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Record W4379056372 · doi:10.21083/ajote.v12i1.7266

Implementing competence about vision disturbances in Tanzania’s teacher education: A contextual analysis

2023· article· en· W4379056372 on OpenAlexvenueno aff
Vibeke Vågenes, Kari Ludvigsen, Arne Jacob Melting

Bibliographic record

VenueAfrican Journal of Teacher Education · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamCompetence (human resources)NorwegianTanzaniaPsychologyPedagogyMathematics educationTeacher educationSociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Around the world, schoolchildren suffer from vision disturbances that may challenge their ability to learn to read and write. Often teachers lack the competences to identify and help children who struggle with vision problems. This study is a part of a Norwegian-Tanzanian research project with intentions to strengthen teachers’ competences on identifying and improving pupils’ vision problems. With a qualitative research design, we analyse how contextual factors of task, time, scale and direction provided possibilities and barriers for implementing the new competence in Tanzanian special needs teacher education, and for scaling up the competence to mainstream teacher education. The task, timing, and direction of the capacity building meant that the efforts were well received in special needs teacher education. The core ideas of the competence building corresponded with the national education strategies for inclusive education and may spread awareness on learning difficulties amongst teachers. Teachers’ knowledge and awareness of vision disturbances and other learning problems may contribute to enhancing inclusive educational goals. However, further scaling up of the competence to ordinary teachers and into mainstream classrooms is hindered by factors related to task and scale, in particular a dual-track educational system and lack of teacher competencies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.341
Teacher spread0.301 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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