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Record W4389796703 · doi:10.1177/21582440231215851

Policy Around the Teaching of English in Technical Education in Cameroon: Achievements, Issues, and Prospects From the Perspectives of Pedagogic Inspectors

2023· article· en· W4389796703 on OpenAlexaff
Alain Flaubert Takam, Innocent Mbouya Fassé

Bibliographic record

VenueSAGE Open · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsSyllabusChristian ministryPedagogyLanguage educationPolitical scienceEnglish languageTeacher educationMathematics educationSociologyPsychologyLaw

Abstract

fetched live from OpenAlex

Examining the teaching and learning of English as a Second Official Language (ESOL) in Cameroon through language laws and other official documents (like the syllabi) in terms of their actual implementation is an important step in the development of ESOL education. Such investigations may contribute to the strengthening of the minority official languages and facilitate conversations on the current state of ESOL teaching and learning and on future strategies to improve its policy, especially in technical education, a field that has so far been grossly under-researched. Through interviews conducted with pedagogic inspectors, this study, unlike most studies mentioned above, investigates the ESOL education policy in place at the Ministry of Secondary Education and its implementation in technical education schools. The Ministry’s determination to improve its ESOL programs shows the positive potential in the ESOL management in French Cameroon’s technical education. However, new proactive approaches are needed in the future. One important recommendation made insistently was the need for an approach focused on reorienting ESOL programs and teacher training for technical education.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.328
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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