A Study of Cross‐Cultural Adaptation by English‐Speaking Sojourners in Spain
Bibliographic record
Abstract
Abstract: This study investigated 127 British university students who worked as English monitors (i.e., instructors) in an “Enjoy English” program in Spain. This program gives children the opportunity to improve their English skills through a number of recreational activities. We assessed the monitors' attitudes toward Spain and Spanish people, motivation to learn Spanish, adjustment to Spanish culture, and self‐ratings of Spanish proficiency, as well their supervisors' ratings of their personalities and their success as instructors in the program. The monitors were tested at the beginning of the four‐week program and again at the end, whereas the supervisors were tested only at the end of the program. The results demonstrated significant changes in the monitors' attitudes and ratings of proficiency in Spanish over the duration of the program. Moreover, these changes defined four dimensions: Integrativeness, Motivation, Adjustment, and Self‐confidence with Spanish. Relationships were also found between pretest characteristics of the monitors, supervisors' perceptions of the monitors' personalities, and supervisors' ratings of teaching performance. A multiple regression analysis showed that Teaching Performance was predicted significantly by the number of languages spoken by the monitors and supervisors' ratings of their Agreeableness and Extroversion. These results are discussed in terms of the roles of attitude and motivation in second language learning, factors associated with adjustment to a new culture, and characteristics of successful teachers.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".