The twin purposes of Guided Inquiry: Guiding student inquiry and evidencebased practice
Bibliographic record
Abstract
Guided Inquiry is a means by which student enquiry can be facilitated in schools, while simultaneously being the vehicle for evidence-based practice. This paper illustrates this twin purpose in two contexts: An overview discussion of the 2008 NSW Association of Independent Schools’ Project, led by Dr. Todd, and a 2010 Guided Inquiry at Loreto Kirribilli. Both projects are discussed as student practice and as a means of gathering data about student learning using the School Library Impact Measure (SLIM) Toolkit, while highlighting the use of wiki as an organising tool. Lastly, the paper affirms the impact that Guided Inquiry has had on some Sydney schools.
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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 | 0.259 | 0.234 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.113 |
| Scholarly communication | 0.037 | 0.036 |
| Open science | 0.004 | 0.037 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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".