Co-Constructing a Learner-Centered, Democratic Syllabus with Teacher Candidates: A Poetic Rendering of Students' Meaning Making Experiences.
Bibliographic record
Abstract
Abstract In this arts-based research study, the creative concept of a co-constructed, learner-centered, and democratic syllabus (marino, 1997; Matusov & Marjanovic-Shane, 2017; Ricci, 2012; Richmond, 2016; Shor, 1996) is creatively and critically examined through a poetic inquiry that focuses on its pedagogical significance in one of the Canadian teacher education programs. Specifically, the author aims to understand what this pedagogical significance means to her students-teacher candidates. The research question is: What does this syllabus-making experience mean to teacher candidates? The study reveals that the pedagogical significance of co-constructed syllabus is embodied in students’ changing self-perceptions as the active and critical knowledge creators, rather than the passive and immutable consumers of the provincial curriculum. Specifically, co-construction embodies diverse learning experiences, as the students struggle to understand why they have to co-construct their syllabus and what this pedagogy actually means to them. The study demonstrates that co-construction actively, enthusiastically, passionately, and energetically generates students’ engagement. Also, the co-constructed syllabus has an unstructured structure with multiple entry possibilities for learning. Keywords: democratic teaching, learner-centered syllabus, co-construction, arts-based research
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".