Cited by 263Artificial Intelligence in EducationArt Education and DevelopmentDigital Education and Society

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index; none of the 47 sources its claims cite is checked for support yet.

Using artificial intelligence in craft education: crafting with text-to-image generative models

Open access
Vartiainen, Henriikka, Tedre, Matti·2023·Digital Creativity

Abstract

Artificial intelligence (AI) and the automation of creative work have received little attention in craft education. This study aimed to address this gap by exploring Finnish pre-service craft teachers’ and teacher educators’ (N = 15) insights into the potential benefits and challenges of AI, particularly text-to-image generative AI. This study implemented a hands-on workshop on creative making with text-to-image generative AI in order to stimulate discourses and capture imaginaries concerning generative AI. The results revealed that making with AI inspired teachers to consider the unique nature of crafts as well as the tensions and tradeoffs of adopting generative AI in craft practices. The teachers identified concerns in data-driven design, including algorithmic bias, copyright violations and black-boxing creativity, as well as in power relationships, hybrid influencing and behaviour engineering. The article concludes with a discussion of the complicated relationships the results uncovered between creative making and generative AI.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This exploratory case study examined Finnish pre-service craft teachers’ and teacher educators’ insights into text-to-image generative AI through a hands-on creative-making workshop. Participants saw opportunities for ideation and externalization, but also raised concerns about design constraints, embodiment, bias, copyright, black-boxing creativity, power, and behaviour engineering.

Key findings

  • Participants saw generative AI as potentially useful for ideation and externalization: it could combine ideas, visualize “impossible” ideas, and help children put vague design ideas into words through gradual prompt-crafting.
  • Teachers identified tensions and tradeoffs in craft design, including concerns that AI-generated visualizations may not fit material, resource, skill, or ergonomic constraints; that digital design lacks the embodiment and materiality of craft making; and that assessment becomes unclear when pupils use text-to-image AI.
  • Concerns about data-driven design included algorithmic bias, copyright violations, black-boxing creativity, power relationships, hybrid influencing, and behaviour engineering. Participants also worried that reliance on existing styles could repeat ideas and reinforce biases.
  • The workshop involved N = 15 participants: 5 teacher educators and 10 pre-service teachers. The 3-hour workshop included a 90-minute hands-on exploration in three small groups using Midjourney, followed by group and joint reflections.

Methods

  • Design: exploratory case study using a research-creation approach; participants collaboratively created visual images with text-to-image generative AI and reflected on AI and automation in ideation and product design.
  • Data/sample: empirical data collected during a workshop in a Finnish university craft teacher education programme in fall 2022; N = 15 participants (5 teacher educators, 10 pre-service teachers), limited to 15 due to limited technical resources and filled in order of registration.
  • Analysis: audio from three group discussions and joint reflections was transcribed, pseudonymized, and analyzed using thematic analysis in Atlas.ti; two researchers discussed interpretations, and data examples were provided.

Limitations

  • Stated in the paper: the tensions captured are based on craft teachers’ first encounters with generative AI, so it remains to be seen whether and how these technologies and tensions will be actualized in educational practice.
  • Stated in the paper: the study focused exclusively on text-to-image generative AI and did not explore benefits or shortcomings of other AI developments; findings of this exploratory study cannot be generalized.
  • Evident from the text: the study is a small, single-workshop case with 15 participants, no demographic details collected, and a specific Finnish craft teacher education context, which further limits transferability.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1080/14626268.2023.2174557

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

37 Own result · 36 Not checked yet · 6 Own method · 5 No basis given · 4 Own interpretation

Verify all 47 references — free account

Show all 19 claims

  • Probably not a substantial claim. 63
  • It may state two separate claims as one. 22
69 of 69
  • The paper relies on this without support.

    AI and the automation of creative work have received little attention in craft education.

    “Artificial intelligence (AI) and the automation of creative work have received little attention in craft education.”
  • The paper relies on this without support.

    There is no research on applications of text-to-image generative models in school education or in teacher education.

    “While there is steady growth in the use of 3D modelling and fabrication technologies in school education, there is, to the best of our knowledge, no research on applications of text-to-image generative models in school education or in teacher education.”
  • The paper relies on this without support.

    There is an evident lack of research on teachers’ insights into AI, experiences with it, and attitudes toward it, as well as on how AI can liberate or impede the values and skills emphasized in craft, design and technology education.

    “There is an evident lack of research on teachers’ insights into AI, experiences with it, and attitudes toward it, as well as on how AI can liberate or impede the values and skills emphasized in craft, design and technology education.”
  • The paper relies on this without support.

    Little is known about how text-to-image generative AI will change the dynamics of learning communities and classrooms.

    “However, as the technology involved is very recent, little is known about how it will change the dynamics of learning communities and classrooms.”
  • The paper relies on this without support.

    People’s design ideas rarely appear out of thin air, but reflect what people have seen and experienced.

    “People’s design ideas rarely appear out of thin air, but reflect what people have seen and experienced.”
5 of 5

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

1 of 1

Citations

Cites

Show all 53 references

Research works printed but not linked: 9

  1. Caramiaux B., 2022, Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 1-24
  2. 10.1145/3271625 · DOI
  3. Heikkilä , M. 2022. “This Artist is Dominating AI-Generated Art. And he’s not Happy about it.” MIT Tech Review , September 16, 2022.
  4. Levendowski A., 2018, Washington Law Review, 93, 579
  5. Martinez S., 2016, Invent to Learn: Making, Tinkering and Engineering in the Classroom. In 2016 Edi
  6. Patel, K. 2008. "Thinkers in the Kitchen: Embodied Thinking and Learning in Practice." Ann Arbour (MI): UMI dissertation services ProQuest.
  7. Seitamaa-Hakkarainen P., 2013, Proceedings of the 2nd International Conference for Design Education Researchers, 1369
  8. TENK. 2019. The Ethical Principles of Research with Human Participants and Ethical Review in the Human Sciences in Finland Finnish National Board on Research Integrity TENK guidelines 2019. https://tenk.fi/sites/default/files/2021-01/Ethical_review_in_human_sciences_2020.pdf.
  9. Vartiainen H., 2020, Techne Series, 27, 52

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Metadata

Authors
Vartiainen, H., & Tedre, M.
Affiliations
University of Eastern Finland (FI)
Corresponding author
Vartiainen, Henriikka
Venue
Digital Creativity
Published
2023-01-02
Volume
34
Issue
1
Pages
1-21
ISSN
  • 1462-6268 (ISSN-L)
  • 1744-3806
OpenAlex
W4321596574
Cited by
263
References
53
Citations by year
2026: 54 · 2025: 98 · 2024: 81 · 2023: 28
FWCI
61.15
Type
journal article
Language
en
Open access
Locations
Digital Creativity (publishedVersion, cc-by)
Funders
Strategic Research Council (352859 and #352876)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art Education and Development
  • Social Sciences › Education › Digital Education and Society
Keywords
generative AI, text-to-image models, craft education, teacher educators, creative making, algorithmic bias, copyright, power relations, data-driven design

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