Scholarlink

<p>The integration of AI in higher education necessitates reliable tools to assess student attitudes. Grounded in Functional Attitude Theory, this study develops and validates the Functional Attitudes toward Artificial Intelligence (FAAI) scale and identifies relevant influencing factors. Study 1 (Sample 1, <i>N</i> = 366, 158 females, <i>M</i>age = 20.21, <i>SD</i>age = 1.03) employed exploratory factor analysis (EFA) to validate the items and preliminary structure of the FAAI scale. Study 2 (Sample 2, <i>N</i> = 623, 254 males, <i>M</i>age = 21.78, <i>SD</i>age = 1.43) employed confirmatory factor analysis (CFA) to validate the three dimension structure, assess validity and reliability, test measurement invariance, and explore influencing factors. Results demonstrated that the 12-item FAAI scale comprises 3-dimension: <i>utility-knowledge</i>, <i>value-expression</i>, and <i>ego-defense</i>, with good validity, reliability, and measurement invariance across majors and genders. Moreover, UTAUT was positively correlated with utility-knowledge and value-expression, but not with ego-defense. Neuroticism is associated with greater concern and defense against AI, while openness is linked to positive attitudes. Subgroup differences emerged, with males stronger in value-expression and females in ego-defense; AI experience enhanced utility-knowledge function; STEM students showed lower ego-defense and value-expression, and rural students outperformed urban ones in these aspects. These findings may advance the understanding of how psychological needs shape AI attitudes among university students, thus providing educators and policymakers with evidence-based insights to tailor AI literacy programs and curriculum design.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Functional attitudes towards artificial intelligence among university students: Development of a scale and influencing factors

  • 期刊论文

  • 发表日期：

    2025年7月1日

查看全文
  • Angyang Li,
  • Shuo Wang

摘要

The integration of AI in higher education necessitates reliable tools to assess student attitudes. Grounded in Functional Attitude Theory, this study develops and validates the Functional Attitudes toward Artificial Intelligence (FAAI) scale and identifies relevant influencing factors. Study 1 (Sample 1, N = 366, 158 females, Mage = 20.21, SDage = 1.03) employed exploratory factor analysis (EFA) to validate the items and preliminary structure of the FAAI scale. Study 2 (Sample 2, N = 623, 254 males, Mage = 21.78, SDage = 1.43) employed confirmatory factor analysis (CFA) to validate the three dimension structure, assess validity and reliability, test measurement invariance, and explore influencing factors. Results demonstrated that the 12-item FAAI scale comprises 3-dimension: utility-knowledge, value-expression, and ego-defense, with good validity, reliability, and measurement invariance across majors and genders. Moreover, UTAUT was positively correlated with utility-knowledge and value-expression, but not with ego-defense. Neuroticism is associated with greater concern and defense against AI, while openness is linked to positive attitudes. Subgroup differences emerged, with males stronger in value-expression and females in ego-defense; AI experience enhanced utility-knowledge function; STEM students showed lower ego-defense and value-expression, and rural students outperformed urban ones in these aspects. These findings may advance the understanding of how psychological needs shape AI attitudes among university students, thus providing educators and policymakers with evidence-based insights to tailor AI literacy programs and curriculum design.