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Record W2914930431 · doi:10.5430/jct.v8n1p11

Assessment of Processes and Resources for Knowledge of Skills of a Chemistry Laboratory at the Senior High School of Ternate Island

2019· article· en· W2914930431 on OpenAlexvenueno aff
Nurfatimah Sugrah, St. Hayatun Nur Abu, Nurul Aulia Rahman, Khusna Arif Rakhman, Muhammad Danial, Muhammad Anwar

Bibliographic record

VenueJournal of Curriculum and Teaching · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSTEM Education
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationScheduleMathematics educationMedical educationPedagogyPsychologyManagementMedicine

Abstract

fetched live from OpenAlex

This article discusses the influence of learning support processes and resources in the knowledge of ChemicalLaboratory skills of high school students in Ternate Island. The learning process of chemistry in high schoolespecially on laboratory, related to time/schedule allocation, practical purpose and achievement indicator in skill areabecome the focus of discussion on this aspect. While the supporting resources of learning, more emphasized onaspects of facilities and infrastructure such as the availability of educators, laboratory buildings, tools and chemicalsthat are based on the value of accreditation Senior High School in Ternate Island. in this study using 3 methods ofcollecting data such as survey techniques in schools, interview with teachers in schools and tests students' lab skills.The results showed that the knowledge of high school students' lab skills on Ternate Island is getting higher inschools with better accreditation. Skill Knowledge of High School Students in Ternate Island is still in the lowcategory on the glass organizing aspect at the laboratory.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.310
Teacher spread0.304 · 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 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
Published2019
Admission routes1
Has abstractyes

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