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Record W4411618261 · doi:10.51847/gcvb1wwtyz

10.51847/gcVB1WWTyZ

2000· article· en· W4411618261 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPsychologyTraining (meteorology)Medical educationAcademic achievementPedagogyMedicinePhysics

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the effect of life skills training on the academic achievement of tenth grade students in Tehran.Method of research is descriptive and a survey research.The study population consists of all tenth grade students who are studying in Tehran in the academic year 2016-2017.Of the population, stratified sample of 376 people were selected.Procedure of the study is that the sample were taught the life skills in 10 sessions of 90 minutes and finally the academic achievement of them was compared with their academic achievement scores (cut-off point).The score that students gained in Standardized and coordinated achievement test, which was run by Education and Training organization were the measure of student achievement.The method of analysis is T-test single group that after running, it was determined that mean of sample group was higher than cut-off point of the population and their difference was significant.So with 99% of confidence we can say that life skills training is effective on the academic achievement of students in Tehran.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.087
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9130.897

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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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