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Record W4405762906 · doi:10.21810/sfuer.v16i1.6689

A Thematic Literature Review of Decolonization and Abolitionist Approaches in Computing Education

2024· article· en· W4405762906 on OpenAlexaffvenue
Karmal Malik, Rutwa Engineer, Adelina Patlatii, S. S. Sarin

Bibliographic record

VenueSFU Educational Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Technology in Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCritical pedagogyCritical thinkingSociologyDiversity (politics)PedagogyEngineering ethicsDecolonizationThematic analysisCritical theoryPower (physics)EpistemologyPolitical scienceSocial scienceQualitative researchPoliticsEngineering

Abstract

fetched live from OpenAlex

This scoping review explores the role of critical and culturally responsive pedagogy in addressing the significant gap in computer science (CS) education. Despite ongoing efforts to increase diversity, many groups, including women, remain underrepresented in CS. The research draws on Paulo Freire's foundational ideas on critical pedagogy, advocating for a dynamic and ethical approach to teaching that fosters critical thinking and community involvement. The review also examines various interventions in literature which incorporate critical, decolonial, and abolitionist pedagogies in CS education. Addressing both the technical and social dimensions of computing, educators can equip students with the tools needed to challenge and transform existing power structures, contributing to a more just and equitable society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0170.020
Science and technology studies0.0020.003
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.388
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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