Development of an AI literacy assessment for non-technical individuals: What do teachers know?

IF 2.4 Q1 EDUCATION & EDUCATIONAL RESEARCH Contemporary Educational Technology Pub Date : 2024-07-01 DOI:10.30935/cedtech/14619
Lu Ding, Sohee Kim, R. A. Allday
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Abstract

With the exponential development and vast interest in artificial intelligence (AI), the global economic impact of AI is expected to reach $15.7 trillion by 2030. While AI has infiltrated everyday life, a lack of knowledge of what AI is and how AI works is ubiquitous across all ages and professions. Teaching AI literacy to non-technical individuals has become imperative and requires immediate attention, however, assessing AI literacy has heavily relied on subjective measurements such as qualitative assessment and self-reported surveys, which may lead to biased results. This study contributes to the field by developing and validating an assessment created based on a well-established AI literacy framework. A total of 196 responses were collected from pre-and in-service teachers in the United States, and 186 responses were included in the analysis to validate the assessment. The final assessment comprises 25 objective-based items reduced from an originally 31-item assessment. Both experts’ insights were sought, and statistical methodology was employed to ensure the validity of the assessment. The results indicate that pre-and in-service teachers have a moderate level of AI literacy and in-service teachers performed slightly better than pre-service teachers on our assessment. Inconsistent answers across various AI concepts indicate that teachers may possess an even more ambiguous understanding of certain AI concepts.
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为非技术人员开发人工智能素养评估:教师知道什么?
随着人工智能(AI)的指数级发展和广泛关注,预计到 2030 年,人工智能对全球经济的影响将达到 15.7 万亿美元。虽然人工智能已经渗透到日常生活中,但对人工智能是什么以及人工智能如何工作缺乏了解的现象在各个年龄段和各个职业中普遍存在。向非技术人员传授人工智能素养已成为当务之急,需要立即引起重视。然而,评估人工智能素养在很大程度上依赖于主观测量,如定性评估和自我报告调查,这可能会导致结果偏差。本研究通过开发和验证基于成熟的人工智能素养框架创建的评估方法,为该领域做出了贡献。从美国的职前和在职教师那里共收集到 196 份答卷,其中 186 份答卷被纳入分析,以验证评估结果。最终的评估由 25 个客观项目组成,而最初的评估项目为 31 个。为确保评估的有效性,我们征求了专家的意见,并采用了统计方法。结果表明,职前和在职教师的人工智能素养处于中等水平,在职教师在评估中的表现略好于职前教师。对各种人工智能概念的回答不一致,表明教师对某些人工智能概念的理解可能更加模糊。
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来源期刊
Contemporary Educational Technology
Contemporary Educational Technology Social Sciences-Education
CiteScore
6.20
自引率
0.00%
发文量
55
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