Incorporating Korean Culture in English Language Teaching for Intercultural Communication: Adopting CCA Approach
Bibliographic record
Abstract
This study investigates the impact of integrating Korean culture into the ELT curriculum adopting a critical cultural awareness approach on students' cultural understanding. Furthermore, the study extends its research to examine the extent to which the local cultural understanding in English acquired from the course contributes to enhancing learners’ intercultural communication in global contexts. This nine-month longitudinal study employed a qualitative data approach derived from a mixed-method study involving pre- and post-survey questionnaires from college EFL learners and in-depth qualitative interviews. Overall, the findings have shown that the integration of local culture into the ELT curriculum helped students: (i) to enrich their understanding of local culture and history; (ii) to examine cultural values with critical perspectives; and (iii) to feel empowered and better prepared to engage in intercultural communication. The analysis also points out that students’ self-/national identity was enhanced, and their English communication skills in global contexts were promoted. Some important implications of this study are discussed for teachers who consider teaching local culture by connecting critical cultural awareness approach in foreign language curricula. Considering that there has been little research on teaching local culture in English class to improve intercultural communication in Korean educational contexts, it is recommended that further research should highlight more dynamic intercultural communication cases by providing on-line communication with students in other countries to facilitate intercultural experiences.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".