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Record W2803461462 · doi:10.5430/wje.v8n3p18

The Degree of Including International Standards of Science Education in the Physics Syllabus of Palestinian Secondary Schools

2018· article· en· W2803461462 on OpenAlexvenueno aff
Inas Aref Saleh Naser

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSyllabusMathematics educationScience educationEleventhLearning standardsSample (material)Academic standardsSecondary educationPhysics educationPsychologyPedagogyHigher educationPolitical sciencePhysicsCurriculum

Abstract

fetched live from OpenAlex

This study aimed at finding out the degree of including international standards of science education in the physicssyllabus of the secondary stage in Palestinian schools. The sample of the study consisted of the analytical aspect ofthe physics textbooks of the eleventh and twelfth grades. The findings of the study show that the rates of includinginternational standards of science education in these textbooks do not match expectations. The study also shows thatthe criterion of physics ranked first on the study scale among the criteria of content, followed by the criterion ofscience as a survey, and then the criterion of unified concepts and processes of science. However, there is obviousomission of the standards of science and technology, science from personal and societal perspectives, and the historyand nature of science. In light of these results, the researcher recommends the development of the physics syllabus ofthe secondary stage to include international standards. The study, further, calls for more research on the assessmentof physics textbooks and other disciples of science at different educational levels in view of content standards as wellason the impact of including such standards on the learning outputs.

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)0.004
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 score0.596
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.061
GPT teacher head0.412
Teacher spread0.351 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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