Teaching English: a transition from a monolithic to a pluricentric approach
Notice bibliographique
Résumé
English language teaching (ELT) has evolved significantly over the past century. In the early 20th century, the dominant model of language teaching was based on a monolithic approach, where the focus was primarily on a single, standardized version of the language. This approach assumed that a uniform language was essential for effective communication and international understanding (Crystal, 2003; Richards & Rodgers, 2014). The methodology was largely rooted in structuralist theories of language and was heavily influenced by the direct method of language teaching, which emphasized speaking and listening over grammar or translation (Richards & Rodgers, 2014). During this period, English teaching focused on producing "native-like" speakers, often modeled after the language standards of the United Kingdom or the United States (Clyne, 1992). However, as the global use of English expanded, particularly with the rise of World Englishes and the increasing use of English in countries outside of the traditional Anglophone world, the monolithic approach began to be questioned. By the late 20th century, scholars and educators began advocating for a more inclusive and flexible approach, one that acknowledged the diverse ways in which English was spoken and used across different regions and cultures (Gerhard, 1992; Xie, 2014). This shift towards embracing the diversity of English use around the world led to the development of the pluricentric approach, which recognizes the legitimacy of multiple English varieties and their role in shaping language learning and communication (Sharifian, 2014). The pluricentric approach to language teaching gained traction with the growing recognition that English, as a global lingua franca, is spoken in many different ways, often influenced by local languages, cultures, and social contexts (Hutz, 2022). As Kachru (1992) argued in his model of the three circles of English, the language cannot be reduced to one standardized form, as it exists in multiple forms that each serve different communicative purposes. This model divides the global spread of English into three concentric circles: the Inner Circle (where English is the native language, such as in the UK, US, and Canada), the Outer Circle (where English is a second language, institutionalized in countries like India, Nigeria, and Singapore), and the Expanding Circle (where English is learned as a foreign language, as in countries like China and Japan). This framework illustrates the shifting perspectives on English, from a single language norm to a pluricentric phenomenon with regional varieties that each have their own validity and significance (Clyne, 1992; Kachru, 1992). The move from a monolithic to a pluricentric approach has far-reaching implications for language teaching. It reflects the growing importance of linguistic diversity in education and acknowledges the need for language learners to engage with English in its various global forms. This article will explore the historical development of English language teaching, analyze the shift from the monolithic to the pluricentric approach, and discuss the pedagogical implications of embracing multiple varieties of English in contemporary ELT.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,015 |
| Communication savante | 0,009 | 0,010 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».