Does Guided Inquiry enhance learning and metacognition?
Bibliographic record
Abstract

 
 
 Research carried out at Loreto Kirribilli, a Catholic independent secondary school in Sydney, Australia, in 2014 demonstrates that Guided Inquiry scaffolding enhances learning and metacognition. Students undertaking the Historical Investigation in Year 11 develop an interest in an area of Ancient or Modern history, explore it, develop an inquiry question, and answer it in an essay. The Ancient History class was scaffolded by Guided Inquiry curriculum design and support, while the Modern History class conducted their investigation independently. Deep learning was evident in the questions asked and the answers written in the Ancient History essays. There is evidence of a difference in quality in the questions asked and answered by Modern Historians. It would appear that the scaffolding of Guided Inquiry has enhanced learning, while recognizing the effect an excellent teacher has on already high achieving students. Ancient history students also demonstrated a high level of metacognition in their reflections.
 
 
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".