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Record W2599167657 · doi:10.5539/ies.v10n4p78

Competencies for Production, Search, Diffusion and Mobilization of Open Educational Resources

2017· article· en· W2599167657 on OpenAlexvenueno aff
Ramona-Imelda García-López, Omar Cuevas Salazar, Gloria Concepción Tenorio Sepúlveda

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsRubricOpen educational resourcesLatin AmericansMathematics educationProduction (economics)Distance educationHigher educationOpen educationPsychologyPolitical sciencePedagogyMedical educationEconomic growthEconomics

Abstract

fetched live from OpenAlex

The purpose of this study is to evaluate the achievement of competencies for production, search, diffusion and open educational resources through a Massive Open Online Course (MOOC). The development of this project required the participation of 10 institutions of higher education in Mexico*, as well as financial support from the National System of Distance Education (SINED). This is a quantitative research and the participants were 134 teachers in Mexico and other Latin American countries. Rubrics were used to evaluate the competencies mentioned (which conformed the four modules object of study); each was broken down into indicators and self-assessment was used with the student (basic), beginner (intermediate) and expert (advanced) criteria. It was found that in the three levels of competency, the total percentage is very similar in the four modules: Basic level is between 0.5% y 3.9%, intermediate, around 30.0% and 31.5% and advanced around 65.4% and 69.5%.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score1.000
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.093
GPT teacher head0.414
Teacher spread0.321 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

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