Toward an Evaluation Habit of Mind: Mapping the Journey
Bibliographic record
Abstract
In this article we chronicle a particular professional development initiative designed to promote the acquisition of an evaluation habit of mind within an educational context. After describing the rationale behind this initiative in some detail, we proceed to map the experiences of four of the participants—a principal, a vice principal, a consultant, and a teacher—as they journeyed toward an understanding of evidence-informed decision making. A combination of document analyses and exit interviews allowed us to plot the developmental course by which this evaluation mindset unfolds. Ultimately, the process of using data as evidence for decision making is revealed as one of developing intrinsic motivation by way of personal “meaning making.” The three overarching cognitive themes of preconceptions, frameworks, and reflections given in the National Research Council's synthesized report on how people learn (Donovan, Bransford, & Pellegrino, 2000) are taken as the structural guideposts for the necessary construction of meaning.
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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 | 0.035 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".