The Effects of Extra-Curricular Involvement on CÉGEP Student Success: A Correlational Study
Bibliographic record
Abstract
The topic of extra-curricular involvement has been studied extensively in various forms. However, most research has focused on extra-curricular involvement at the secondary education level with a large number of studies examining after school programs and athletics. Fewer studies have looked at higher education students as a population and those that have returned mixed results. The purpose of this research is to study how involvement in extra-curricular activities (ECAs) affects student success as determined by academic standing. In conducting this study, a modified version of the National Survey for Student Engagement was used as the primary instrument to gather data from 135 students (64.4% male, 35.6% female) enrolled in various academic programs in a Montréal area Anglophone CÉGEP. A quantitative correlational design was used to address several research questions which focused on determining the relationship between ECAs and student success. Furthermore, ECAs were categorized into groupings and tested to ascertain which sets have the greatest impact on student success. Results, limitations, implications, future direction, and conclusions are discussed.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".