Given the ubiquity of artificial intelligence (AI), it is essential to empower students to become creators, designers, and producers of AI technologies, rather than limiting them to the role of informed consumers. To achieve this, learners need to be equipped with AI knowledge and concepts and develop AI literacy. Paradoxically, it is largely unclear what AI literacy is and how we should learn and teach it. We address both of these questions through a systematic review of systematic reviews, also known as an umbrella review, to gain a comprehensive understanding of AI literacy. After searching the literature, we critically examine the results of 17 reviews focusing on AI literacy and the teaching and learning of AI concepts. Our analysis revealed several encouraging developments: a general consensus on the definition of AI literacy, the availability of teaching tools and materials that support AI learning without prior programming experience, and effective pedagogical approaches that have shown positive effects on students' understanding and engagement. In addition, we identified several areas needing attention in the field: an interdisciplinary pedagogical approach, integration of ethical considerations in AI education, discussions on AI policy, and standardized, content-validated, reliable assessments across educational levels and cultures.
AhmadZ.KaiserW.RahimS. (2023). Hallucinations in ChatGPT: An unreliable tool for learning. Rupkatha Journal on Interdisciplinary Studies in Humanities, 15(4), 12. https://doi.org/10.21659/rupkatha.v15n4.17
2.
AlmatrafiO.JohriA.LeeH. (2024). A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023). Computers and Education Open, 6(1), Article 100173. https://doi.org/10.1016/j.caeo.2024.100173
3.
AnderljungM.HazellJ. (2023). Protecting society from AI misuse: When are restrictions on capabilities warranted?(No. arXiv:2303.09377). arXiv. https://arxiv.org/abs/2303.09377
4.
AromatarisE.FernandezR.GodfreyC. M.HollyC.KhalilH.TungpunkomP. (2015). Summarizing systematic reviews: Methodological development, conduct and reporting of an umbrella review approach. International Journal of Evidence-Based Healthcare, 13(3), 132–140. https://doi.org/10.1097/XEB.0000000000000055
5.
Author et al. (2024). Anonymized for blind review.
6.
Author et al. (under review). Anonymized for blind review.
7.
AyanwaleM. A.SanusiI. T.AdelanaO. P.ArulebaK. D.OyelereS. S. (2022). Teachers’ readiness and intention to teach artificial intelligence in schools. Computers and Education: Artificial Intelligence, 3(1), Article 100099. https://doi.org/10.1016/j.caeai.2022.100099
8.
BastaniH.BastaniO.SunguA.GeH.KabakcıÖ.MarimanR. (2024). Generative AI can harm learning(SSRN Scholarly Paper No. 4895486). Social Science Research Network. https://doi.org/10.2139/ssrn.4895486
9.
BellasF.Guerreiro-SantallaS.NayaM.DuroR. J. (2023). AI curriculum for European high schools: An embedded intelligence approach. International Journal of Artificial Intelligence in Education, 33(2), 399–426. https://doi.org/10.1007/s40593-022-00315-0
10.
BewersdorffA.ZhaiX.RobertsJ.NerdelC. (2023). Myths, mis- and preconceptions of artificial intelligence: A review of the literature. Computers and Education: Artificial Intelligence, 4(3), Article 100143. https://doi.org/10.1016/j.caeai.2023.100143
11.
CarolusA.KochM. J.StrakaS.LatoschikM. E.WienrichC. (2023). MAILS - meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change- and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), Article 100014. https://doi.org/10.1016/j.chbah.2023.100014
12.
*Casal-OteroL.CatalaA.Fernández-MoranteC.TaboadaM.CebreiroB.BarroS. (2023). Ai literacy in k-12: A systematic literature review. International Journal of STEM Education, 10(1), 29. https://doi.org/10.1186/s40594-023-00418-7
13.
CaveS.CoughlanK.DihalK. (2019). “scary robots”: Examining public responses to AI. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, Honolulu, HI, USA, 27–28 January, 2019, pp. 331–337. https://doi.org/10.1145/3306618.3314232
14.
ÇelebiC.YilmazF.DemiRU.KarakusF. (2023). Artificial intelligence, AI literacy, digital literacy, AI literacy scale. Ogretim Teknolojisi ve Hayat Boyu Ogrenme Dergisi - Instructional Technology and Lifelong Learning. https://doi.org/10.52911/itall.1401740
15.
CelikI. (2023). Towards intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, Article 107468. https://doi.org/10.1016/j.chb.2022.107468
16.
CetindamarD.KittoK.WuM.ZhangY.AbedinB.KnightS. (2024). Explicating AI literacy of employees at digital workplaces. IEEE Transactions on Engineering Management, 71, 810–823. https://doi.org/10.1109/TEM.2021.3138503
17.
ChanC. K. Y.ZhouW. (2023). An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI. Smart Learning Environments, 10(1), 64. https://doi.org/10.1186/s40561-023-00284-4
18.
ChiuT. K. F. (2021). A holistic approach to the design of artificial intelligence (AI) education for K-12 schools. TechTrends, 65(5), 796–807. https://doi.org/10.1007/s11528-021-00637-1
19.
ChiuT. K. F.AhmadZ.IsmailovM.SanusiI. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6(6), Article 100171. https://doi.org/10.1016/j.caeo.2024.100171
20.
Council Of Chief State School Officers & National Governors' Association. (2009). Common core state standards initiative. https://www.corestandards.org
*FlegerC.-B.AmanuelY.KrugelJ. (2023). Learning tools using block-based programming for AI education. In 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait, 01–04 May 2023, pp. 1–5. https://doi.org/10.1109/EDUCON54358.2023.10125154
23.
*GennariR.MelonioA.PellegrinoM. A.D’AngeloM. (2023). How to playfully teach ai to young learners: A systematic literature review. In Proceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter, Torino Italy, 20–22 September, 2023, pp. 1–9. https://doi.org/10.1145/3605390.3605393
GhimireA.EdwardsJ. (2024). From guidelines to governance: A study of AI policies in education. In OlneyA. M.ChountaI.-A.LiuZ.SantosO. C.BittencourtI. I. (Eds.), Artificial intelligence in education. Posters and late breaking results, workshops and tutorials, industry and innovation tracks, practitioners, doctoral consortium and blue sky (pp. 299–307). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-64312-5_36
26.
GraingerM. J.BolamF. C.StewartG. B.NilsenE. B. (2020). Evidence synthesis for tackling research waste. Nature Ecology & Evolution, 4(4), 495–497. https://doi.org/10.1038/s41559-020-1141-6
27.
HeegD. M.AvraamidouL. (2023). The use of artificial intelligence in school science: A systematic literature review. Educational Media International, 60(2), 125–150. https://doi.org/10.1080/09523987.2023.2264990
28.
HornbergerM.BewersdorffA.NerdelC. (2023). What do university students know about artificial intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5(1), Article 100165. https://doi.org/10.1016/j.caeai.2023.100165
29.
HwangY.LeeJ. H.ShinD. (2023). What is prompt literacy? An exploratory study of language learners’ development of new literacy skill using generative AI(No. arXiv:2311.05373). arXiv. https://doi.org/10.48550/arXiv.2311.05373
30.
JiaF.SunD.LooiC. (2024). Artificial intelligence in science education (2013–2023): Research trends in ten years. Journal of Science Education and Technology, 33(1), 94–117. https://doi.org/10.1007/s10956-023-10077-6
31.
KandlhoferM.SteinbauerG.Hirschmugl-GaischS.HuberP. (2016). Artificial intelligence and computer science in education: From kindergarten to university. In 2016 IEEE Frontiers in Education Conference (FIE), Erie, PA, USA, 12–15 October 2016, pp. 1–9. https://doi.org/10.1109/FIE.2016.7757570
32.
KaracaO.ÇalışkanS. A.DemirK. (2021). Medical artificial intelligence readiness scale for medical students (MAIRS-MS) – development, validity and reliability study. BMC Medical Education, 21(1), 112. https://doi.org/10.1186/s12909-021-02546-6
33.
KimK.KwonK.Ottenbreit-LeftwichA.BaeH.GlazewskiK. (2023). Exploring middle school students’ common naive conceptions of artificial intelligence concepts, and the evolution of these ideas. Education and Information Technologies, 28(8), 9827–9854. https://doi.org/10.1007/s10639-023-11600-3
34.
KimS.JangY.KimW.ChoiS.JungH.KimS.KimH. (2021). Why and what to teach: AI curriculum for elementary school. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15569–15576. https://doi.org/10.1609/aaai.v35i17.17833
35.
KimS. W.LeeY. (2022). The artificial intelligence literacy scale for middle school students. Journal of the Korea Society of Computer and Information, 27(3), 225–238. https://doi.org/10.9708/jksci.2022.27.03.225
36.
*KimiafarK.SarbazM.TabatabaeiS. M.GhaddaripouriK.MousaviA. S.Raei MehnehM.Mousavi BaigiS. F. (2023). Artificial intelligence literacy among healthcare professionals and students: A systematic review. Frontiers in Health Informatics, 12, 168. https://doi.org/10.30699/fhi.v12i0.524
KongS.-C.CheungM. Y. W.TsangO. (2024). Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach. Computers and Education: Artificial Intelligence, 6(5), Article 100214. https://doi.org/10.1016/j.caeai.2024.100214
39.
KongS. C.CheungM. Y. W.ZhangG. (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers and Education: Artificial Intelligence, 2(4), Article 100026. https://doi.org/10.1016/j.caeai.2021.100026
40.
LaupichlerM. C.AsterA.MeyerheimM.RaupachT.MergenM. (2024). Medical students’ AI literacy and attitudes towards AI: A cross-sectional two-center study using pre-validated assessment instruments. BMC Medical Education, 24(1), 401. https://doi.org/10.1186/s12909-024-05400-7
41.
LaupichlerM. C.AsterA.PerschewskiJ.-O.SchleissJ. (2023). Evaluating AI courses: A valid and reliable instrument for assessing artificial-intelligence learning through comparative self-assessment. Education Sciences, 13(10), 978. https://doi.org/10.3390/educsci13100978
42.
LaupichlerM. C.AsterA.RaupachT. (2023). Delphi study for the development and preliminary validation of an item set for the assessment of non-experts’ AI literacy. Computers and Education: Artificial Intelligence, 4(8), Article 100126. https://doi.org/10.1016/j.caeai.2023.100126
43.
*LaupichlerM. C.AsterA.SchirchJ.RaupachT. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3(4), Article 100101. https://doi.org/10.1016/j.caeai.2022.100101
44.
LawrenceL.EcheverriaV.YangK.AlevenV.RummelN. (2024). How teachers conceptualise shared control with an AI co-orchestration tool: A multiyear teacher-centred design process. British Journal of Educational Technology, 55(3), 823–844. https://doi.org/10.1111/bjet.13372
45.
LeeJ.JeongH. (2023). Keyword analysis of artificial intelligence education policy in South Korea. IEEE Access, 11, 102408–102417. https://doi.org/10.1109/ACCESS.2023.3317261
*LeeJ.WuA. S.LiD.KulasegaramK. M. (2021). Artificial intelligence in undergraduate medical education: A scoping review. Academic Medicine: Journal of the Association of American Medical Colleges, 96(11S), S62–S70. https://doi.org/10.1097/ACM.0000000000004291
48.
LehmannM.CorneliusP. B.StingF. J. (2024). AI meets the classroom: When does ChatGPT harm learning?No. arXiv:2409.09047; Version 1. arXiv. https://arxiv.org/abs/2409.09047
49.
LinP.Van BrummelenJ. (2021). Engaging teachers to co-design integrated AI curriculum for K-12 classrooms. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8–13 May, 2021, pp. 1–12. https://doi.org/10.1145/3411764.3445377
LongD.MagerkoB. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, April, 23, 2020, pp. 1–16. https://doi.org/10.1145/3313831.3376727
52.
MertalaP.FagerlundJ. (2024). Finnish 5th and 6th graders’ misconceptions about artificial intelligence. International Journal of Child-Computer Interaction, 39, Article 100630. https://doi.org/10.1016/j.ijcci.2023.100630
53.
Moodi GhalibafA.MoghadasinM.EmadzadehA.MastourH. (2023). Psychometric properties of the persian version of the medical artificial intelligence readiness scale for medical students (MAIRS-MS). BMC Medical Education, 23(1), 577. https://doi.org/10.1186/s12909-023-04553-1
54.
Morales-GarcíaW. C.Sairitupa-SanchezL. Z.Morales-GarcíaS. B.Morales-GarcíaM. (2024). Adaptation and psychometric properties of a brief version of the general self-efficacy scale for use with artificial intelligence (GSE-6AI) among university students. Frontiers in Education, 9, 1293437. https://doi.org/10.3389/feduc.2024.1293437
55.
NgD. T. K.LeungJ. K. L.ChuK. W. S.QiaoM. S. (2021a). Ai literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509. https://doi.org/10.1002/pra2.487
56.
NgD. T. K.LeungJ. K. L.ChuS. K. W.QiaoM. S. (2021b). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2(2008), Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
57.
*NgD. T. K.LeeM.TanR. J. Y.HuX.DownieJ. S.ChuS. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445–8501. https://doi.org/10.1007/s10639-022-11491-w
*OyelereS. S.SanusiI. T.AgboF. J.OyelereA. S.OmidioraJ. O.AdewumiA. E.OgbeborC. (2022). Artificial intelligence in african schools: Towards a contextualized approach. In 2022 IEEE Global Engineering Education Conference (EDUCON), Tunis, Tunisia, 28–31 March 2022, pp. 1577–1582. https://doi.org/10.1109/EDUCON52537.2022.9766550
60.
PageM. J.McKenzieJ. E.BossuytP. M.BoutronI.HoffmannT. C.MulrowC. D.ShamseerL.TetzlaffJ. M.AklE. A.BrennanS. E.ChouR.GlanvilleJ.GrimshawJ. M.HróbjartssonA.LaluM. M.LiT.LoderE. W.Mayo-WilsonE.McDonaldS.MoherD. (2021). The prisma 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
61.
ParkH.KimH. S.ParkH. W. (2021). A scientometric study of digital literacy, ICT literacy, information literacy, and media literacy. Journal of Data and Information Science, 6(2), 116–138. https://doi.org/10.2478/jdis-2021-0001
62.
PinskiM.BenlianA. (2023). AI literacy—towards measuring human competency in artificial intelligence. In Hawaii International Conference on System Sciences 2023 (HICSS-56), Online, 7-1-2023, 3. https://aisel.aisnet.org/hicss-56/cl/ai_and_future_work/3
63.
PinskiM.BenlianA. (2024). AI literacy for users – a comprehensive review and future research directions of learning methods, components, and effects. Computers in Human Behavior: Artificial Humans, 2(1), Article 100062. https://doi.org/10.1016/j.chbah.2024.100062
64.
PolakS.SchiavoG.ZancanaroM. (2022). Teachers’ perspective on artificial intelligence education: An initial investigation. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April–5 May 2022, pp. 1–7. https://doi.org/10.1145/3491101.3519866
*PupicN.Ghaffari-zadehA.HuR.SinglaR.DarrasK.KarwowskaA.ForsterB. B. (2023). An evidence-based approach to artificial intelligence education for medical students: A systematic review. PLOS Digital Health, 2(11), Article e0000255. https://doi.org/10.1371/journal.pdig.0000255
67.
*RizviS.WaiteJ.SentanceS. (2023). Artificial intelligence teaching and learning in k-12 from 2019 to 2022: A systematic literature review. Computers and Education: Artificial Intelligence, 4, Article 100145. https://doi.org/10.1016/j.caeai.2023.100145
68.
RobinsonK. A.BrunnhuberK.CiliskaD.JuhlC. B.ChristensenR.LundH.Evidence-Based Research Network. (2021). Evidence-based research series-paper 1: What evidence-based research is and why is it important?Journal of Clinical Epidemiology, 129(3), 151–157. https://doi.org/10.1016/j.jclinepi.2020.07.020
69.
SalaminA. D.RussoD.RuegerD. (2023). ChatGPT, an excellent liar: How conversational agent hallucinations impact learning and teaching. In Proceedings of the 7th International Conference on Teaching, Learning and Education, Copenhagen, Denmark, 2023-11.
70.
*SanusiI. T.OyelereS. S.AgboF. J.SuhonenJ. (2021). Survey of resources for introducing machine learning in k-12 context. In 2021 IEEE Frontiers in Education Conference (FIE), Lincoln, NE, USA, 13–16 October 2021, pp. 1–9. https://doi.org/10.1109/FIE49875.2021.9637393
71.
*SanusiI. T.OyelereS. S.VartiainenH.SuhonenJ.TukiainenM. (2023). A systematic review of teaching and learning machine learning in k-12 education. Education and Information Technologies, 28(5), 5967–5997. https://doi.org/10.1007/s10639-022-11416-7
72.
SchiffD. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2
73.
SongJ.ZhangL.YuJ.PengY.MaA.LuY. (2022). Paving the way for novices: How to teach AI for K-12 education in China. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12852–12857. https://doi.org/10.1609/aaai.v36i11.21565
74.
SongY.TianX.RegattiN.KatukaG. A.BoyerK. E.IsraelM. (2024). Artificial intelligence unplugged: Designing unplugged activities for a conversational AI summer camp. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V, 1, 1272–1278. https://doi.org/10.1145/3626252.3630783
75.
Soto-SanfielM. T.Angulo-BrunetA.LutzC. (2024). The scale of artificial intelligence literacy for all (SAIL4ALL): A tool for assessing knowledge on artificial intelligence in all adult populations and settings. https://doi.org/10.31235/osf.io/bvyku
76.
SparksJ. R.OberT. M.TenisonC.ArslanB. (2024). Opportunities and challenges for assessing digital and AI literacies.
77.
SteinbauerG.KandlhoferM.ChklovskiT.HeintzF.KoenigS. (2021). A differentiated discussion about AI education K-12. KI - Künstliche Intelligenz, 35(2), 131–137. https://doi.org/10.1007/s13218-021-00724-8
78.
SuJ.ZhongY. (2022). Artificial intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3(1), Article 100072. https://doi.org/10.1016/j.caeai.2022.100072
79.
*SuJ.GuoK.ChenX.ChuS. K. W. (2023). Teaching artificial intelligence in k–12 classrooms: A scoping review. Interactive Learning Environments, 32(9), 5207–5226. https://doi.org/10.1080/10494820.2023.2212706
80.
*SuJ.NgD. T. K.ChuS. K. W. (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Computers and Education: Artificial Intelligence, 4(1), Article 100124. https://doi.org/10.1016/j.caeai.2023.100124
81.
SuttonA.ClowesM.PrestonL.BoothA. (2019). Meeting the review family: Exploring review types and associated information retrieval requirements. Health Information and Libraries Journal, 36(3), 202–222. https://doi.org/10.1111/hir.12276
82.
*SuJ.ZhongY.NgD. T. K. (2022). A meta-review of literature on educational approaches for teaching ai at the k-12 levels in the asia-pacific region. Computers and Education: Artificial Intelligence, 3(1), Article 100065. https://doi.org/10.1016/j.caeai.2022.100065
83.
TatarC.JiangS.RoséC. P.ChaoJ. (2024). Exploring teachers’ views and confidence in the integration of an artificial intelligence curriculum into their classrooms: A case study of curricular co-design program. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00404-2
84.
TedreM.ToivonenT.KahilaJ.VartiainenH.ValtonenT.JormanainenI.PearsA. (2021). Teaching machine learning in K–12 classroom: Pedagogical and technological trajectories for artificial intelligence education. IEEE Access, 9, 110558–110572. https://doi.org/10.1109/ACCESS.2021.3097962
85.
TorreyL. (2021). Teaching problem-solving in algorithms and AI. Proceedings of the AAAI Conference on Artificial Intelligence, 26(3), 2363–2367. https://doi.org/10.1609/aaai.v26i3.18952
86.
TouretzkyD.Gardner-McCuneC.MartinF.SeehornD. (2019). Envisioning AI for K-12: What should every child know about AI?Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9795–9799. https://doi.org/10.1609/aaai.v33i01.33019795
VeluruC. (2024). Responsible artificial intelligence on large scale data to prevent misuse, unethical challenges and security breaches. Journal of Artificial Intelligence & Cloud Computing, 1–6. https://doi.org/10.47363/JAICC/2024(3)331
90.
VoulgariI.ZammitM.StouraitisE.LiapisA.YannakakisG. (2021). Learn to machine learn: Designing a game based approach for teaching machine learning to primary and secondary education students. In Interaction Design and Children, Athens, Greece, 24 June 2021, pp. 593–598. https://doi.org/10.1145/3459990.3465176
91.
WangB.RauP.-L. P.YuanT. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929x.2022.2072768
92.
WangN.LesterJ. (2023). K-12 education in the age of AI: A call to action for K-12 AI literacy. International Journal of Artificial Intelligence in Education, 33(2), 228–232. https://doi.org/10.1007/s40593-023-00358-x
93.
WangX.LiX.HuangJ. (2023). Junior high school artificial intelligence literacy: Connotation, evaluation and promotion strategy. Open Journal of Social Sciences, 11(05), 33–49. https://doi.org/10.4236/jss.2023.115004
94.
WangY.-Y.ChuangY.-W. (2024). Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, 29(4), 4785–4808. https://doi.org/10.1007/s10639-023-12015-w
95.
WienrichC.CarolusA. (2021). Development of an instrument to measure conceptualizations and competencies about conversational agents on the example of smart speakers. Frontiers of Computer Science, 3, 685277. https://doi.org/10.3389/fcomp.2021.685277
96.
WilliamsR. (2023). A review of assessments in K-12 AI literacy curricula.
97.
WuC.LiY.LiJ.ZhangQ.WuF. (2021). Web-based platform for K-12 AI education in China. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15687–15694. https://doi.org/10.1609/aaai.v35i17.17848
98.
XiongY.LingQ.LiuJ. (2023). Educational missions and tactics in the EU artificial intelligence strategy in the era of digital transformation: A policy analysis based on EU documents published during 2018–2022. In ChenC.-H.ScapellatoA.BarbieroA.KorzunD. G. (Eds.), Advances in transdisciplinary engineering. IOS Press. https://doi.org/10.3233/ATDE230999
99.
YauK. W.ChaiC. S.ChiuT. K. F.MengH.KingI.WongS. W.-H.YamY. (2022). Co-Designing artificial intelligence curriculum for secondary schools: A grounded theory of teachers’ experience. In 2022 International Symposium on Educational Technology (ISET), Hong Kong, 19–22 July 2022, pp. 58–62. https://doi.org/10.1109/ISET55194.2022.00020
100.
YilmazF. G. K.YilmazR. (2023). Yapay Zekâ Okuryazarlığı Ölçeğinin Türkçeye Uyarlanması. Bilgi ve İletişim Teknolojileri Dergisi, 5(2), Article 2.
101.
*YimI. H. Y.SuJ. (2024). Artificial intelligence (ai) learning tools in k-12 education: A scoping review. Journal of Computers in Education. https://doi.org/10.1007/s40692-023-00304-9
102.
YueM.JongM. S.-Y.NgD. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29(15), 19505–19536. https://doi.org/10.1007/s10639-024-12621-2
103.
*YueM.JongM. S.-Y.DaiY. (2022). Pedagogical design of k-12 artificial intelligence education: A systematic review. Sustainability, 14(23), Article 15620. https://doi.org/10.3390/su142315620
104.
ZhaiC.WibowoS.LiL. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7
105.
ZhangH.PerryA.LeeI. (2024). Developing and validating the artificial intelligence literacy concept inventory: An instrument to assess artificial intelligence literacy among middle school students. International Journal of Artificial Intelligence in Education, 35(1), 398–438. https://doi.org/10.1007/s40593-024-00398-x
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