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Record W4406313536 · doi:10.21083/ajote.v13i2.7624

Implementation of learners’ science process skills by primary school teachers in the Lejweleputswa District of South Africa: A case study

2024· article· en· W4406313536 on OpenAlexvenueno aff
Ritu Bhagwandeen, Mrs Shirley Moopeloa, Awelani Rambuda

Bibliographic record

VenueAfrican Journal of Teacher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationProcess (computing)Scientific literacyPerceptionNatural scienceSchool teachersScience educationPsychologyPedagogyComputer science

Abstract

fetched live from OpenAlex

This research explores teachers’ perceptions of the development of learners’ science process skills through the implementation of inquiry-based approaches in Thabong primary schools in the Lejweleputswa District, South Africa. Its aim was to find effective teaching methods using inquiry-based approaches to develop learners’ science process skills and improve their scientific literacy. This quantitative study was conducted with natural sciences and technology, natural sciences, and mathematics teachers, and data was analysed using SPSS 27. The results showed a statistically significant relationship between inquiry-based approaches and learners’ acquisition of science process skills. Although teachers understood the advantages of using inquiry-based teaching, there were many obstructions to the implementation of this in classrooms in the schools used in this study.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.035
GPT teacher head0.424
Teacher spread0.389 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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