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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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Cites
Designing and Conducting Mixed Methods Research
Robinson, P. M. (2007) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1753-6405.2007.00096.x · Cited by 23,362
Whose culture has capital? A critical race theory discussion of community cultural wealth
Yosso *, T. J. (2005) · Race Ethnicity and Education · doi:10.1080/1361332052000341006 · Cited by 8,663 · cited 1×
“This provides further evidence of student engagement as he was active in leveraging existing familial and aspirational capital (Yosso, 2005) to make sense of AI and refine his existing perceptions of AI.”
Background(2006) · Cited by 7,081
(2018) · Cited by 3,510
What is AI Literacy? Competencies and Design Considerations
Long, D., & Magerko, B. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376727 · Cited by 3,241 · cited 2×
“This approach also aligns well with the use of embodied interaction proposed in the AI Literacy framework (Design Consideration 2: Embodied Interactions, Long & Magerko, 2020) where learners can “put themselves in the agent’s shoes as a way of making sense of the agent’s reasoning process” (p. 598).”
BackgroundMethodThe Psychology of Working Theory.
Duffy, R. D., Blustein, D. L., Diemer, M. A., & Autin, K. L. (2016) · Journal of Counseling Psychology · doi:10.1037/cou0000140 · Cited by 1,209
Planning Early for Careers in Science
Tai, R. H., Liu, C. Q., Maltese, A. V., & Fan, X. (2006) · Science · doi:10.1126/science.1128690 · Cited by 1,102
Envisioning AI for K-12: What Should Every Child Know about AI?
Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33019795 · Cited by 918
Coeckelbergh, M. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/12549.001.0001 · Cited by 865
Wang, Y., & Wang, Y. (2019) · Interactive Learning Environments · doi:10.1080/10494820.2019.1674887 · Cited by 830
Research works printed but not linked: 4
- Ali, S., Payne, B. H., Williams, R., Park, H. W., & Breazeal, C. (2019). Constructionism, ethics, and creativity: Developing primary and middle school artificial intelligence education. In International workshop on education in artificial intelligence K-12 (EDUAI’19) (pp. 1–4).
- Badham, R., Clegg, C., & Wall, T. (2000). Socio-technical theory. Handbook of Ergonomics. John Wiley.
- Payne, B. H. (2020). Can my algorithm be my opinion?: An AI+ ethics curriculum for middle school students (Unpublished master’s thesis). Massachusetts Institute of Technology, Cambridge.
- Torrey, L. (2012). Teaching problem-solving in algorithms and AI. 3rd Symposium on Educational Advances in Artificial Intelligence.
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Nirchi, S., Mangione, G. R., Vincenzo, C. D., & Pettenati, M. C. (2025) · Journal of Educational Cultural and Psychological Studies (ECPS Journal) · doi:10.7358/ecps-2024-030-nirc · Cited by 5
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Yin, M. (2024) · Advances in Vocational and Technical Education · doi:10.23977/avte.2024.060303 · Cited by 4
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Kong, S. C., & Hou, C. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100503 · Cited by 10
Liu, R., & Glave, C. Z. (2025) · Journal of Research in Childhood Education · doi:10.1080/02568543.2025.2578526 · Cited by 6
Darabipourshiraz, H., Ng, L. M., Wang, G., Rollins, S. K., & Long, D. (2026) · ACM Transactions on Computing Education · doi:10.1145/3786761 · Cited by 3
Wang, Y. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2025.1745975 · Cited by 3
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Kong, S. C., & Hu, W. (2026) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2026.100556 · Cited by 7
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Xu, Y., Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H. M. L., King, I., Wong, S. W. H., & Yam, Y. (2023) · IEEE International Conference on Teaching, Assessment, and Learning for Engineering · doi:10.1109/tale56641.2023.10398321 · Cited by 3
Chen, Y., Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H. M. L., King, I., Wong, S. W. H., & Yam, Y. (2024) · International Symposium on Educational Technology · doi:10.1109/iset61814.2024.00010 · Cited by 4
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Priyanti Rusanti, S., Murtadhlo, M., Budiyanto, B., Hariyati, N., Muhimmah, H. A., & Hisham, T. S. B. (2025) · IJORER International Journal of Recent Educational Research · doi:10.46245/ijorer.v6i1.763 · Cited by 3
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Xu, H. (2025) · The Journal of General Psychology · doi:10.1080/00221309.2025.2541585 · Cited by 3
Torreciba, N. D., & Alieto, E. O. (2025) · EthAIca · doi:10.56294/ai2025416 · Cited by 4
Martins, R. M., von Wangenheim, C. G., Rauber, M. F., Hauck, J. C. R., & Silvestre, M. F. (2023) · Informatics in Education · doi:10.15388/infedu.2024.13 · Cited by 3
Preparing Teachers to Teach Artificial Intelligence in Classrooms: An Exploratory Study
Zhang, H., Lee, I. A., & Moore, K. S. (2023) · Proceedings. · doi:10.22318/icls2023.370046 · Cited by 3
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Becoming Fei: An Educational Game for AI and Data Science Education for Novice Learners
Wang, N., Fu, B., Dinçer, B. H., Masur, O., Faizi, D., Ravindran, H., Wang, J., Lai, D., & Merchant, C. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93746-0_6 · Cited by 2
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Kim, J. (2025) · Midwest journal of education. · doi:10.69670/mje.2.1.4 · Cited by 2
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Pandey, S., & Gaikwad, H. V. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-97-9526-0_35 · Cited by 2
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Owen, V., Parkman, S., Lindley, J., & Rubegni, E. (2025) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3713043.3731499 · Cited by 2
Understanding the Effects of AI Literacy Lessons on Student Usage and Understanding of LLMs
Li, G. (2025) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3702653.3744301 · Cited by 2
Revolutionizing Education with AI: Ethical Considerations in K-12 Settings
Gökçe, A. T. (2025) · Education and human development · doi:10.5772/intechopen.1012230 · Cited by 2
Machine learning-powered skill-job matching recommendation system for vocational education
Chen, Q., Lu, L., Huang, R., Sun, T., Qi, X., & Lu, X. (2025) · Journal of Computational Methods in Sciences and Engineering · doi:10.1177/14727978251391342 · Cited by 2
Vorotnykova, I. P., & Zakhar, O. (2025) · OPEN EDUCATIONAL E-ENVIRONMENT OF MODERN UNIVERSITY · doi:10.28925/2414-0325.2025.193 · Cited by 5
Fang, X., & Du, C. (2025) · Bridging human and machine: future education with intelligence · doi:10.1007/978-981-95-0950-8_7 · Cited by 2
Moore, K. S., Rabinowitz, G. S., Ali, S., Weckel, M., Lee, I. A., Gupta, P., & Chaffee, R. (2026) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2026.100552 · Cited by 3
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Li, X., Riggs, A. T., Dai, Z., Farmer, C. B., Morrison, K. G., & Howell, N. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790863 · Cited by 2
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Lin, S., & Tan, Z. (2026) · SAGE Open · doi:10.1177/21582440261463131 · Cited by 2
Толочко, С. В., Bordіug, N., & Godunova, A. V. (2024) · doi:10.30525/978-9934-26-405-4-24 · Cited by 14
Ahuja, S., & Kumar, J. (2024) · International Journal of Technology and Design Education · doi:10.1007/s10798-024-09925-2 · Cited by 4
Reddy, G. S., Rizvi, H. A., Kochhar, H. K., Shaikh, A., Udhayakumar, R., & Dhanraj, J. A. (2024) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i61595.2024.10828612 · Cited by 2
Vandenberg, J. L., Torbey, R., Zhang, C. X., Mott, B., Bailey, K., & Wilson, J. P. (2025) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3641555.3705150 · Cited by 2
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Solyst, J., Pan, M. Y., Andam, A., Poblete, I. P., Eslami, M., Hammer, J., Ogan, A., & Stewart, A. (2025) · Proceedings. · doi:10.22318/icls2025.547433 · Cited by 2
Gong, L., Chen, J., & Ye, M. (2025) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--56237 · Cited by 2
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Barber, G. L., Grehan, L., Dunne, J., Davis, B., & Qadeer, H. (2024) · Conference on Human Centred Artificial Intelligence - Education and Practice (HCAIep) · doi:10.1145/3701268.3701275 · Cited by 4
Julie, F. Z. (2025) · Lecture Notes in Education Psychology and Public Media · doi:10.54254/2753-7048/2025.21811 · Cited by 1
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Martins, R. M., von Wangenheim, C. G., Rauber, M. F., Hauck, J. C. R., & Borgatto, A. F. (2025) · Revista Brasileira de Informática na Educação · doi:10.5753/rbie.2025.5751 · Cited by 1
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Mupaikwa, E. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2297-1.ch008 · Cited by 3
Cai, X. (2026) · Language Teaching Research · doi:10.1177/13621688251398618 · Cited by 3
Wang, H., Lai, X., Huang, S., Dai, X., Zhao, X., & Wang, Y. (2026) · Behavioral Sciences · doi:10.3390/bs16010072 · Cited by 1
Bautista, Y. J. P. (2026) · Signals and communication technology · doi:10.1007/978-3-032-03554-7_9 · Cited by 1
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Liu, J., Zhuang, Y., Yang, H., Li, S., & Qu, C. (2026) · Behavioral Sciences · doi:10.3390/bs16030362 · Cited by 1
Landesman, R., Schwartz, L., & Davis, K. (2026) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2026.100815 · Cited by 4
Darabipourshiraz, H., Rollins, S. K., Trajkova, M., Zhang, C., Belghith, Y., McKlin, T., Roberts, J., Magerko, B. S., & Long, D. (2026) · International Conference on Tangible, Embedded, and Embodied Interaction (TEI) · doi:10.1145/3731459.3773305 · Cited by 1
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Shen, W., Chiu, T. K. F., Chai, C. S., Yau, K. W., Meng, H. M. L., King, I., Wong, S., & Yam, Y. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101041 · Cited by 2
Sanusi, S., Rusnawati, R., Pelas, M. U., Halik, H., & Maksum, H. (2026) · Qualitative Research Journal · doi:10.1108/qrj-09-2024-0219 · Cited by 4
Helali, M. M., Mostafa, M. M., Aldawsari, H. K., Ibrahim, A. N., Bukhamseen, A. M., & Nemt-allah, M. A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1810679 · Cited by 1
Darabipourshiraz, H., Smyslova, D., Xu, D., Jiang, S., & Long, D. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791555 · Cited by 1
Petchprayoon, C., Maneengam, R., Maneengam, A., & Chantarakamol, P. (2026) · Human Behavior, Development and Society · doi:10.62370/hbds.v27i2.283345 · Cited by 1
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Nguyen, T. H., Truong, L. T., & Nguyen, N. H. T. (2026) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2026.100618 · Cited by 4
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Jetzinger, F., & Michaeli, T. (2026) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3765964.3811641 · Cited by 1
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Orhani, S. (2023) · International Journal on Social Science Economics and Art · doi:10.35335/ijosea.v13i1.254 · Cited by 1
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Andreas, D., & Manete, S. E. (2024) · Voice · doi:10.54636/2nj35e84 · Cited by 1
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Lv, J. (2024) · Journal of Electrical Systems · doi:10.52783/jes.1706
Kobara, T., Saito, D., Washizaki, H., & Fukazawa, Y. (2024) · IEEE World Engineering Education Conference (EDUNINE) · doi:10.1109/edunine60625.2024.10500453
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He, L. N., & Hamid, H. B. (2024) · International Journal of Religion · doi:10.61707/17kvqf03
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Hau, D., Reuter, R. A. P., Mariño, O., & Houssemand, C. (2024) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt61570.2024.00091
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Lei, Y. (2024) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2024-3243
Martínez-Rolán, X. (2024) · European Public & Social Innovation Review · doi:10.31637/epsir-2025-344
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Hughes, C., Niu, Y., & Greer, T. W. (2025) · Springer eBooks · doi:10.1007/978-3-031-75899-7_7
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Curtis, S., Iyer, R., Kirk‐Giannini, C. D., Krakovna, V., Krueger, D., Lambert, N., Marnette, B., McKenzie, C., Michael, J., Miyazono, E., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5097286
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Lim, H., Boulden, D. C., Vandenberg, J. L., Cateté, V., Min, W., & Mott, B. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v39i28.35188
Mosae, T., & Kaushal, R. (2024) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v5.i7.2024.4877 · Cited by 1
Joshi, M., & Bhindi, J. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-86305-9_30
Scrutinizing the role of advanced robotics in educational processes: A qualitative study
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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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