Knowledge artefacts: Lessons learned and Stories as a means to transfer knowledge amongst cohorts of high school students working on an inquiry‐based project
Bibliographic record
Abstract
Abstract This paper briefly outlines the framework of an ongoing exploratory study on knowledge transfer (KT) between student cohorts working on an inquiry‐based project using knowledge artefacts (KA) mediated by a website. Three successive cohorts of grade 8 students completed a history project which led them to build knowledge about an historical topic of interest. While working on their inquiry‐based project, the students encountered obstacles and gained experiential knowledge of the research process. The researcher recorded the lessons learned and stories told by the students' in the form of knowledge artefacts (KA). The goal of this study is to transfer the experiential knowledge from previous cohorts, coded in the form of KAs and mediated by a website, to new students. The research rationale is based on the assumption that the transfer of experiential knowledge may improve the research processes and results of new students working on a similar project.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".