The Mediating Effect of Student Involvement between Social Practice Activity and Sense of Social Responsibility
Bibliographic record
Abstract
The study aims to understand the intricate association between Social Practice Activity (SPA), Students' Involvement (SI), and Sense of Social Responsibility (SSR), and focuses on the following two questions: (1) What is the relationship between SPA, SI and SSR? (2) Does SI have a mediating role in SPA and SSR? The questionnaire was employed in this study, 502 valid questionnaires were received from college students at a vocational university in Shanxi, China. Data were analyzed using the software including SPSS and AMOS, and the specific methods include correlational analysis, confirmatory factor analysis and structural equation modeling. The Bootstrap method mediating effect test was used to test the mediating role of SI between SPA and SSR. The results revealed that there was a significant correlation between SPA, SI and SSR and their dimensions. SI (including rule-based involvement, procedural involvement, and autonomous involvement) has a positive mediating effect between SPA (including activity organization, teacher guidance, and service support) and SSR (including global social responsibility and responsibility of people). This result supports that focus on students' involvement in social practice activities, and combine the creation of an external environment with the promotion of individual involvement.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".