The Community of Inquiry Framework: Future Practical Directions - Shared Metacognition.
Bibliographic record
Abstract
Abstract: Metacognition is a required cognitive ability to achieve deep and meaningful learning that should be viewed from both an individual and social perspective. Recently, the transition from the earliest individualistic models to an acknowledgement of metacognition as socially situated and socially constructed has precipitated the study of metacognition in collaborative learning environments. This metacognitive construct was developed using the Community of Inquiry framework as a theoretical guide and tested applying qualitative research techniques by way of developing a metacognition questionnaire. The results indicate that in order to better understand the structure and dynamics of metacognition in teacher education programs; we must go beyond individual approaches to learning and consider metacognition in terms of complementary self- and co-regulation that integrates individual and shared regulation. This research study examines this shared metacognition framework and the use of digital technologies in the 3rd year of a Canadian Bachelor of Education program. Teacher candidates completed both the Shared Metacognition and Community of Inquiry surveys. The results indicate that a teacher must use digital technologies to intentionally design, facilitate, and direct a collaborative constructive learning environment in order for students to learn how to co-regulate their learning (shared metacognition). Keywords: action research, student engagement, shared metacognition, Community of Inquiry (CoI), mixed method, teaching presence Résumé: La métacognition est une capacité cognitive requise pour réaliser un apprentissage profond et significatif qui doit être considéré à la fois d'un point de vue individuel et social. Récemment, le passage des premiers modèles individualistes à une reconnaissance de la métacognition comme socialement située et socialement construite a amené à étudier la métacognition dans les environnements d'apprentissage collaboratif. Cette construction métacognitive a été développée en utilisant le cadre de la communauté d'enquête comme guide théorique et testée en appliquant des techniques de recherche qualitative en développant un questionnaire sur la métacognition. Les résultats indiquent que pour mieux comprendre la structure et la dynamique de la métacognition dans les programmes de formation des enseignants, nous devons aller au-delà des approches individuelles de l'apprentissage et considérer la métacognition en termes d'autorégulation complémentaire et de corégulation qui intègre la régulation individuelle et partagée. Cette étude de recherche examine ce cadre de métacognition partagé et l'utilisation des technologies numériques en 3e année d'un programme canadien de baccalauréat en éducation. Les enseignants candidats ont répondu aux sondages sur la métacognition et la communauté d'enquête. Les résultats indiquent qu'un enseignant doit utiliser les technologies numériques pour concevoir, faciliter et diriger intentionnellement un environnement d'apprentissage constructif collaboratif afin que les élèves apprennent à coréguler leur apprentissage (métacognition partagée). Mots clés: engagement étudiant, métacognition partagée, Community of Inquiry (CoI), présence enseignante
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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 | 0.033 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.014 | 0.026 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".