Promoting Intercultural Competence in a Learning Activity Supported by Virtual Reality Technology
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
Virtual reality (VR) technology makes it possible to create an authentic virtual environment that benefits immersive learning. We designed an intercultural learning activity and applied VR technology to support it. Then, we investigated students’ perceptions of the learning activity, VR technology, and intercultural competence (IC) development during learning. Students from China and Uzbekistan participated in the activity, in which a pragmatic mixed-methods approach was used. The data were collected through student reports, three questionnaires, and interviews, and then analyzed. Three main findings were obtained. First, 13 items related to perception of the learning activity were revealed. When compared with earlier studies, new items were found, including presence, immersion, and authentic cultural experience. Second, the results showed that the participants intended to continue using VR technology, were satisfied with intercultural learning supported by VR technology, and felt that the technology confirmed their expectations. Third, the results showed that intercultural learning supported by VR technology helped facilitate IC development. Based on these results, we discuss implications and offer suggestions for educators and researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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