MétaCan
Menu
Back to cohort
Record W2972273515 · doi:10.23887/jjpte.v6i2.20231

STUDI EVALUASI PROSES PEMBELAJARAN PRAKARYA DAN KEWIRAUSAHAAN KELAS XII MIPA DI SMA NEGERI 1 SINGARAJA

2017· article· en· W2972273515 on OpenAlexaff
Bayu Sukaharta, Nyoman Santiyadnya, Gede Nurhayata

Bibliographic record

VenueJurnal Pendidikan Teknik Elektro Undiksha · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Curriculum and Learning Methods
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics educationCraftNonprobability samplingClass (philosophy)Context (archaeology)Data collectionComputer sciencePsychologyMathematicsSociologyArtificial intelligenceStatisticsGeographyPopulation

Abstract

fetched live from OpenAlex

This study aims to describe the suitability of planning and learning process conducted by the teacher to the rules Permendikbud No. 22 Year 2016 and describes the suitability of doubtgiven weight to the learning plan that has been held. The evaluation study of the study include the planning and implementation process of the craft and entrepreneurial learning in SMAN 1 Singaraja, especially in class XII Mathematics. Sources of data in this study were teachers craft and entrepreneurship as well as students were selected using purposive sampling. The data collection technique used is the technique of interview, observation partisipatif,study documents, and questionnaires. Based on data analysis, obtained results of the study are: 1) variable learning plan for each teacher can be said to correspond to Permendikbud No. 22, 2016; 2) learning model in the implementation of applied learning by each teacher is different but still within the context of the same approach; 3) based on the student's perspective based questionnaires,implementation of learning each teacher reaches criteria.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.073
GPT teacher head0.424
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 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Pendidikan Teknik Elektro UndikshaSame topicEducational Curriculum and Learning MethodsFrench-language works237,207