(Re-) Mapping the System: Toward Dialogue-Driven Transformation in the Teaching and Assessment of Writing Authors
Bibliographic record
Abstract
Over three days, 180 junior and senior high school English teachers, postsecondary (university and college) writing instructors, workplace (corporate and small business) writing instructors, and government officials who are responsible for portfolios related to workforce training and literacy met to understand from a broad systems-level perspective how writing development was being supported and assessed in Alberta Canada. Conversations were structured using Dynamic Criteria Mapping (Broad, 2003) as a method for understanding the values, expectations, and contextual factors that shape the system. Participants shared values related to clarity of expression, risk-taking, and ability to motivate audience. These values, however, were enacted differently within school and workplace contexts. Writing as a problem-solving activity was identified as a tool for enhancing knowledge transfer within the system. Alberta’s large-scale writing exams, on the other hand, created barriers to transfer and development by undermining shared values within the system. Recommendations related to curriculum redesign, pedagogical change, assessment reform, and professional development are suggested for enhancing students’ longitudinal development as writers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".