The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Teaching Elementary Computer Science through Universal Design for Learning
Open accessAbstract
Given the academic diversity of today's classrooms, elementary teachers engaged in computer science (CS) and computational thinking (CT) instruction must create CS/CT experiences that are accessible and engaging to a broad range of learners, including those with disabilities. One method of developing inclusive instructional experiences is through the Universal Design for Learning (UDL) framework, wherein teachers proactively design instruction for the broadest range of learners. Doing so may be challenging as elementary teachers may not be familiar with the UDL framework or may not have experience with applying UDL within CS/CT instruction. The purpose of this qualitative study was to investigate how four elementary teachers provided UDL-based instruction to academically diverse learners during CS/CT instruction. Teachers received professional development and instructional coaching related to UDL within CS/CT education. Data included teachers' lesson plans, coaching logs, and teacher interviews which were qualitatively analyzed and triangulated. Data revealed that teachers generally addressed all three UDL principles, with an emphasis on two of the principles (multiple means of engagement and multiple means of representing content) above the third principle (multiple means of action and expression). They focused on breaking tasks into steps, emphasizing student choice, and presenting information in multiple ways. Findings revealed nuanced implementation differences among the teachers as well.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The cited source says what the claim attributes to it.
In the citing paper
“Three papers focused on K-12 and/or specialist teachers such as TVIs (e.g., [23, 24]) and involved no disabled students.”
From Where are the Disabled Students?: A Literature Review of Disability Inclusion in Computing Education Research (2026) · cites this paper as [24]
The cited source says what the claim attributes to it.
In the citing paper
“Two of the 10 papers focused on teaching specifically to disabled students (e.g., [23]), and one paper was about teaching accessibly to all students [24].”
From Where are the Disabled Students?: A Literature Review of Disability Inclusion in Computing Education Research (2026) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398
National Center for Education Statistics
Carlson, C. L. (2008) · Encyclopedia of Educational Psychology · doi:10.4135/9781412963848.n192 · Cited by 4,546
Qualitative research in practice : examples for discussion and analysis
Merriam, S. B. (2002) · Cited by 4,203
Universal Design for Learning Guidelines, version 1.0.
Cast (2008) · Cited by 1,808
Teaching every student in the digital age: universal design for learning
(2003) · Choice Reviews Online · doi:10.5860/choice.40-3555 · Cited by 1,528
Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis
Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015) · Computers & Education · doi:10.1016/j.compedu.2014.11.022 · Cited by 333
Self-citationUnderstanding STEM Education and Supporting Students through Universal Design for Learning
Basham, J. D., & Marino, M. T. (2013) · Teaching Exceptional Children · doi:10.1177/004005991304500401 · Cited by 239
Children and Youth With Disabilities: Innovative Methods for Single Qualitative Interviews
Teachman, G., & Gibson, B. E. (2012) · Qualitative Health Research · doi:10.1177/1049732312468063 · Cited by 220
King-Sears, M. E., Johnson, T., Berkeley, S., Weiss, M. P., Peters-Burton, E., Evmenova, A., Menditto, A., & Hursh, J. C. (2015) · Learning Disability Quarterly · doi:10.1177/0731948714564575 · Cited by 90
"For all" in "computer science for all"
Ladner, R. E., & Israel, M. (2016) · Communications of the ACM · doi:10.1145/2971329 · Cited by 79
Self-citation
Research works printed but not linked: 1
- Matthew S Taylor . 2018. Computer Programming With PreK-1st Grade Students With Intellectual Disabilities. The Journal of Special Education ( 2018 ), 0022466918761120. Matthew S Taylor. 2018. Computer Programming With PreK-1st Grade Students With Intellectual Disabilities. The Journal of Special Education (2018), 0022466918761120.
Cited by
Haynes-Magyar, C., & Ericson, B. J. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445292 · Cited by 35
Θωμά, Ρ., Φαρασόπουλος, Ν., & Lousta, C. (2023) · Teaching and Teacher Education · doi:10.1016/j.tate.2023.104210 · Cited by 28
Teaching computational thinking to exceptional learners: lessons from two inclusive classrooms
Prado, Y., Jacob, S. R., & Warschauer, M. (2021) · Computer Science Education · doi:10.1080/08993408.2021.1914459 · Cited by 31
Israel, M., Kester, B., Williams, J., & Ray, M. J. (2022) · ACM Transactions on Computing Education · doi:10.1145/3513138 · Cited by 28
Self-citation
Metadata
- Authors
- Israel, M., Jeong, G., Ray, M., & Lash, T.
- Affiliations
- University of Florida (US)
- University of Illinois Urbana-Champaign (US)
- Cornell Tech (US)
- Venue
- Proceedings of the 51st ACM Technical Symposium on Computer Science Education
- Publisher
- ACM
- Published
- 2020-02-26
- Pages
- 1220-1226
- OpenAlex
- W3007359344
- Cited by
- 49
- References
- 17
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 7 · 2023: 11 · 2022: 3 · 2021: 4 · 2020: 2
- FWCI
- 5.81
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Technical Symposium on Computer Science Education (SIGCSE) (publishedVersion)
- Funders
- National Science Foundation (1935196)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Education › Disability Education and Employment
- Social Sciences › Education › Inclusive Education and Diversity
- Keywords
- Universal Design for Learning, computational thinking, inclusive instruction, students with disabilities, teacher professional development, instructional coaching, multiple means of engagement, multiple means of representation, student choice
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
