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Record W2951343728 · doi:10.21083/ajote.v8i0.4367

The medium of instruction in Ethiopian Higher Education Institutions: Kotebe Metropolitan University Case study.

2019· article· en· W2951343728 on OpenAlexvenueno aff
Bekau Atnafu Taye

Bibliographic record

VenueAfrican Journal of Teacher Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAmharicOfficial languageFirst languagePolitical scienceLocal languageFocus groupMedium of instructionPopulationSociologyPsychologyPedagogyLinguisticsComputer scienceLawDemographyAnthropology

Abstract

fetched live from OpenAlex

The aim of this article is to examine the medium of instruction in Ethiopian higher education institutions and the perceived consequences of the failure to learn a lingua franca. The study was qualitative and it used interviews and focus group discussions (FGDs). Five teachers and five students took part in the interviews and six teachers and six students participated in the FGDs. The findings of the study showed that the role of Amharic as a working language has not been given recognition despite the fact that Amharic was constitutionally granted to be a working language. Due to language barriers, students who are speakers of Oromipha and other languages from the Eastern and Western parts of Ethiopia suffer passivity in the classroom because they do not speak Amharic although Amharic has been taught as a subject in all regional states of the country. Increased identity politics seems to have generated a negative attitude towards Amharic, Ethiopia's former official lingua franca. Non-Amharic native speakers appeared to lose interest in learning Amharic while they were in primary and secondary schools. The absence of an official, common language which could be used for wider communication in higher education has resulted in having challenges among the student population.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.323
Teacher spread0.296 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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