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Record W2808221400 · doi:10.5539/gjhs.v10n7p105

Extracurricular Activities Amongst Health Colleges Students at the Imam Abdulrahman Bin Faisal University

2018· article· en· W2808221400 on OpenAlexvenueno aff
Mohammed Al-Hariri, Abdulghani Al-Hattami

Bibliographic record

VenueGlobal Journal of Health Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationStudent affairsPsychologyExtracurricular activityBinIncentiveMedicinePedagogyHigher educationPolitical scienceEngineering

Abstract

fetched live from OpenAlex

OBJECTIVES: To study the attitude of health colleges students about extracurricular activities.METHODS: A cross sectional study was conducted among 213 students, only 117 students responded. An online survey was sent to all students in the second-year health colleges at the Imam Abdulrahman Bin Faisal University (formally University of Dammam) in Saudi Arabia in 2015 (February-April). The survey consisted of two parts; Part I: Students participation in different activities, and Part II: consisted of questions about the barriers of participating in the extracurricular activities.RESULTS: The results showed that the participation percentage in extracurricular activities was low (9.6%). Students at the present study reported that the most common obstacle was the conflict with the classes. Students stated other factors such as; there were no incentive, not encouraged by faculty members to participate in extracurricular activities, no guidance for the activities and its objectives and that most of the activities are not attractive.CONCLUSION: Engagement in extracurricular activities among health colleges student at the Imam Abdulrahman Bin Faisal University was low. Obstacles should be addressed by the deanships of student affairs in order to enhance the involvement in extracurricular activity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0070.005
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.447
Teacher spread0.417 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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