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The Need For Bilingual Mode of Instructional Design for Higher Education: Instructional Strategies

2021· article· en· W3199068973 sur OpenAlexaboutno aff
Sharon Jeevarajathy. E Edmon, N. Hema

Notice bibliographique

RevueSPAST Abstracts · 2021
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueSecond Language Learning and Teaching
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFirst languageMathematics educationSpace (punctuation)PedagogyPsychologyComputer scienceSociologyLinguistics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

THE NEED FOR A BILINGUAL MODE OF INSTRUCTIONAL DESIGN FOR HIGHER EDUCATION In India, English has been in the academic and educational domain for almost two centuries but still English language skills are not effectively used among the educated masses. Especially students from economically and socially backward communities, students who did their schooling in mother tongue and native language struggle to learn and be competent in English in spite of getting systematically exposed to the language for more than a decade. As a result many fail to be globally competent in evading through the opportunities. Their knowledge never gets materialized and their skills never get utilized. This is because the demanding needs of the vast majority of the student community are different from what is being taught to them. They do not serve as a bridge between the educational space and the world of opportunities.  Students who have external sources of learning English get what they need but students whose only way of acquiring English language through classroom scenarios struggle miserably because their needs are not met. In spite of the growing demands for learning English language, the learners approach towards English language learning is not positive. This is mainly because the L2 classrooms are not conducive and inclusive enough to intrinsically motivate students. The traditional influence of completely immersing the students in the target language is still prominent among the teaching community even in the Post Method Era. This alienates the L1 speakers from the L2 classrooms. Vigorous trainings and drillings in the target language yield hardly any practical language skills. As the students do not have any point of reference to rely on they lose track of what they learn.  Usage of learners’ native language or the mother tongue is vehemently condemned and with this as the starting point the learners’ develop a growing anxiety and low self-esteem that prevents them from successfully acquiring the second language. This phenomenon is what Krashen calls as the “additive filter.” The more the additive filter is raised among the learners, less will be their productivity level. This major problem could be avoided to a greater extend if a bilingual mode of instruction is developed for language teaching. As the bilingual instruction makes use of the students’ existing language repertoire, there is an establishment of familiarity. This will first make the students confident and further motivate them to learn the language with purpose. When a bilingual mode of instruction is used the learners will be able to relate the new information to the existing information and expand their knowledge. Providing the relevant instructional material and teaching pedagogy is a very important factor in developing the leaners’ motivation. In spite of the criticism against bilingual teaching, it has still proved to be an effective way to teach second language. Research conducted in Welsh, Canada and other western countries show that bilingual medium of teaching L2 has created a positive impact among learners. After all the ultimate goal is not to make the learners master the language or learn everything about the language but to facilitate them in learning the basic language skills necessary to get through the available opportunities. In a survey conducted among a heterogeneous group of L2 learners at undergraduate level whose native languages were Tamil, Telugu, Malayalam and Urudu, out of 91 respondents 92% of the native speakers have responded that their mother tongue did not stop them from learning the target language. 78% of leaners recorded that using their mother tongue (L1) has helped them learn the target language comfortably. 81% of the learners have felt that the classroom atmosphere was more conducive for interaction if the instructor is bilingual in the classroom. This survey leads to the hypothesis that bilingual mode of teaching could be an effective pedagogical approach in bringing a better language outcome among the learners. 32% of the L2 learners have pointed out that they are scared to speak in the target language. 20% of the learners have felt that they are not able to express themselves and their knowledge effectively because of the inhibitions. This proves the “additive filter hypothesis”. The aim of this paper is to analyse and find appropriate bilingual instructional strategies for these learners by which their additive filter is lowered and motivational factors are increased in learning and producing better English language skills. Bilingual teaching will happen among the peers even if they are not systematically exposed to it. This could be misleading and it might end up in subtractive bilingualism rather than enriching the language repertoire. An appropriate teaching material will stop this from happening. If teaching is designed rightly then language can be acquired easily. This paper will proceed further in conducting a needs analysis in both inductive and deductive methods. Relevant teaching methodologies and theories, instructional design strategies and motivational theories of learning will be considered and applied in creating and analyzing the survey. Based on the analysis of the datas collected and observations made a sustainable and relevant bilingual instructional strategy will be suggested for the learners that will increase their motivation in acquiring L2  and produce immediate results.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0030,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0070,002

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.

Tête enseignante Opus0,044
Tête enseignante GPT0,290
Écart entre enseignants0,246 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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