Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study.

IF 4.7 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Helen Zhang, Irene Lee, Safinah Ali, Daniella DiPaola, Yihong Cheng, Cynthia Breazeal
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引用次数: 0

Abstract

The rapid expansion of artificial intelligence (AI) necessitates promoting AI education at the K-12 level. However, educating young learners to become AI literate citizens poses several challenges. The components of AI literacy are ill-defined and it is unclear to what extent middle school students can engage in learning about AI as a sociotechnical system with socio-political implications. In this paper we posit that students must learn three core domains of AI: technical concepts and processes, ethical and societal implications, and career futures in the AI era. This paper describes the design and implementation of the Developing AI Literacy (DAILy) workshop that aimed to integrate middle school students' learning of the three domains. We found that after the workshop, most students developed a general understanding of AI concepts and processes (e.g., supervised learning and logic systems). More importantly, they were able to identify bias, describe ways to mitigate bias in machine learning, and start to consider how AI may impact their future lives and careers. At exit, nearly half of the students explained AI as not just a technical subject, but one that has personal, career, and societal implications. Overall, this finding suggests that the approach of incorporating ethics and career futures into AI education is age appropriate and effective for developing AI literacy among middle school students. This study contributes to the field of AI Education by presenting a model of integrating ethics into the teaching of AI that is appropriate for middle school students.

将道德和职业前途与技术学习相结合促进中学生人工智能素养的探索性研究
人工智能(AI)的迅速发展要求在 K-12 阶段推广人工智能教育。然而,教育年轻学生成为有人工智能素养的公民面临着一些挑战。人工智能素养的组成要素界定不清,中学生能在多大程度上参与学习人工智能这一具有社会政治影响的社会技术系统也不明确。在本文中,我们认为学生必须学习人工智能的三个核心领域:技术概念和流程、伦理和社会影响以及人工智能时代的职业前景。本文介绍了 "发展人工智能素养(DAILy)"研讨会的设计和实施,该研讨会旨在整合中学生对这三个领域的学习。我们发现,工作坊结束后,大多数学生对人工智能概念和流程(如监督学习和逻辑系统)有了总体了解。更重要的是,他们能够识别偏见,描述在机器学习中减少偏见的方法,并开始考虑人工智能会如何影响他们未来的生活和职业。毕业时,近一半的学生将人工智能解释为不仅仅是一门技术学科,而是一门对个人、职业和社会都有影响的学科。总之,这一发现表明,将伦理和职业未来纳入人工智能教育的方法适合初中生的年龄特点,并能有效培养他们的人工智能素养。本研究提出了一种适合中学生的将伦理融入人工智能教学的模式,为人工智能教育领域做出了贡献。
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来源期刊
International Journal of Artificial Intelligence in Education
International Journal of Artificial Intelligence in Education COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
11.10
自引率
6.10%
发文量
32
期刊介绍: IJAIED publishes papers concerned with the application of AI to education. It aims to help the development of principles for the design of computer-based learning systems. Its premise is that such principles involve the modelling and representation of relevant aspects of knowledge, before implementation or during execution, and hence require the application of AI techniques and concepts. IJAIED has a very broad notion of the scope of AI and of a ''computer-based learning system'', as indicated by the following list of topics considered to be within the scope of IJAIED: adaptive and intelligent multimedia and hypermedia systemsagent-based learning environmentsAIED and teacher educationarchitectures for AIED systemsassessment and testing of learning outcomesauthoring systems and shells for AIED systemsbayesian and statistical methodscase-based systemscognitive developmentcognitive models of problem-solvingcognitive tools for learningcomputer-assisted language learningcomputer-supported collaborative learningdialogue (argumentation, explanation, negotiation, etc.) discovery environments and microworldsdistributed learning environmentseducational roboticsembedded training systemsempirical studies to inform the design of learning environmentsenvironments to support the learning of programmingevaluation of AIED systemsformal models of components of AIED systemshelp and advice systemshuman factors and interface designinstructional design principlesinstructional planningintelligent agents on the internetintelligent courseware for computer-based trainingintelligent tutoring systemsknowledge and skill acquisitionknowledge representation for instructionmodelling metacognitive skillsmodelling pedagogical interactionsmotivationnatural language interfaces for instructional systemsnetworked learning and teaching systemsneural models applied to AIED systemsperformance support systemspractical, real-world applications of AIED systemsqualitative reasoning in simulationssituated learning and cognitive apprenticeshipsocial and cultural aspects of learningstudent modelling and cognitive diagnosissupport for knowledge building communitiessupport for networked communicationtheories of learning and conceptual changetools for administration and curriculum integrationtools for the guided exploration of information resources
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