Bibliographic record
Abstract
This design-based study was the first empirical investigation of a new model of learning and instruction called Knowledge Community and Inquiry (KCI). In KCI, students are engaged as a learning community as they work on scaffolded inquiry activities that target specific science learning objectives. Although community-oriented approaches have been successful at the elementary level, there has been relatively little uptake of such methods at the secondary school level – particularly in science. The pedagogical framework of KCI addresses the challenges of community models by blending established inquiry based approaches with community-oriented pedagogy. This dissertation tested the validity of KCI by designing, implementing, and empirically evaluating a curriculum based on the KCI model. This was achieved through curriculum trials involving two separate cohorts of grade-ten biology students (n = 102; n = 112).\n\nThe first implementation consisted of a two-week physiology lesson that engaged students in co-authoring wiki artifacts about human system diseases, which students then used as a resource for solving medical case studies. The second implementation, an eight-week lesson on Canada's biodiversity, was a deeper application of the model, and focused on students' collaborative processes during the construction of their wiki-based knowledge repository. In both cases, the curriculum was evaluated according to its design, enactment, and learning outputs, as evidenced by students' knowledge artifacts and performance on the final exam. Technology scaffolds ensured that students focused on the physiology and biodiversity science curriculum expectations. Analyses of the data revealed that KCI engaged students in collaborative learning processes that were characteristic of a knowledge community. Additionally, final exam scores demonstrated increased learning performance when compared to those from previous years where students did not participate in KCI. \n\nThe findings from this research provide the first empirical support for KCI, and demonstrate its potential for engaging secondary science students in the kinds of collaborative inquiry processes of authentic knowledge communities. This dissertation provides insight into the conditions necessary for such engagement, and contributes design recommendations for blending knowledge community and inquiry in secondary school science curriculum.
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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 | 0.029 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".