Examining the Experiences of an International Service Learning Program in Tanzania for Canadian Teacher Candidates
Bibliographic record
Abstract
International Service Learning (ISL) initiatives have been increasingly adopted by North American universities to better ensure that teacher candidates are instilled with the global mindedness required to ensure all students, regardless of ethnic or cultural backgrounds, have equal access and opportunity to excel in Western education systems, which have traditionally been homogenous. However, because ISL initiatives are relatively new, few studies have explored the benefits of such programs. To determine the effectiveness of ISL initiatives, it is important to evaluate the impact they have on teacher candidates. The current phenomenological study examines the lived experiences of a group of teacher candidates who participated in an international community service-learning program in Tanzania, East Africa. A series of pre-immersion, immersion, and post-immersion interviews were conducted to determine how participants interpret and attach meaning to their experience and its impact on them personally and professionally. The findings suggest that participating in ISL, such as the Tanzania program, encourages teacher candidates to engage in critical self-reflection and that the life changing experiences gained through an ISL program challenge teacher candidates’ homogenous frame of reference and instil in them the global mindedness required to effectively teach in a multicultural setting. A longitudinal study should further examine the long-term benefits such programs have throughout a teacher candidate’s careers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".