The DOI matches its Crossref record; 47 of the 50 references it cites were found in a registry or an index.
Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study
Open accessAbstract
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.
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“More importantly, K-12 education prioritizes AI ethics to address ethical issues and dilemmas in AI development and deployment, promoting responsible AI usage (Kong et al., 2023;Zhang et al., 2023).”
From A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway (2025) · cites this paper as Zhang et al., 2023
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“It represents a fundamental shift in education, where understanding AI becomes as crucial as reading, writing, and arithmetic (Zhang et al., 2023).”
From Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education (2024) · cites this paper as Zhang et al., 2023
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“It represents a fundamental shift in education, where understanding AI becomes as crucial as reading, writing, and arithmetic (Zhang et al., 2023). current state of AI literacy in education reflects a burgeoning field, ripe with potential yet facing the challenges of early adoption.”
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Retracted
Metadata
- Authors
- Zhang, H., Lee, I., Ali, S., DiPaola, D., Cheng, Y., & Breazeal, C.
- Affiliations
- Boston College (US)
- Massachusetts Institute of Technology (US)
- MIT Media Lab (US)
- Corresponding author
- Zhang, Helen
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 33
- Issue
- 2
- Pages
- 290-324
- ISSN
- 1560-4292 (ISSN-L)
- PMC
- PMC9084886
- OpenAlex
- W4229441880
- Cited by
- 396
- References
- 50
- Citations by year
- 2026: 106 · 2025: 137 · 2024: 107 · 2023: 39
- FWCI
- 71.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- Directorate for Education and Human Resources (2022502)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Keywords
- AI literacy, artificial intelligence in education, junior high school students, AI ethics, machine learning bias, bias mitigation, supervised learning, logical systems, K-12 education, socio-technical systems
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