2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT) 2021
DOI: 10.1109/respect51740.2021.9620635
|View full text |Cite
|
Sign up to set email alerts
|

Do Abstractions Have Politics? Toward a More Critical Algorithm Analysis

Abstract: The expansion of computer science (CS) education in K-12 and higher-education in the United States has prompted deeper engagement with equity that moves beyond inclusion towards a more critical CS education. Rather than frame computing as a value-neutral tool, a justice-centered approach to equitable CS education draws on critical pedagogy to ensure the rightful presence of political struggles-emphasizing the development of not only knowledge and skills, but also CS disciplinary identities. While recent effort… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
11
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
4
1
1

Relationship

2
4

Authors

Journals

citations
Cited by 7 publications
(11 citation statements)
references
References 31 publications
0
11
0
Order By: Relevance
“…By centering runtime or space complexity analysis [28] as the primary means for evaluating data structure and algorithm tradeoffs, undergraduate computing programs emphasize efficiency as the primary (sometimes only) concern in data structure and algorithm analysis, thus marginalizing computing's ethical and social responsibilities. A more critical reading of the CS2 learning goals reveals the limits of cognitive approaches that frame "[a]lgorithm design and implementation [as] a means of realizing a specification or abstract data type without critically questioning the design of the abstraction" [8,22,25].…”
Section: Data Structures and Algorithmsmentioning
confidence: 99%
See 4 more Smart Citations
“…By centering runtime or space complexity analysis [28] as the primary means for evaluating data structure and algorithm tradeoffs, undergraduate computing programs emphasize efficiency as the primary (sometimes only) concern in data structure and algorithm analysis, thus marginalizing computing's ethical and social responsibilities. A more critical reading of the CS2 learning goals reveals the limits of cognitive approaches that frame "[a]lgorithm design and implementation [as] a means of realizing a specification or abstract data type without critically questioning the design of the abstraction" [8,22,25].…”
Section: Data Structures and Algorithmsmentioning
confidence: 99%
“…Ethics Critiques sociopolitical values of data structure and algorithm design [22] and dominant computing epistemologies that approach social good without design justice [8]. Identity Centers students in culturally responsive-sustaining pedagogies [9] to resist dominant computing culture and value Indigenous ways of living in nature [3].…”
Section: A Critical Comparative Approachmentioning
confidence: 99%
See 3 more Smart Citations