任的地理差异。
• 提供国际视角，以为在 K-12 教育中推动 AI-EdTech 采用的干预措施提供信息。

提出的方法

• 在六个国家（Brazil, Israel, Japan, Norway, Sweden, USA）对 508 名 K-12 教师进行跨国调查。
• 使用经验证的量表测量对 AI-EdTech 的信任、感知利益、关注、AI 自我效能以及 AI 理解。
• 在个体层面使用 CVSCALE 基于霍夫斯泰德维度评估文化价值。
• 使用国家固定效应多元线性回归和缺失数据的多重插补（10 次插补）来分析数据。
• 通过回归模型检验信任及其前因（利益和关注）与教师特征之间的关系。

实验结果

研究问题

• RQ1 在多大程度上，K-12 教师对 AI-EdTech 的信任可以用对 AI-EdTech 的感知利益和关注来解释？
• RQ2 人口统计学和职业特征、AI 自我效能、AI 理解、文化价值以及地理位置如何与教师对 AI-EdTech 的信任相关？
• RQ3 文化价值和地理位置是否解释了跨国在感知利益、关注和信任方面的变异？

主要发现

• 更高的 AI-EdTech 自我效能感和更强的 AI 理解与更高的感知利益、较少的关注以及对 AI-EdTech 的更高信任相关。
• 感知利益与关注与信任显著相关，利益与信任正相关，关注与信任负相关。
• 六个国家中教师对 AI-EdTech 的信任存在地理和文化差异。
• 在教师中未发现年龄、性别或最高教育水平在信任方面的差异。
• 利益、关注和信任相互关联，并随文化价值及国家/情境因素而异。