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Record W4407993600 · doi:10.3126/ire.v9i2.75029

Impact of Physical Activity on Academic Achievement of Secondary Level Students in Kathmandu

2024· article· en· W4407993600 on OpenAlexaff
Shailandra Chiluwal, Kishore Bohara, Suresh Jang Shahi, Mitra Lal Shrestha, Suresh Bahadur Thapa

Bibliographic record

VenueInterdisciplinary Research in Education · 2024
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMathematics educationAcademic achievementPsychology

Abstract

fetched live from OpenAlex

This study aims at exploring the impact of physical activity on the academic achievement of secondary-level students in Kathmandu District, Nepal. Cross-sectional research design was used, and data were collected from 31 students of grade nine and ten studying at Pushpa Kunja High School through structured questionnaires. The results reveal an inverse relationship between physical activity and academic performance. Solo activities like running and walking positively affected academic achievement, while team sports and yoga showed inconsistent trends. A statistically significant negative correlation was also found between the intensity of physical activity and academic performance (r = −0.392, p = 0.029). It means; higher the students' achievement level, lesser the participation in vigorous activities. This would challenge the assumption of a universally positive relationship between physical activity and academic achievement and also highlights the importance of balancing them for good academic achievement. This study, therefore, calls for specific school-based interventions to ensure optimal physical activities for holistic development, considering the unique cultural and infrastructural factors related to Nepal's education system.

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 score0.008
Threshold uncertainty score0.015

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 integrity0.0000.001
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 head0.281
GPT teacher head0.671
Teacher spread0.391 · 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
Published2024
Admission routes1
Has abstractyes

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