大学学生对生成人工智能工具的接受:关于意见,态度和行为意图的混合方法研究
Özlem Canan Güngören1, Duygu Gür Erdoğan2, M Barış Horzum3
1Computer and Educational Technology Department, Sakarya University, Hendek, Sakarya, Türkiye. ocanan@sakarya.edu.tr.
BMC psychology
|January 14, 2026
概括
大学的学生大学生.
科学领域:
- 教育技术的教育技术
- 人与计算机的交互
- 人工智能接受的人工智能接受
背景情况:
- 生成型人工智能 (AI) 工具在高等教育中越来越普遍.
- 了解学生采用这些工具对于有效的整合至关重要.
- 之前的研究已经探索了技术接受模式,但生成性AI的具体因素需要进一步调查.
研究的目的:
- 检查影响大学生接受生成性AI工具的因素.
- 调查感知到的有用性,易用性和对生成AI的行为意图之间的关系.
- 确定影响学生采用人工智能工具的人口和使用相关变量.
主要方法:
- 采用了一种连续解释混合方法设计.
- 第一阶段涉及到对土耳其601名本科生进行定量调查.
- 第二阶段使用了定性案例研究,采访了80名本科生.
主要成果:
- 感知到的有用性和感知到的易用性显著影响了接受度.
- 人口变量 (性别) 和使用模式 (持续时间,频率,目的) 是关键因素.
- 结构方程建模揭示了这些因素在塑造态度和意图方面的整体作用.
结论:
- 学生对生成人工智能的接受是一个多方面的问题,受技术感知和用户特征的影响.
- 教育机构在制定政策和培训生成性AI工具时应该考虑这些因素.
- 进一步的研究可以探索特定的生成人工智能应用及其对学习成果的影响.
相关概念视频
Stereotype Content Model
15.3K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
15.3K
Non-equilibrium in the Cell
5.3K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
5.3K
