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Record W2991944144 · doi:10.21083/ajote.v8i0.5047

Underutilization of instructional materials for teaching and learning of Chemistry in Nigerian secondary schools: Ohafia Education Zone, Abia State’s Example.

2019· article· en· W2991944144 on OpenAlexvenueno aff
Ngozi O. Obiyo

Bibliographic record

VenueAfrican Journal of Teacher Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsAbiaCronbach's alphaMathematics educationPopulationMedical educationChemistry educationPsychologyChemistryPedagogyMedicineFood scienceEnvironmental health

Abstract

fetched live from OpenAlex

This study investigated the factors associated with underutilization of instructional materials for teaching and learning of Chemistry in Nigeria. A survey research design was adopted for the study. The study population comprised 86 Chemistry teachers and 1,180 Senior Secondary 2 (SS2) Chemistry students including those with special needs in the 86 public secondary schools in Ohafia Education Zone, Abia State in southeast geopolitical zone of Nigeria. The sample size was 456 respondents of 57 Chemistry teachers and 399 SS 2 Chemistry students selected through multi-stage sampling procedure. The data collection was by questionnaire and Cronbach Alpha was applied in computing the reliability estimate of 0.97. The findings indicated that the inability of teachers to improvise and their lack of manipulative skills, among others, are factors militating against the utilization of instructional materials. The researchers recommended the necessity for adequate provision of instructional materials in the schools and for teachers to ensure that these materials are effectively utilized. Students with special needs should be catered for based on their individualized education program as stipulated by the National Policy on Education in inclusive settings.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.552

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 head0.013
GPT teacher head0.306
Teacher spread0.292 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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