Bibliographic record
Abstract
Asynchronous discussion technologies offer the advantage of providing time for reflection essential for higher order cognitive thinking. In the context of a ten-week graphic design foundations course in the Digital Graphic Design program at Vancouver Community College, this advantage provides an avenue for advancing critical discussion of design work. Garrison, Anderson and Archer’s (2000) Community of Inquiry (COI) model is applied in tandem with the design process to develop a blended approach to the traditional critique. The appropriate alignment of curriculum and faculty and student interactions to the environments best suited is determined. Guiding principles and learning objectives and tasks are developed to support cognitive, social and teaching presences essential to foster critical discourse in asynchronous discussion environments. Les technologies asynchrones de discussion ont l’avantage d’offrir du temps pour la reflexion, laquelle est essentielle a la pensee cognitive d’ordre superieur. Dans le cadre d’un cours de dix semaines sur les fondements du graphisme dans le programme de Digital Graphic Design au Vancouver Community College, cet avantage fournit une voie permettant de faire progresser la discussion critique du travail en graphisme. Le modele de la communaute d’enquete (Community of Inquiry Model - COI) de Garrison, Anderson et Archer (2000) est ici applique en tandem avec le processus de conception afin d’elaborer une approche combinee de la critique traditionnelle. Est ainsi determine l’enlignement approprie vers les environnements les mieux adaptes au curriculum, aux enseignants et aux interactions des etudiants. Des principes directeurs et des objectifs et tâches d’apprentissage sont elabores pour soutenir la presence cognitive, sociale et d’enseignement necessaire a la stimulation d’un discours critique dans le cadre d’environnements asynchrones de discussion.
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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 | 0.023 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.009 |
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".