Theoretical Foundations and Classroom Strategies for Increasing Students' Cultural Awareness
Bibliographic record
Abstract
This paper presents a three-step approach to increasing cultural competence in undergraduates enrolled in a semester-long course in Global Awareness. Step 1 consisted of the premise that effective educational efforts for this goal must combine a sound theoretical foundation of cultural awareness with a thorough understanding of the developmental characteristics of this age group. Step 2 consisted of a series of intentional, interactive, activities (e.g., discussion, readings, interactive exercises, videos, etc.) that were employed for nine weeks to help students process these theoretical perspectives and connect them to various topics related to identity and cultural competence (e.g., cultural dimensions, identity statuses, TCKs, stereotype threat, etc.). Step 3 involved the culminating high-impact activity of an 8-week virtual exchange program (Soliya Connect) that provided students with the opportunity to meet peers from other countries and discuss cultural competence, current social issues, and world events from various cultural perspectives. Throughout the course, we explicitly focused on strengthening students’ ability to understand, appreciate and interact with people from cultures or belief systems different from their own. We assessed cultural competence at the beginning and at the end of the semester with an American adaptation of the Cultural Competence Self-Assessment Checklist that was initially created with funding from the Canadian government. Results indicated a statistically significant increase in cultural competence from pre-test to post-test assessment. These results support the use of this comprehensive 3-step approach of employing intentional and explicit strategies to increase the cultural competence in undergraduates.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".