Service-Learning as a Catalyst for Community Change: An Empirical Examination Measuring the Benefits of a Life Skills Curriculum in Local At-Risk High Schools
Bibliographic record
Abstract
This research attempts to measure the impact of service-learning on community recipients – at-risk high school students in urban Southern California. The service-learning project, an integrative, six-week assignment, involves upper-division business majors delivering the Options: Business Education and Life Skills curriculum to at-risk students in two local alternative education high schools. In addition to delivering business education and life skills, a critical design component of the curriculum is the opportunity for college students to be role models and provide mentoring guidance to at-risk high school students. This study used surveys to gather data on student perceptions of four constructs: (1) strengths and values, (2) school and work-related skills, (3) business etiquette and resume building, and (4) future life and career planning. Pre-tests and post-tests were administered to gauge differences in perception during the six-week service-learning project. Results indicated positive effects of the service-learning curriculum overall. Further, the data revealed statistically significant results with particularly noteworthy outcomes in the planning for the future and preparing for the world of work responses.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".