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Record W4403764111 · doi:10.24908/pceea.2023.17110

A Review of Trends in Engineering Education Research from an Equity, Diversity, and Inclusion Perspective

2024· review· en· W4403764111 on OpenAlexaffvenueabout
Branna MacDougall, Demewoz Menna, Bronwyn Chorlton

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typereview
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsQueen's University
Fundersnot available
KeywordsPerspective (graphical)Diversity (politics)Inclusion (mineral)Equity (law)Engineering ethicsSociologyPolitical scienceRegional scienceSocial scienceEngineeringComputer scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Equity, diversity, and inclusivity (EDI) have been a topic of high interest in recent years as engineering trends towards becoming a diverse and inclusive profession for all. The purpose of this research is to understand trends in EDI-related engineering education research in Canada over the past ten years and to allow for a reflection of previously identified needs that have yet to see change. This study considers engineering education papers based in Canada published from 2013 through 2022. Several unique subsets of EDI have been consistent areas of interest throughout the past 10 years; gender has been and remains one of the top researched EDI topics, with race and ethnicity receiving approximately consistent research attention throughout, albeit to a lesser extent than gender. Certain areas of diversity have seen consistently little research attention throughout the years, such as the need to consider accessibility in engineering education and practice.

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0180.030
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.069
GPT teacher head0.394
Teacher spread0.325 · 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.

Study designSystematic review
DomainMethods
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

Citations1
Published2024
Admission routes3
Has abstractyes

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Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicCareer Development and DiversityFrench-language works237,207