Integrating Service-Learning in Korean Language Education: Three Case Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This study reports three pilot implementations of Community-Based Language Learning (CBLL) in advanced Korean language education at the University of Toronto between 2023 and 2025. The cases were designed to examine the feasibility and pedagogical value of integrating community-connected experiential learning into advanced-level curricula. The first case involved a student serving as a teaching assistant (TA) in a credit-bearing high school Korean language course. The second case examined three university students who worked as TAs in an intensive summer Korean language camp for secondary school learners, where they designed instructional materials and led tutorial sessions. The third case explored a remote, project-based collaboration with the Toronto office of the Korea Creative Content Agency (KOCCA), where a student produced a professional research report on the Canadian media industry entirely in Korean. Drawing on instructor observations and student reflection surveys, this study analyzes learning outcomes, affective factors, and implementation challenges across the three cases. Findings indicate that CBLL participation fostered pedagogical language use, intercultural awareness, and professional communication skills, as well as increased learner confidence, while also revealing challenges related to student anxiety, assessment design, and coordination of reciprocal community partnerships. The results demonstrate the feasibility of CBLL in advanced Korean programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it