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Record W4388164259 · doi:10.1080/01587919.2023.2267472

Equity, diversity, and inclusion in open education: A systematic literature review

2023· article· en· W4388164259 on OpenAlexfundno aff
Francisco Iniesto, Carina Bossu

Bibliographic record

VenueDistance Education · 2023
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
FundersGovernment of NunavutWilliam and Flora Hewlett Foundation
KeywordsInclusion (mineral)Equity (law)Diversity (politics)Distance educationPerspective (graphical)Systematic reviewKnowledge managementSociologyOpen educational resourcesHigher educationOpen educationPublic relationsPedagogyEngineering ethicsPolitical scienceComputer scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

Equity, diversity, and inclusion (EDI) and open education are key areas in the current development of educational systems internationally.However, little is known about the general perspective of what has been addressed about EDI in open educational contexts to date.To address this gap, this paper presents a systematic literature review of 15 papers where we examined the current state of the art and the main suggestions for EDI implementation.Results indicate that practitioners should involve all stakeholders, including institutions, faculty members, and students, in EDI development to enhance open educational practices as well as in the cocreation of open educational resources which need to consider culture, language, and location, among others.This review of literature contributes an evidence base to support the future development and adoption of EDI in open educational contexts by organizing relevant literature into coherent themes that can inform future research.

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)0.028
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.095
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0210.020
Science and technology studies0.0020.002
Scholarly communication0.0040.006
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.353
Teacher spread0.322 · 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
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

Citations23
Published2023
Admission routes1
Has abstractyes

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