Elements, Principles, and Critical Inquiry for Identity-Centered Designs of Online Environments
Bibliographic record
Abstract
Within higher education, we are in need of learning designs that facilitate and support students in sharing, examining, and refining their own critical identities as learners and professionals. In the past, technology mediated identity work has focused on individual tool use or learning setting. As professional learning designers, we felt that we are in need of designs to explore and support critical identity processes across various learning contexts, medias and tools. Based on our literature review and our own professional practice, we have identified the recurring and intertwining themes of visibility, agency, community, competencies, and narrative. We also present a design framework that encompasses a set of identity-centered design elements and principles, and we offer self-reflective critical questions to aid in design, development, and implementation of online collaborative learning environments. We then apply the framework to two case studies to demonstrate how the elements, principles, and critique can be used to understand and evaluate new and preexisting designs. Environnements, principes et enquête critique pour une conception des environnements en ligne centrée sur l’identité Résumé Dans l’enseignement supérieur existe un besoin de conceptions de l’apprentissage qui facilitent l’éducation et soutiennent les étudiants dans le partage, l’examen et l’affinement de leurs identités en tant qu’apprenants et professionnels, identités définies comme critiques car prises en compte selon une approche de la sociologie critique. Dans le passé, le travail de médiation technologique de l’identité s’est centré sur l’usage individuel d’outil ou le cadre d’apprentissage. Cependant, en tant que professionnels de l’ingénierie pédagogique, nous cherchons à explorer des conceptions qui soutiennent les processus d’identité critique dans différents contextes d’apprentissage, médias et outils. En nous fondant sur une revue de littérature et sur la pratique professionnelle, nous avons identifié différents thèmes qui apparaissent de manière récurrente et sont souvent entrecroisés tels que ceux de visibilité, organisation, communauté, compétences, et récit. L’exploration de ces thèmes s’accompagne d’un modèle d’ingénierie pédagogique englobant un ensemble d’éléments de conception centrée sur l’identité et de principes allant de pair avec un questionnement réflexif critique visant à favoriser la conception, le développement et l’implémentation d’environnements collaboratifs d’apprentissage en ligne. Ce cadre est ensuite appliqué à une étude de cas pour montrer comment les éléments, principes et l’approche critique peuvent être utilisés pour comprendre et évaluer les conceptions nouvelles et préexistantes. Mots-clés : identité, analyse de l’apprenant, ingénierie pédagogique, conception inclusive, identité communautaire, étude de cas
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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 | 0.073 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".