pith. sign in

arxiv: 2604.19099 · v1 · submitted 2026-04-21 · 💻 cs.HC · cs.AI

Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews

Roberto Martinez-Maldonado , Vanessa Echeverria , Jenna Hawes , YJ Kim , Zara Maddigan , Mikaela Milesi , Todd Nelson , Yi-Shan Tsai This is my paper

Pith reviewed 2026-05-10 02:33 UTC · model grok-4.3

classification 💻 cs.HC cs.AI
keywords AI in educationrelational designreciprocityIndigenous worldviewsparticipatory designgenerative AIrelational accountabilityeducational technology
0
0 comments X

The pith

Meaningful AI in education should support learning with others through reciprocal relationships rather than replacing human interactions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Education is a social, constructive, and relational practice rather than mere information transmission or individual optimization. Generative AI often prioritizes efficiency and automation, which can erode the social and ecological relationships central to learning. The paper re-frames learner-AI interactions as context-specific relationships with defined purposes and boundaries. It draws on participatory design and Indigenous worldviews emphasizing reciprocity and relational accountability to argue that AI should sustain these connections instead of substituting for them.

Core claim

We advance this perspective by conceptualising AIED as a relational design problem grounded in reciprocity; articulating key tensions introduced by GenAI in education; and outlining design directions that expand the AIED design space toward reciprocity, including when not to use AI, how to define pedagogical boundaries, and how to support responsible uses of AIED innovations that sustain communities and natural environments.

What carries the argument

Relational design problem grounded in reciprocity and relational accountability, which treats AI-learner interactions as bounded, context-specific relationships rather than replacements for human ones.

If this is right

  • AIED systems would incorporate explicit decisions about when not to deploy AI to preserve human relationships.
  • Pedagogical boundaries would be defined to keep AI from substituting for social learning processes.
  • Responsible AI innovations would be evaluated on their ability to sustain communities and natural environments alongside learning gains.
  • Participatory design would become a core requirement for AIED projects to embed relational accountability.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • This approach could shift evaluation metrics in educational technology from individual performance scores toward measures of sustained social and ecological ties.
  • Developers might need new protocols for ongoing community consent and adaptation to prevent relational designs from becoming extractive over time.
  • The framing suggests testing in specific educational contexts where Indigenous knowledge systems are already present to surface practical implementation challenges.

Load-bearing premise

Indigenous worldviews and participatory design practices can be directly translated into AI system requirements without cultural appropriation, loss of context, or unintended negative effects on the communities involved.

What would settle it

Classroom observations or controlled studies comparing collaborative learning behaviors and social engagement in settings using standard generative AI tools versus AI systems explicitly designed with reciprocity boundaries and community input.

Figures

Figures reproduced from arXiv: 2604.19099 by Jenna Hawes, Mikaela Milesi, Roberto Martinez-Maldonado, Todd Nelson, Vanessa Echeverria, Yi-Shan Tsai, YJ Kim, Zara Maddigan.

Figure 1
Figure 1. Figure 1: Conceptual framing of relational AI in education, linking reciprocity, partici￾patory design, and indigenous worldviews to key tensions and design opportunities. 2 Positionality The authors come from diverse cultural and disciplinary backgrounds, includ￾ing Ecuadorian, Mexican (Mesoamerican), Korean, Taiwanese, non-Indigenous Australian, and First Nations Australian perspectives. As researchers and prac￾ti… view at source ↗
read the original abstract

Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and relational practice. However, recent advances in generative artificial intelligence (GenAI) increasingly emphasise efficiency, automation, and individualised assistance, risking the weakening of relational learning processes. Despite growing adoption, AI in education (AIED) research has yet to fully articulate how AI can be designed in ways that sustain the social and ecological relationships through which learning occurs. In this paper, we re-centre education as relational and frame learner-AI interactions as context-specific relationships with clearly defined purposes and boundaries, rather than positioning them as substitutes for, or replacements of, human interaction. Grounded in participatory design practices and inspired by Indigenous worldviews (including Aboriginal Australian, Native American, and Mesoamerican traditions) that foreground reciprocity and relational accountability, we argue that meaningful educational AI should support learning with others rather than replace them. We advance this perspective by: i) conceptualising AIED as a relational design problem grounded in reciprocity; ii) articulating key tensions introduced by GenAI in education; and iii) outlining design directions that expand the AIED design space toward reciprocity, including when not to use AI, how to define pedagogical boundaries, and how to support responsible uses of AIED innovations that sustain communities and natural environments.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The manuscript is a conceptual position paper arguing that AI in education (AIED) should be reframed as a relational design problem rather than an efficiency- or automation-driven one. It claims that education is fundamentally social and relational, that generative AI risks eroding these processes through individualization, and that meaningful AIED should support learning with others. Grounded in participatory design practices and inspired by Indigenous worldviews (Aboriginal Australian, Native American, Mesoamerican) that emphasize reciprocity and relational accountability, the paper advances three contributions: (i) conceptualizing AIED as relational, (ii) articulating GenAI-induced tensions, and (iii) outlining high-level design directions including when not to use AI, defining pedagogical boundaries, and supporting responsible uses that sustain communities and environments.

Significance. If the perspective holds, it provides a timely normative counter-framework to dominant optimization-focused AIED research, potentially guiding designs that preserve social and ecological relationships in learning. The paper explicitly credits participatory design practices and positions Indigenous worldviews as inspirational sources rather than direct translations, which strengthens its scope as a perspective piece and helps expand the AIED design space toward context-specific, bounded interactions.

minor comments (3)
  1. The three contributions listed in the abstract (i–iii) are clear at a high level but would benefit from explicit section headings or a roadmap paragraph early in the manuscript to help readers navigate the argument structure.
  2. The design directions in contribution (iii) are described conceptually; adding one or two brief illustrative scenarios (even hypothetical ones drawn from participatory design literature) would improve concreteness without altering the perspective nature of the paper.
  3. Ensure the bibliography includes specific citations for the participatory design practices and the cited Indigenous traditions referenced in the abstract and introduction to support the grounding claims.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their accurate and encouraging summary of our manuscript and for recommending minor revision. The assessment correctly captures the paper's framing of AIED as a relational design problem, the tensions arising from GenAI, and the grounding in participatory design and Indigenous worldviews as inspirational sources rather than direct translations.

Circularity Check

0 steps flagged

No significant circularity

full rationale

The paper is a conceptual position piece that advances a normative perspective on relational AI in education. It draws inspiration from external sources (participatory design practices and Indigenous worldviews) without any mathematical derivations, equations, fitted parameters, predictions, or self-referential reductions. No load-bearing steps reduce by construction to author-defined inputs or prior self-citations. The argument is self-contained as high-level framing and design directions.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central argument rests on domain assumptions about the nature of education and the applicability of Indigenous perspectives to technology design, with no free parameters or invented technical entities.

axioms (2)
  • domain assumption Education is fundamentally a social, constructive, and relational practice rather than mere information transmission or individual optimization.
    Explicitly stated as the opening premise in the abstract.
  • domain assumption Indigenous worldviews from Aboriginal Australian, Native American, and Mesoamerican traditions foreground reciprocity and relational accountability.
    Invoked as the inspirational foundation for the proposed AIED design approach.

pith-pipeline@v0.9.0 · 5565 in / 1296 out tokens · 40146 ms · 2026-05-10T02:33:49.910779+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

53 extracted references · 53 canonical work pages

  1. [1]

    Teaching for High Potential pp

    Alley, T.F.: Struggle matters. Teaching for High Potential pp. 11–11 (2025) Relational AI in Education 13

    work page 2025

  2. [2]

    International Studies in Sociology of Education32(4), 1152–1175 (2023)

    Anderson, P.J., Yip, S.Y., Diamond, Z.M.: Getting schools ready for indigenous academic achievement: a meta-synthesis of the issues and challenges in australian schools. International Studies in Sociology of Education32(4), 1152–1175 (2023). https://doi.org/10.1080/09620214.2021.2025142

    work page doi:10.1080/09620214.2021.2025142 2023

  3. [3]

    Journal of Global Indigeneity9(1) (2025).https://doi.org/10.54760/001c.133656

    Barrowcliffe, R., Hutchinson, B., Abdilla, A., Acres, L., ohers: Envisioning abo- riginal and torres strait islander ai futures communique: March 2025. Journal of Global Indigeneity9(1) (2025).https://doi.org/10.54760/001c.133656

    work page doi:10.54760/001c.133656 2025

  4. [4]

    In- ternational Journal of Artificial Intelligence in Education32(3), 756–782 (2022)

    Bhimdiwala, A., Neri, R.C., Gomez, L.M.: Advancing the design and implemen- tation of artificial intelligence in education through continuous improvement. In- ternational Journal of Artificial Intelligence in Education32(3), 756–782 (2022). https://doi.org/10.1007/s40593-021-00278-8

    work page doi:10.1007/s40593-021-00278-8 2022

  5. [5]

    Biesta,G.J.:Beyondlearning:Democraticeducationforahumanfuture.Routledge (2015)

    work page 2015

  6. [6]

    Stanford Social Innovation Review15(1), 28–33 (2017)

    Blackwell, A.G.: The curb-cut effect. Stanford Social Innovation Review15(1), 28–33 (2017)

    work page 2017

  7. [7]

    Education and In- formation Technologies30(16), 23693–23728 (2025).https://doi.org/10.1007/ s10639-025-13686-3

    Chugh, R., Turnbull, D., Kutty, S., Sabrina, F., Rashid, M.M., Morshed, A., Azad, S., Kaisar, S., Subramani, S.: Generative ai as a learning assistant in ict education: student perspectives and educational implications. Education and In- formation Technologies30(16), 23693–23728 (2025).https://doi.org/10.1007/ s10639-025-13686-3

    work page 2025

  8. [8]

    Yale University Press, New Haven, CT (2021)

    Crawford, K.: Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, New Haven, CT (2021)

    work page 2021

  9. [9]

    Joule7(10), 2191–2194 (2023).https://doi.org/https://doi.org/10.1016/j.joule.2023

    de Vries, A.: The growing energy footprint of artificial intelligence. Joule7(10), 2191–2194 (2023).https://doi.org/https://doi.org/10.1016/j.joule.2023. 09.004

    work page doi:10.1016/j.joule.2023 2023

  10. [10]

    AFOSR-3233, Stanford Research Institute, CA (1962)

    Engelbart,D.C.:Augmentinghuman intellect:Aconceptual framework.Tech.Rep. AFOSR-3233, Stanford Research Institute, CA (1962)

    work page 1962

  11. [11]

    Orienta-Konsultit, Helsinki (1987)

    Engeström, Y.: Learning by Expanding: An Activity-Theoretical Approach to De- velopmental Research. Orienta-Konsultit, Helsinki (1987)

    work page 1987

  12. [12]

    British Journal of Educational Technology56(2), 489–530 (2025).https://doi.org/https://doi.org/10.1111/ bjet.13544

    Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., Gašević, D.: Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology56(2), 489–530 (2025).https://doi.org/https://doi.org/10.1111/ bjet.13544

    work page 2025

  13. [13]

    American Psychologist34(10), 906–911 (1979)

    Flavell, J.H.: Metacognition and cognitive monitoring: A new area of cognitive– developmental inquiry. American Psychologist34(10), 906–911 (1979)

    work page 1979

  14. [14]

    Continuum, New York (1970)

    Freire, P.: Pedagogy of the Oppressed. Continuum, New York (1970)

    work page 1970

  15. [15]

    Frontiers in Sociology10(2025).https://doi.org/10.3389/fsoc.2025

    Fricker, A.: Yarning as decolonial praxis in initial teacher training: an australian context. Frontiers in Sociology10(2025).https://doi.org/10.3389/fsoc.2025. 1561532

    work page doi:10.3389/fsoc.2025 2025

  16. [16]

    Parrhesia: A Journal of Critical Philosophy (37) (2023)

    Graham, M.: The law of obligation, aboriginal ethics: Australia becoming, australia dreaming. Parrhesia: A Journal of Critical Philosophy (37) (2023)

    work page 2023

  17. [17]

    2021, International Journal of Artificial Intelligence in Education, 32, doi: 10.1007/s40593-021-00239-1

    Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Buck- ingham Shum, S., Santos, O.C., Rodrigo, M.T., Cukurova, M., Bittencourt, I.I., Koedinger, K.R.: Ethics of ai in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education32(3), 504–526 (2022). https://doi.org/10.1007/s40593-021-00239-1

    work page doi:10.1007/s40593-021-00239-1 2022

  18. [18]

    Patterns3(3) (2022)

    Hsu, Y.C., Huang, T., Verma, H., Mauri, A., Nourbakhsh, I., Bozzon, A.: Em- powering local communities using artificial intelligence. Patterns3(3) (2022). https://doi.org/10.1016/j.patter.2022.100449 14 Martinez-Maldonado et al

    work page doi:10.1016/j.patter.2022.100449 2022

  19. [19]

    Information Technology for Development30(4), 626–643 (2024)

    Iazzolino, G., Stremlau, N.: Ai for social good and the corporate capture of global development. Information Technology for Development30(4), 626–643 (2024). https://doi.org/10.1080/02681102.2023.2299351

    work page doi:10.1080/02681102.2023.2299351 2024

  20. [20]

    arXiv preprint arXiv:2511.01205 (2025)

    Jin, Y., Martinez-Maldonado, R., Shi, W., Huang, S., Zheng, M., Han, X., Gasevic, D., Yan, L.: When machines join the moral circle: The persona effect of generative ai agents in collaborative reasoning. arXiv preprint arXiv:2511.01205 (2025)

    work page arXiv 2025

  21. [21]

    https://doi.org/10.25916/sut.28955288.v1

    Jones, N.: The Kara: A Framework for Indigenous Design Thinking (5 2025). https://doi.org/10.25916/sut.28955288.v1

    work page doi:10.25916/sut.28955288.v1 2025

  22. [22]

    Milkweed Editions, Minneapolis, MN (2015)

    Kimmerer, R.W.: Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge, and the Teachings of Plants. Milkweed Editions, Minneapolis, MN (2015)

    work page 2015

  23. [23]

    In: du Boulay, B., Mitrovic, A., Yacef, K

    Lajoie, S.P., Li, S.: Theory-driven design of aied systems for enhanced interaction and problem-solving. In: du Boulay, B., Mitrovic, A., Yacef, K. (eds.) Handbook of Artificial Intelligence in Education, pp. 229–249. Edward Elgar Publishing (2023). https://doi.org/10.4337/9781800375413.00020

    work page doi:10.4337/9781800375413.00020 2023

  24. [24]

    Here the GPT made a choice, and every choice can be biased

    Lee, H.P.H., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., Wilson, N.: The impact of generative ai on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. CHI ’25, ACM, New York, NY, USA...

    work page doi:10.1145/3706598 2025

  25. [25]

    León-Portilla, M., et al.: Cuícatl y tlahtolli: las formas de expresión en náhuatl (1983)

    work page 1983

  26. [26]

    Lewis, J.E., Hagerty, J., Whittaker, M., Maiden, N., Kempt, Z.: Indigenous proto- col and artificial intelligence: Position paper. Tech. rep., Indigenous Protocol and AI Working Group, Canada (2020)

    work page 2020

  27. [27]

    In: du Boulay, B., Mitrovic, A., Yacef, K

    Martinez-Maldonado, R., van Leeuwen, A., Swiecki, Z.: Artificial intelligence tech- niques for supporting face-to-face and online collaborative learning. In: du Boulay, B., Mitrovic, A., Yacef, K. (eds.) Handbook of Artificial Intelligence in Educa- tion, pp. 422–439. Edward Elgar Publishing (2023).https://doi.org/10.4337/ 9781800375413.00031

    work page arXiv 2023

  28. [28]

    The Design Journal25(3), 437–458 (2022).https: //doi.org/10.1080/14606925.2022.2058680

    Munroe, H., Ibinarriaga, D.H.: Indigenising design: The seven grandfathers’ teach- ings as a design methodology. The Design Journal25(3), 437–458 (2022).https: //doi.org/10.1080/14606925.2022.2058680

    work page doi:10.1080/14606925.2022.2058680 2022

  29. [29]

    Murawin Professional Services: State of the environment indigenous theme semi- nar and interview outcomes: 2. Tech. rep., Australian Government Department of Agriculture, Water and the Environment, Canberra (2021)

    work page 2021

  30. [30]

    National Academies Press, Washington, DC (2000).https://doi.org/10.17226/9853

    National Research Council: Learners and Learning. National Academies Press, Washington, DC (2000).https://doi.org/10.17226/9853

    work page doi:10.17226/9853 2000

  31. [31]

    (11 2023), linkedIn post

    Nelson, T.: Across sectors we’re witnessing a profound shift ... (11 2023), linkedIn post. Available at: LinkedIn post

    work page 2023

  32. [32]

    Big Data & Society12(2) (2025).https://doi.org/10

    Perera, M., Vidanaarachchi, R., Chandrashekeran, S., Kennedy, M., Kennedy, B., Halgamuge, S.: Indigenous peoples and artificial intelligence: A systematic review and future directions. Big Data & Society12(2) (2025).https://doi.org/10. 1177/20539517251349170

    work page 2025

  33. [33]

    In: du Boulay, B., Mitrovic, A., Yacef, K

    Porayska-Pomsta, K., Holmes, W., Nemorin, S.: The ethics of ai in education. In: du Boulay, B., Mitrovic, A., Yacef, K. (eds.) Handbook of Artificial Intelligence in Education, pp. 571–604. Edward Elgar Publishing (2023).https://doi.org/10. 4337/9781800375413.00038

    work page arXiv 2023

  34. [34]

    Monash University Publishing (2024), ebook, 194 pages Relational AI in Education 15

    Russ-Smith, J., Lazarus, M.D.: The AI (R)evolution: Valuing Country, Culture and Community in a World of Algorithms. Monash University Publishing (2024), ebook, 194 pages Relational AI in Education 15

    work page 2024

  35. [35]

    (Nov 2019)

    Selwyn,N.:Shouldrobotsreplaceteachers?:AIandtheFutureofEducation.Polity Press, United Kingdom, 1st edn. (Nov 2019)

    work page 2019

  36. [36]

    Sharma, K., Gupta, P., Shetty, R., Agarwal, P., Bijalwan, A.: Revolutionizing Education with Edge AI, chap. 26, pp. 579–610. John Wiley & Sons, Ltd (2025). https://doi.org/https://doi.org/10.1002/9781394355037.ch26

    work page doi:10.1002/9781394355037.ch26 2025

  37. [37]

    Learning: Research and Practice9(2), 159–167 (2023).https://doi.org/ 10.1080/23735082.2023.2261131

    Sharples, M.: Towards social generative ai for education: theory, practices and ethics. Learning: Research and Practice9(2), 159–167 (2023).https://doi.org/ 10.1080/23735082.2023.2261131

    work page doi:10.1080/23735082.2023.2261131 2023

  38. [38]

    Innovations in Education and Teaching International62(5), 1648–1664 (2025).https://doi.org/10.1080/14703297.2025.2530118

    Sichterman, B., Noroozi, O., Boetje, J., van Ginkel, S., Khosravi, H., Versendaal, J.: Supporting peer learning with artificial intelligence: A systematic literature review. Innovations in Education and Teaching International62(5), 1648–1664 (2025).https://doi.org/10.1080/14703297.2025.2530118

    work page doi:10.1080/14703297.2025.2530118 2025

  39. [39]

    Sinclair, K.: Aboriginal pedagogies: exploring Indigenous ways of knowing, being and doing, p. 12–29. Cambridge University Press (2024)

    work page 2024

  40. [40]

    MIT Press, Cambridge, MA (2006)

    Stahl, G.: Group Cognition: Computer Support for Building Collaborative Knowl- edge. MIT Press, Cambridge, MA (2006)

    work page 2006

  41. [41]

    Curriculum Inquiry47(5), 439–445 (2017).https://doi.org/10.1080/ 03626784.2017.1398391

    Toukan, E.V., Gaztambide-Fernández, R.: Pedagogies of time, place, and identi- fication. Curriculum Inquiry47(5), 439–445 (2017).https://doi.org/10.1080/ 03626784.2017.1398391

    work page arXiv 2017

  42. [42]

    Corporate Governance7(2) (2025)

    Turnbull, S.: Sustaining business, the environment and humanity with bio-regional citizens governed by nature. Corporate Governance7(2) (2025)

    work page 2025

  43. [43]

    UNESCO: Ai competency framework for teachers (2023)

    work page 2023

  44. [44]

    Velander, J., Otero, N., Milrad, M.: What is Critical (about) AI Literacy? Explor- ing Conceptualizations Present in AI Literacy Discourse, pp. 139–160. Springer, Cham (2024).https://doi.org/10.1007/978-3-031-58622-4_8

    work page doi:10.1007/978-3-031-58622-4_8 2024

  45. [45]

    Harvard university press (1978)

    Vygotsky, L.S., Cole, M.: Mind in society: Development of higher psychological processes. Harvard university press (1978)

    work page 1978

  46. [46]

    Consciousness and cognition22(1), 264–271 (2013)

    Weil, L.G., Fleming, S.M., Dumontheil, I., Kilford, E.J., Weil, R.S., Rees, G., Dolan, R.J., Blakemore, S.J.: The development of metacognitive ability in adoles- cence. Consciousness and cognition22(1), 264–271 (2013)

    work page 2013

  47. [47]

    Somatechnics15(3), 296–314 (2025)

    Worrell, T., Carlson, B.: Indigenous ai futures: Uncle chatty gee, aunty lexi, and algorithmic settler colonialism. Somatechnics15(3), 296–314 (2025)

    work page 2025

  48. [48]

    Scientific Rep.15(1) (2025).https://doi.org/10.1038/s41598-025-98385-2

    Wu, S., Liu, Y., Ruan, M., Chen, S., Xie, X.Y.: Human-generative ai collaboration enhances task performance but undermines human’s intrinsic motivation. Scientific Rep.15(1) (2025).https://doi.org/10.1038/s41598-025-98385-2

    work page doi:10.1038/s41598-025-98385-2 2025

  49. [49]

    Global Journal of Flexible Systems Management25(4), 849–879 (2024).https://doi.org/10

    Yadav, V., Yadav, N.: Beyond sustainability, toward resilience, and regeneration: An integrative framework for archetypes of regenerative innovation. Global Journal of Flexible Systems Management25(4), 849–879 (2024).https://doi.org/10. 1007/s40171-024-00418-8

    work page 2024

  50. [50]

    International Journal of Education in Math- ematics, Science and Technology12(2), 470–495 (2024)

    Young, J.R., Bevan, D., Sanders, M.: How productive is the productive struggle? lessons learned from a scoping review. International Journal of Education in Math- ematics, Science and Technology12(2), 470–495 (2024)

    work page 2024

  51. [51]

    In: Mikulan, P., Sinclair, N

    Yunkaporta, T., Davis, J.: Education as embassy: Pluriversal pedagogies and tran- sknowledging. In: Mikulan, P., Sinclair, N. (eds.) Unschooled Futures: Pluriversal Speculations, chap. 9. Bloomsbury Publishing (2026)

    work page 2026

  52. [52]

    Journal of Indigenous Research8(2020), Article 4 (2020).https://doi.org/10.26077/ ky71-qt27

    Yunkaporta, T., Shillingsworth, D.: Relationally responsive standpoint. Journal of Indigenous Research8(2020), Article 4 (2020).https://doi.org/10.26077/ ky71-qt27

    work page 2020

  53. [53]

    Journal of Educational Computing Research63(5), 1292– 1322 (2025).https://doi.org/10.1177/07356331251342081

    Zhang, S., Prasad, P.G., Schroeder, N.L.: Learning about ai: A systematic review of reviews on ai literacy. Journal of Educational Computing Research63(5), 1292– 1322 (2025).https://doi.org/10.1177/07356331251342081

    work page doi:10.1177/07356331251342081 2025