Bridging Spaces: Cross-Cultural Perspectives on Promoting Positive Online Learning Experiences
Bibliographic record
Abstract
The globalization of online courses has transformed online learning into cross-cultural learning spaces. Students from non-English backgrounds are enrolling in credit-bearing courses and must adjust their thinking and writing to adapt to online practices. Online courses have as their aim the construction of knowledge, but students' perceptions of the learning environment and teacher interactions may influence the quality of educational experiences. Limited social presence, delayed feedback, lack of social cues, gender, and cultural dynamics contribute to the complex online social context. This article explores how the globalization of online learning creates unique challenges in online courses in terms of how dominant pedagogical structures based on Western educational practices reinforce ways of knowing, thinking, and writing. Online courses can transform learning through self-reflection, critical thinking, and consciousness-raising when culturally inclusive assignments are designed to link both instructors' and students' lived experiences to classroom learning.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".