Impact of Adventure-Based Approaches on the Self-Conceptions of Middle School Physical Education Students
Bibliographic record
Abstract
Background: Research has identified enhancement of positive self-concept as an important outcome connected with participation in adventure-based activities in physical education (PE). Purpose: This study compared the effectiveness of Team Building Through Physical Challenges (TBPC) and Adventure Curriculum for Physical Education (ACPE) programs on the self-conceptions of middle school PE students. Both approaches include adventure-type tasks adapted for use in PE. Methodology/Approach: Participants consisted of 397 female ( n = 183) and male ( n = 214) students who were enrolled in Coeducational Grades 7 and 8 PE classes in three middle schools. Students in the treatment classes were exposed to either the TBPC condition or the ACPE condition during PE classes over 7 months, whereas students in the control group completed the regular PE curriculum that did not include activities from either approach. Findings/Conclusions: Results suggest that both approaches benefit the self-conceptions of children with each being particularly effective at changing those self-conceptions logically related to specific organizing themes. Specifically, ACPE was greater than TBPC, for global self-worth and perceived behavioral conduct. TBPC was greater than ACPE for perceived social approval. Implications: Incorporating either the TBPC or the ACPE program in middle school PE can benefit the self-conceptions of 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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".