Developing and Evaluating Intercultural Competence in MA Curricular: An Outcome-Based Assessment Approach
Bibliographic record
Abstract
This book chapter explores enhancing intercultural competence in the Master of Arts program in communication studies, emphasizing the importance of using an outcome-based assessment approach. Drawing upon the experience of working in an MA program as the academic director and curriculum developer, the author presents a new framework of intercultural competence, aligning with the main domains based on the UNESCO framework. It provides an empirical case of building intercultural competence as an essential learning outcome in an MA of communication study program that comprises of 14 courses, including intercultural learning projects and research papers. It emphasizes an outcome-based assessment approach that incorporates universal design for learning (UDL) to accommodate the diverse and unique learning needs of students with diverse backgrounds in international programs. It offers several practical implications for higher education educators to rethink and embrace the development of intercultural competence in MA curricula.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".