Research on the Impact of College Students' Participation in Social Practice Activities for Special Children on Their Attitudes and Behavioral Intentions
Bibliographic record
Abstract
Studying the influence of college students' participation in social practice activities serving special children on their attitudes and behavioral intentions not only enriches the existing research on attitudes towards special children but also provides certain data support and reference value for the research on college students' attitudes and behavioral intentions towards special children and the development of special children's education. It also meets the current practical needs of research on attitudes towards special children. Firstly, the research subjects were divided into the practice team group and the ordinary college student group, and questionnaires were conducted on both groups at the same time intervals. The questionnaire, combined with demographic information, examined the degree of acceptance, understanding, and related behaviors towards special children from three dimensions. Secondly, the demographic information and attitudes towards special children of the college student group and the practice team group were compared at the baseline state. Thirdly, independent sample t-tests, Kruskal-Wallis H or Mann-Whitney U tests were used to compare normal and non-normal continuous data respectively; for categorical variables, χ² tests were used when the minimum sample size was greater than 5, and Fisher's exact tests were used when the minimum sample size was less than or equal to 5. In addition, a linear regression model was used to explore the impact of contact with special children on college students' related attitudes, and the data with differences at the baseline were included as covariates in the multivariate linear regression model for adjustment. Finally, a non-restricted cubic spline model was used to fit the curve of the sum of scores in each dimension of the practice team group towards special children and the change over time. The survey found that ordinary college students had relatively low attention and contact with special children; however, contact with special children was beneficial to improving college students' attitudes and understanding of special children, and a series of targeted suggestions were put forward.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".