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Record W2093284579 · doi:10.5539/ass.v8n10p151

An Evaluation of Advanced Level Chemistry Teaching in Gweru District Schools, Zimbabwe

2012· article· en· W2093284579 on OpenAlexvenueno aff
Mandina Shadreck

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumChemistry educationQuality (philosophy)Christian ministryMathematics educationChemistryMedical educationEngineeringPsychologyPedagogyMedicinePolitical sciencePhysics

Abstract

fetched live from OpenAlex

This study evaluated the implementation of the Advanced level chemistry curriculum in Gweru district secondary schools in Zimbabwe. To guide this study seven research questions were raised and answered. The study employed a descriptive survey design and three instruments were used to collect data from 6 secondary schools selected from 12 schools in the district using the Probability Proportionate to Size (PPS) sampling technique. Six (6) school heads, 10 chemistry teachers and 130 students participated in the study. The instruments used for data collection were a questionnaire, interviews and personal observations. The study established that the important factors that limit the quality of chemistry teaching and learning include overloaded curriculum content and inadequate time for teaching chemistry; inadequate resources, apparatus, equipment and consumables. Insufficient funding of science, lack of support staff and ineffective teaching methodologies further limit the quality of chemistry teaching and learning. The study recommends the in servicing of chemistry teachers to give them a better orientation on what is expected of them and expose them to current methods of teaching and presenting content materials to learners. The Ministry of Education Arts, Sports and Culture should for partnerships with private sector and nongovernmental organizations to provide the necessary infrastructure and enabling environment to make chemistry education thrive.

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)0.006
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.098
GPT teacher head0.473
Teacher spread0.374 · 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 designObservational
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

Citations2
Published2012
Admission routes1
Has abstractyes

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