The Intercultural Competence in Colombian University Teachers - Analysis of a Questionnaire
Bibliographic record
Abstract
The promotion of Intercultural Competence (IC) in English Teaching has been an area of extensive study and advocacy at a global level; however, in the Colombian context, this initiative is in its first stages. This article reports results from a first phase of a mixed research study carried out within the framework of the Doctorate in Education at Universidad Autónoma de Madrid, which aims to explore and identify the intercultural profile of a group of English professors working at eight public universities in Colombia. In the first stage, a quantitative survey study was developed, based on the results of a questionnaire that was answered anonymously and voluntarily by 70 English teachers. After examining the questionnaire, one of the most interesting results was the significant difference between the beliefs of professors with and without postgraduate studies. This mirrors the fact that a high number of these educators understand promotion of intercultural competence merely as content transmission, ignoring the development of skills and attitudes. Whatsmore, it is evident that a large percentage of these professors filter cultural topics for the class and approach them in a personal and anecdotal way. On the other hand, there is a marked concern amongst the population about the need for promoting cultural relativism in students, both in order to recognize their own identity and accept otherness.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".