Online language teaching: The convergence of learning management systems and teaching practices
Notice bibliographique
Résumé
How do different Learning Management System (LMS) components facilitate and/or constrain the activities and pedagogical approaches in fully online language courses? To what extent online language instructors exercise their pedagogical preferences when teaching in LMS environments? These questions were examined from an Educational Technology perspective, considering foreign language learning as a question of learning design. The study employed a survey design with scaled and open-ended questions. Quantitative data were analyzed using non-parametric tests, and qualitative data were analyzed using an open coding procedure. The participants were 97 university and college second-language instructors located in Canada and the United States, who were currently teaching or had taught credit-bearing online courses. Results showed that online language instructors do not make frequent use of synchronous or communicative LMS tools (chat rooms, whiteboards, multimedia rooms; peer review, whiteboards or Wikis); and there is not a clear relation between tools and the type of learning activities they are used for. The study also explored where the type of LMS, the language taught and the years of teaching experience of the instructor were factors that influence the use of LMSs. Although some associations were found, no general conclusions could be drawn. In relation to instructors´ ability to implement their pedagogical preferences when teaching online courses, analysis indicated that the great majority of the participants felt limited by the LMS to some degree, and that limitation was felt more strongly by instructors who had a higher preference for the Constructivist approach. Qualitative analysis suggested that the main advantages of teaching through a LMS were the flexibility and convenience that the online medium provides to students, and that it is a good medium to promote a student-centered type of learning. The major limitations centered on the lack of physical contact, the difficulty to organize synchronous communications or group-based activities, and the time instructors require to prepare and deliver activities as well as to provide personalized feedback to students.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».