Helping him see: guiding a visually impaired student through the computer science curriculum
Abstract
In this paper, we describe some of the challenges of teaching computer science to a visually impaired student along with suggested solutions for these challenges. We include perspectives of both professors and a severely visually impaired student.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Three of the papers with disabled participants featured disabled author-participants.
“Three of these papers even featured disabled author-participants, with blind students [5, 17] and a blind CS professional [47].”
From Where are the Disabled Students?: A Literature Review of Disability Inclusion in Computing Education Research (2026) · cites this paper as [17]
Five papers involved disabled participants directly, with one paper featuring a disabled student co-author, and two papers featured teachers' descriptions of the experiences of disabled students.
“Five papers involved disabled participants directly, with one paper featuring a disabled student co-author [17], and two papers featured teachers' descriptions of the experiences of disabled students.”
From Where are the Disabled Students?: A Literature Review of Disability Inclusion in Computing Education Research (2026) · cites this paper as [17]
Cites
Karel the Robot: A Gentle Introduction to the Art of Programming
Pattis, R. E., Roberts, J., & Stehlik, M. (1994) · Cumulative Index of Computer Aided Architectural Design · Cited by 352 · see citing works
Reges, S. (2006) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/1121341.1121432 · Cited by 79 · see citing works
Roberts, E. S., Bruce, K. B., Cross, J. H., Cutler, R., Grissom, S., Klee, K. J., Rodger, S. H., Trees, F., Utting, I., & Yellin, F. (2006) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/1121341.1121384 · Cited by 26 · see citing works
Java: Learning to Program with Robots
Becker, B. W. (2006) · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Understanding Accessibility and Collaboration in Programming for People with Visual Impairments
Pandey, M., Kameswaran, V., Rao, H. V., O'Modhrain, S., & Oney, S. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449203 · Cited by 54 · see citing works
Teaching Algorithmic Thinking Using Haptic Models for Visually Impaired Students
Capovilla, D., Krugel, J., & Hubwieser, P. (2013) · International Conference on Learning and Teaching in Computing and Engineering (LaTICE) · doi:10.1109/latice.2013.14 · Cited by 24 · see citing works
Haptic Models of Arrays Through 3D Printing for Computer Science Education
Papazafiropulos, N., Fanucci, L., Leporini, B., Pelagatti, S., & Roncella, R. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-41264-1_67 · Cited by 15 · see citing works
Crockett, A. R., & Gannod, G. C. (2020) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie44824.2020.9273978 · Cited by 8 · see citing works
Lessons and tools from teaching a blind student
Connelly, R. (2010) · Journal of computing sciences in colleges · Cited by 8 · see citing works
Teaching spreadsheets to visually-impaired students in an environment similar to a mainstream class
Capovilla, D., & Hubwieser, P. (2013) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/2462476.2462477 · Cited by 5 · see citing works
How Learning Styles in CS Can Foster Inclusion of Visually Impaired Students
Capovilla, D., Mühling, A., & Hubwieser, P. (2015) · International Conference on Learning and Teaching in Computing and Engineering (LaTICE) · doi:10.1109/latice.2015.17 · Cited by 4 · see citing works
Figueira, I., Cisneros, J. M., Weber, J. L., Sanka, W., Phan, K., Wong-Ma, J., & Branham, S. M. (2026) · Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1 · doi:10.1145/3770762.3772561 · Cited by 3 · see citing works
A History of BPC: Lessons from Our Past Informing Our Future Directions
Melton, M., & Rorrer, A. S. (2024) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3626252.3630763 · Cited by 3 · see citing works
Making turing machines accessible to blind students
Crescenzi, P., Rossi, L., & Apollaro, G. (2012) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/2157136.2157190 · Cited by 2 · see citing works
A Complete Bibliography of Publications in SIGCSE Bulletin: 2000{2009
Beebe, N. H. F. (2012) · Cited by 1 · see citing works
Voice and Touch Diagrams (VATagrams) Diagrams for the Visually Impaired
Lung, T. (2011) · University Library - University of Saskatchewan (University of Saskatchewan)
- Authors
- Califf, M. E., Goodwin, M. M., & Brownell, J.
- Affiliations
- Illinois State University (US)
- Venue
- Proceedings of the 39th SIGCSE technical symposium on Computer science education
- Publisher
- ACM
- Published
- 2008-03-12
- Pages
- 444-448
- OpenAlex
- W2058741558
- Cited by
- 12
- References
- 4
- Citations by year
- 2026: 1 · 2024: 1 · 2021: 1 · 2020: 1 · 2016: 1 · 2015: 1 · 2013: 2 · 2012: 2
- FWCI
- 3.77
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Technical Symposium on Computer Science Education (SIGCSE) (publishedVersion)
- Topics
- Social Sciences › Safety Research › Disability Education and Employment
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Keywords
- visually impaired students, computer science education, accessibility, assistive technology, educational challenges, student perceptions
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