Enhancing Engagement and Academic Success Through Combat Sports in Higher Education
Bibliographic record
Abstract
This narrative survey evaluates the effects of combat sports together with physical education on student participation while developing discipline and academic achievements in higher education institutions. Physical education frameworks are widely recognized for wellness benefits yet academic employments of combat sports demonstrate limited study as education instruments for developing mental and social competencies that improve student learning achievement. This review analyses combat sports' structured discipline through domain-specific literature from sports science, educational psychology and higher education pedagogy which establishes the mechanisms through which combat sports develop university students' self-regulation, motivation and resilience and social cohesion. The study evaluates how these activities enable comprehensive pupil growth especially among minority student communities through developing personal identity together with increased self-assurance as well as social connection. Physical education provides an inclusive framework to merge educational success with physical activity through an examination of combat sports effectiveness as intervention methods. This study employed a qualitative review methodology, synthesising existing literature on combat sports, physical activity, and student development. To ensure sustainability, the paper recommends integrating combat sports and structured physical education into university curricula and co-curricular activities. These initiatives should be supported by inclusive student development policies. This approach fosters both academic success and holistic student wellness, particularly in under-resourced educational contexts where access and retention remain significant challenges.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".