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Record W2985900629 · doi:10.5944/openpraxis.11.3.981

OER Mainstreaming in Cameroon: Perceptions and Barriers

2019· article· en· W2985900629 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Praxis · 2019
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOpen educational resourcesMainstreamingContext (archaeology)Government (linguistics)Higher educationNoveltyPolitical scienceEconomic growthPedagogySociologyPsychologyGeographySpecial educationEconomics

Abstract

fetched live from OpenAlex

The government of Cameroon has been increasingly pre-occupied with the quality of learning outcomes and the lack of learning resources at all levels of the education system. Research on similar educational systems in Sub-Saharan Africa and beyond indicate that Ministries of Education are exploring the potential of open educational resources (OER) to cut down the high cost of textbooks and enhance the availability of quality learning materials in classrooms. To explore possibilities of mainstreaming OER under the Ministries of Basic and Secondary Education in Cameroon, a quantitative research design approach was used to survey n=393 Regional Pedagogic Supervisors from the 10 Regions of the country. The outcome of this study presents the factors shaping the perspectives of Regional Pedagogic Supervisors in terms of perceptions and barriers to using OER. The novelty of this approach is the application of a proven model for technology acceptance testing in the context of OER. Based on the findings, three major recommendations for mainstreaming OER in Cameroon with potential impact on lowering textbook costs and increasing learning outcomes were formulated.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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