The Difficulties of Learning English: Perceptions and Attitudes in Mexico
Bibliographic record
Abstract
The political, cultural, and economical relationship between the United States and Mexico is becoming more interdependent, and in general, Mexico’s participation in the world economy has increased the spread of English as a Second Language (ESL). English is ubiquitous in Mexico’s everyday life, as opposed to indigenous languages which are mostly hidden. The diffusion of English makes ESL learning mandatory if Mexicans want to aspire to a better social and economic life. Nevertheless, this contextual ‘imposition’ highly influences perceptions and attitudes Mexicans have towards the language. This in turn may create a strong barrier to the whole language learning process. Based on student surveys in two different universities, this paper accents negative perceptions and attitudes towards English language learning, and highlights Mexico’s colonial past and the effects of linguistic imperialism. In the conclusion, it will open the discussion on how these attitudes could be managed in the classroom, and will offer possible directions for future research in intercultural language learning. La relation politique, culturelle et économique entre les États-Unis et le Mexique est de plus en plus interdépendante, et en général, la participation du Mexique sur les marchés internationaux a propagé l’enseignement de l’anglais en tant que langue seconde. L’anglais est une langue omniprésente dans la vie quotidienne du Mexique, bien au-delà des langues autochtones qui sont en général plutôt cachées. Pour qu’un mexicain puisse aspirer à de meilleures possibilités économiques et sociales, l’apprentissage de l’anglais devient indispensable. Cette « imposition » contextuelle influence cependant clairement les perceptions et les attitudes que les mexicains ont envers la langue et crée des obstacles souvent difficiles à surmonter lors de l’apprentissage de cette dernière. Cet article met donc l’accent sur les perceptions et les attitudes négatives envers la langue en se basant sur des sondages d’étudiants dans deux universités différentes. Il cherche à expliquer ce blocage en faisant ressortir le passé colonial du Mexique et l’influence de l’impérialisme linguistique. En conclusion, l’article invitera à discuter sur les différentes façons de gérer ces attitudes au sein d’une salle de classe et proposera quelques recherches futures pour l’apprentissage interculturel des langues.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".