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Record W2949157001 · doi:10.21083/ajote.v8i0.4451

The Middle Ground of Curriculum: History Teachers’ Experiences in Ghanaian Senior High Schools

2019· article· en· W2949157001 on OpenAlexaffvenue
Charles Adabo Oppong, Moses Allor Awinsong, Stephen Kwakye Apau

Bibliographic record

VenueAfrican Journal of Teacher Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCurriculumNegotiationCensusQualitative propertyCurriculum theoryQualitative researchMathematics educationEmergent curriculumProcess (computing)PedagogyCurriculum mappingSociologyCurriculum developmentMedical educationPsychologySocial scienceComputer scienceMedicine

Abstract

fetched live from OpenAlex

This study explores Ghanaian history teachers’ experiences of the "middle ground of curriculum; a crucial stage of curriculum negotiation and a process, according to Harris (2002), that includes what “teachers individually and collectively perceived and enacted. . . prior to classroom implementation” The study employed the concurrent parallel design (Quan-qual). The researchers collected quantitative data from sixty history teachers in Cape Coast Metropolis through the census method. Six teachers were randomly selected from the sixty to participate in the qualitative phase of the study. The quantitative data was analysed descriptively (means and standard deviations) while the qualitative data was analysed based on emerging themes. The findings revealed that the history departments through departmental relation, subject conceptualisation and governance influence the ways in which teachers negotiate the formal curriculum prior to teaching. More specifically, the study established the interaction of these variables that shape history teachers’ decision-making on the middle ground of the curriculum. The study, therefore, showed that the internalisation of curriculum change is a dynamic process that is evidenced at all levels of curriculum change – the high ground, middle ground of the curriculum, and lower ground

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)0.002
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 score0.165
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.060
GPT teacher head0.333
Teacher spread0.272 · 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
Published2019
Admission routes2
Has abstractyes

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