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Record W2344847813 · doi:10.5539/jel.v5n3p83

Implementation of Cooperative Learning Model in Preschool

2016· article· en· W2344847813 on OpenAlexvenueno aff
Nilüfer Okur Akçay

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsJigsawMathematics educationChristian ministryPsychologyClass (philosophy)Data collectionTeaching methodTest (biology)Sample (material)Subject (documents)PedagogyComputer scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

<p>In this study, the effectivity of jigsaw method, one of the cooperative learning models, on teaching the concepts related to sense organs and their functions to four-five year-old children in nursery class was analyzed. The study is in the semi-experimental design consisting of experimental and control groups and pretest and posttest. The sample of this study consists of 38 children from the nursery class of Ministry of National Education in Ağrı city center, in 2015-2016 academic years. Two groups determined randomly have been formed. These are: Jigsaw Group (JG, N=20) and Control Group (CG, N=18). In the direction of the goals of this study, a data collection tool has been developed by the researcher to collect data. The test prepared by the researcher to determine the knowledge levels of the students about organs like ear, tongue, eye and skin and senses like hearing, smelling, tasting, seeing and sensing has been used. As a result of the obtained data, it has been determined that cooperative learning model is more effective in teaching the sense organs subject to the children compared to the traditional teaching method.</p>

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)0.005
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.353
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

Citations29
Published2016
Admission routes1
Has abstractyes

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