CoChat
Sign Up
Cited by 15Gender and Technology in EducationInclusion and Disability in Education and SportCareer Development and Diversity

Neurodivergent Legitimacy in Computing Spaces

Kirdani-Ryan, Mara, Ko, Amy J.·2024·ACM Transactions on Computing Education
DOI 10.1145/3690651
Open this paper in CoChat — free account

Abstract

For computing to serve humanity, computing spaces must be safe for all individuals. While prior work has surfaced how hegemonic racial and gendered expectations manifest in computing, it has only indirectly attended to expectations surrounding neurodivergence. As computing stereotypes largely align with stereotypes of some neurodivergent individuals, we investigated whether computing legitimized neurodivergent traits over neuronormative ones. We conducted semi-structured interviews with 21 students, faculty, and industry professionals, sampling both neurodivergent-identifying and non-neurodivergent-identifying participants. We found that computing legitimized hyper-focus, deep “special” interests, and high organization, and that fitting these expectations was frequently required for persistence. Some neurodivergent-identifying participants felt that computing provided refuge from societal neuronormative expectations, though one’s sense of refuge depended on sufficiently fitting computing’s neurodivergent expectations. We offer reflections on inclusion and belonging efforts within computing, as well as directions for future work that attends to individuals’ neurodivergent identities.

Integrity signals

Registry

Crossref · 10.1145/3690651

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • Systematic approaches to embedding accessibility and diversity in both technology development and computing curricula remain rare.

    “Despite widespread calls for inclusive education, systematic approaches to embedding accessibility and diversity in both technology development and computing curricula remain rare [2, 16, 17, 26].”

    From Teaching Participatory Inclusive IT Design with a Neurodiversity Lens in Computing Education (2025) · cites this paper as [16]

  • In much existing provision, neurodivergent students are positioned primarily as recipients of accommodations instead of equal partners in shaping technology and pedagogy.

    “In much existing provision, neurodivergent students are positioned primarily as recipients of accommodations instead of equal partners in shaping technology and pedagogy [1, 16, 40].”

    From Teaching Participatory Inclusive IT Design with a Neurodiversity Lens in Computing Education (2025) · cites this paper as [16]

  • Program-level alignment and institutional supports are needed to make participation less contingent and more sustainable.

    “Program-level alignment and institutional supports are likewise needed to make participation less contingent and more sustainable, echoing fieldlevel agendas for neurodiversity in academia [1, 4, 16, 37].”

    From Teaching Participatory Inclusive IT Design with a Neurodiversity Lens in Computing Education (2025) · cites this paper as [16]

  • Curriculum embedding is a necessary but not sufficient condition, to be complemented by policy, resourcing, and platform-level constraints.

    “Our results primarily speak to the first step of this pathway, learner knowledge and collaborative practice, rather than downstream institutional or platform change; accordingly, we frame curriculum embedding as a necessary but not sufficient condition, to be complemented by policy, resourcing, and platform-level constraints [4, 10, 16, 19, 21, 30, 37].”

    From Teaching Participatory Inclusive IT Design with a Neurodiversity Lens in Computing Education (2025) · cites this paper as [16]

  • The results primarily speak to learner knowledge and collaborative practice, not downstream institutional or platform change.

    “Our results primarily speak to the first step of this pathway, learner knowledge and collaborative practice, rather than downstream institutional or platform change; accordingly, we frame curriculum embedding as a necessary but not sufficient condition, to be complemented by policy, resourcing, and platform-level constraints [4, 10, 16, 19, 21, 30, 37].”

    From Teaching Participatory Inclusive IT Design with a Neurodiversity Lens in Computing Education (2025) · cites this paper as [16]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Kirdani-Ryan, M., & Ko, A. J.
Affiliations
University of Washington (US)
ORCID
Venue
ACM Transactions on Computing Education
Publisher
Association for Computing Machinery (ACM)
Published
2024-12-04
Volume
24
Issue
4
Pages
1-28
ISSN
1946-6226 (ISSN-L)
DOI
10.1145/3690651
OpenAlex
W4402227667
Cited by
15
References
17
Citations by year
2026: 6 · 2025: 9
FWCI
11.10
Type
journal article
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
ACM Transactions on Computing Education (publishedVersion)
Topics
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Social Sciences › Sociology and Political Science › Inclusion and Disability in Education and Sport
  • Social Sciences › Safety Research › Career Development and Diversity
Keywords
neurodivergence, neuronormativity, hyperfocus, interest groups, stereotypes, inclusion, sense of belonging, neurodivergent identity, computing workforce

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review