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是什么驱动了学生使用AI聊天机器人?对话式AI中的技术接受度

What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI

North Carolina State University(北卡罗来纳州立大学);Pennsylvania State University(宾夕法尼亚州立大学)

Griffin Pitts, Sanaz Motamedi

AI总结:

研究探讨了学生使用对话式AI的驱动因素,发现感知有用性是主要影响因素,信任和主观规范也起重要作用。

摘要:

对话式AI工具已被学生迅速采用,并成为他们学习日常的一部分。为了理解这种采用背后的原因,我们借鉴技术接受模型(TAM),并考察感知有用性和感知易用性如何影响学生使用能够为学习任务生成响应的对话式AI的行为意图。我们通过引入信任、感知愉悦和主观规范作为额外因素来扩展TAM,这些因素捕捉了社会和情感影响以及对AI输出的不确定性的影响。使用偏最小二乘结构方程建模,我们发现感知有用性仍然是预测学生使用对话式AI意图的最强预测因素。然而,在考虑其他因素后,感知易用性对行为意图没有显著的直接效应,而是通过感知有用性间接发挥作用。信任和主观规范显著影响对有用性的感知,而感知愉悦则对使用意图产生直接和间接的影响。这些发现表明,对话式AI系统的采用决策受到努力相关考虑的影响较小,而更多受到对系统输出的信心、情感参与和社会背景的影响。未来的研究需要进一步探讨这些接受关系如何在不同的对话系统和使用情境中推广。

英文摘要:

Conversational AI tools have been rapidly adopted by students and are becoming part of their learning routines. This widespread use comes amid ongoing concerns about the reliability of AI-generated responses and the appropriate role of AI in education. Drawing on the Technology Acceptance Model, we examine how students' perceptions of conversational AI, including its usefulness, ease of use, trustworthiness, enjoyment, and social influence, relate to their intentions to use these tools for learning. We investigate both the direct and indirect relationships among these perceptions to understand how they are associated with students' behavioral intentions. Using survey data from 229 students and partial least squares structural equation modeling, we found that perceived usefulness was the strongest direct predictor of intention, followed by perceived enjoyment. Perceived ease of use, trust, and subjective norms did not have significant direct associations with intention. However, trust and subjective norms had significant total indirect associations, while perceived enjoyment had both significant direct and indirect associations. The model explained 70.2% of the variance in behavioral intention. These findings suggest that students' intentions to use conversational AI are associated less directly with effort-related considerations and more with perceived usefulness and affective experience. They also highlight the importance of understanding what students perceive as valuable in conversational AI interactions, particularly when designing tools intended to encourage engagement while supporting learning.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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