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Record W7061250351

PENERAPAN PEMBELAJARAN RESIPROKAL DALAM PERMAINAN BOLA BESAR UNTUK MENINGKATKAN PHYSICAL LITERACY SISWA SEKOLAH DASAR

2023· other· id· W7061250351 on OpenAlexaboutno aff

Bibliographic record

VenueRepository at Universitas Pendidikan Indonesia (Universitas Pendidikan Indonesia) · 2023
Typeother
Languageid
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Domain (mathematical analysis)Christian ministryNasalization
DOInot available

Abstract

fetched live from OpenAlex

Dalam lingkup pendidikan jasmani, physical literacy ialah muara dari pendidikan jasmani. Dengan demikian, diperlukan suatu pendekatan guna meningkatkan physical literacy yaitu dengan menggunakan penerapan pembelajaran resiprokal dalam permainan bola besar. Sehubung dengan itu, pada penelitian ini permainan bola besar di modifikasi untuk anak sekolah dasar menjadi bola voli mini dan sepak bola mini. Tujuan penelitian ini untuk mengetahui apakah penerapan pembelajaran resiprokal dalam permainan bola besar dapat meningkatkan physical literacy siswa sekolah dasar, khususnya pada domain pengetahuan dan pemahaman & domain kompetensi fisik. Menggunakan instrumen penelitian Canadian Asessment Physical Literacy (CAPL-2). Penelitian ini dilaksanakan melalui metode penelitian eksperimen yang dilakukan sebanyak 12 kali pertemuan. Sampel penelitian ini adalah 27 siswa kelas V SDPN 252 Setiabudi Bandung. Sampel dibagi menjadi dua yaitu kelompok eksperimen dan kelompok kontrol. Hasil yang di dapat dalam hipotesis awal kedua kelompok memiliki kemampuan yang sama. Kemudian, pada hipotesis akhir terdapat perbedaan hasil dari dua kelompok tersebut kelompok eksperimen dan kelompok kontrol pada post-test, yaitu adanya peningkatan kelompok eksperimen dari dua domain physical literacy (pengetahuan dan pemahaman & komponen fisik) sedangkan kelompok kontrol tidak ada. Adanya peningkatan pada kelompok eksperimen karena adanya pengaruh atau pemberian treatment penerapan pembelajaran resiprokal dalam permainan bola besar. Dapat disimpulkan bahwa penerapan pembelajaran resiprokal dalam permainan bola besar dapat meningkatkan physical literacy siswa sekolah dasar. Within the scope of Physical Education, physical literacy is the estuary of physical education. Thus, an approach is needed to improve physical literacy, such as by using the application of reciprocal learning in big ball games. In this regard, in this study, the big ball game was modified for elementary school children to become mini volleyball and mini soccer. The purpose of this study was to find out whether the application of reciprocal learning in big ball games could can improve the physical literacy of elementary school students by using the Canadian Assessment Physical Literacy (CAPL-2) research instrument. Experimental research method was conducted in 12 meetings. Samples of the study were 27 fifth grade students at SDPN 252 Setiabudi Bandung. The samples were divided into two groups, such us the experimental group and the control group. The results obtained in the initial hypothesis showed that the two groups had the same abilities. Then, in the final hypothesis, there a difference in the results of the two groups on post-test scores. It implies that there was an increase in the experimental group from the two domains of physical literacy (knowledge and understanding & physical components), while the control group was not. The increase in the experimental group might be because of the influence of reciprocal learning in big ball games. It can be concluded that the application of reciprocal learning in big ball games can improve the physical literacy of elementary school students.

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)0.003
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: none
Teacher disagreement score0.042
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0420.008

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 head0.009
GPT teacher head0.243
Teacher spread0.233 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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