Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 49Teaching and Learning ProgrammingDisability Education and EmploymentInclusive Education and Diversity

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 access
Israel, Maya, Jeong, Gakyung, Ray, Meg, Lash, Todd·2020·Proceedings of the 51st ACM Technical Symposium on Computer Science Education

Abstract

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/3328778.3366823

Cites

17 of 17 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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.

The self-check needs the paper’s full text.

Citations

Cites

Show all 17 references

Research works printed but not linked: 1

  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

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
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.