Transforming college students through international service-learning: A case study of three programmes from the City-Youth Empowerment Project (CYEP)
Bibliographic record
Abstract
International service-learning (ISL) programmes, grounded under the transformative learning theory, have long shown promising results in enhancing the development of college students. However, in recent years, scholars have begun to take notice of the number of conceptual and methodological deficiencies that the ISL body of research suffers from. Our study addresses this void by adopting a quasi-experimental design to understand the developmental benefits accrued by college students who joined one of three ISL programmes. More specifically, this study seeks to understand the role of service settings and social context in the transformative process. A pretest-posttest approach was used to examine students’ growth in three ISL programmes (one from Cambodia and two from Myanmar). A total of 31 college students completed the questionnaire before and after the ISL programmes. Analysing the data through repeated-measure ANCOVAs, all three ISL programmes were found to help students increase their personal insight (general and social self-efficacy), understanding of social issues (interpersonal and problem-solving skills and political awareness) and cognitive development (communication skills). Establishing a non-hierarchical relationship with the partner agency in the service setting, providing emotional counseling to the college students and organizing multiple community outreach opportunities were found to be particularly beneficial for facilitating these transformations. Building on the results, suggestions for ISL practice and research are provided.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".