The implications of context upon early reading professional learning.
Bibliographic record
Abstract
Students who are not proficient readers by the end of Grade 3 show higher incidences of high school drop-out, incarceration and teen pregnancy than average to good readers (Torgesen, 2000; Vanderstaay, 2006). Contemporary research findings on student reading achievement and early reading teacher professional learning and knowledge present a juxtaposed picture of the current state of the field of early literacy instruction. A complexivist guided instrumental case study research design with three pairs of early reading teachers from three distinctly different elementary schools within the same school board in an Eastern Canadian province seeks to answer the research question: How do teachers perceive the relationships between their professional learning, their early reading practices and student reading outcomes. Themes from within case analysis reflect the influence of context upon teacher perspectives and particularly how teachers early reading professional learning needs reflects the needs of the students and community they teach in. Cross-case analysis presents themes interweaving the common challenges, preferred ways of learning, and developmental trajectories teachers travel in their early reading professional learning and practice. This research offers contemporary findings for conceptualizing and understanding the role of context on teachers’ early reading professional learning.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".