MétaCan
Menu
Retour à la cohorte
Enregistrement W3013762543 · doi:10.21125/inted.2020.1553

ANTICIPATING FUTURE NEEDS IN FRENCH IMMERSION PROGRAMS WHERE NO TEXTBOOKS ARE USED

2020· article· en· W3013762543 sur OpenAlexaboutno aff
Marie J. Myers

Notice bibliographique

RevueINTED proceedings · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueFrench Language Learning Methods
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScrutinyComputer sciencePreparednessMathematics educationChristian ministryClass (philosophy)Consistency (knowledge bases)Action researchGRASPPedagogyPsychologyPolitical scienceArtificial intelligenceProgramming language

Résumé

récupéré en direct d'OpenAlex

Problem:The Ministry of Education of Ontario usually lists authorized textbooks for use in schools in a document called The Trillium List (2019). There is however, a lack of titles for French immersion. This creates a number of issues. It is hard to have consistency within and across programs when teachers do not know what learners covered during the previous year. What is agreed upon, in Ontario second language education, is the adoption of the action-oriented communicative approach as delineated in Council of Europe documents (CEFR).The research:Objectives were1. To identify in the teacher preparation program, preparedness in terms of language proficiency and capability to adapt to future learners’ language use level. In light of such issues, the course outline is based on forecasting needs. Not only is the instructor required to get a good grasp of the student’s capabilities in the course, mostly as regards ability to use the French language, but also figure out at what level future learners will be able to use the language.2. To establish competencies to enact the communicative-action-oriented perspective as mandated by the Ministry (2014).The future teachers were required to establish their own language passports, which were analyzed first. Then, based upon the levels of ability, action-oriented tasks were designed in groups. These came under scrutiny to assess both pedagogical thinking and future possibilities of expansion and adaptation for in-class use during the future school placements.Method:The method used is qualitative as it best allows to scrutinize for individual details and follow-through with observational data collection over time. The researcher was the course instructor and notes were taken in a journal during and after each class meeting. Assignments were also examined and notes taken on them as relevant to the objectives of this research.To establish language ability, the future teachers established their own language passports, which were analyzed first. In addition observational notes were taken during class on language use and as well while the future teachers were preparing language activities for learners at different levels. Then, based upon the levels of ability, and an examination of Ministry Curriculum guidelines (2013, 2014) action-oriented tasks were designed in groups. These came under scrutiny to assess both pedagogical thinking and future possibilities of expansion and adaptation for in-class use during the future teachers’ practicum placements.An analysis of final assignments around the creation of a teaching unit was carried out and these findings will also be reported.Results:Various participants experienced some difficulties with unit development. If fluidity in language use was a limitation, it appears that participant initiative and commitment to work and the seriousness of effort, were more important factors in measuring success. Indeed those who consulted more with the instructor, explored various avenues and one future teacher who even restarted on a new path from the beginning, were more successful.We will present a detailed successful unit of analysis showing positive aspects as well as concerns around decision making and action-orientation in the pedagogical unit developed. References will be made about similar units and those that greatly differ in quality will be expanded upon with suggested pathways for improvement and explanations for the causes of deviations.

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)0,003
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,140
Score d'incertitude au seuil0,279

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,001
Communication savante0,0030,003
Science ouverte0,0010,003
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,037
Tête enseignante GPT0,317
Écart entre enseignants0,280 · 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'étudeQualitatif
Domainenon disponible
GenreEmpirique

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
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueINTED proceedingsMême sujetFrench Language Learning MethodsTravaux en français237 207