The end game in <scp>K</scp>uhlthau's <scp>ISP M</scp>odel: Knowledge construction for grade 8 students researching an inquiry‐based history project
Bibliographic record
Abstract
This article reports on a field study of the information behavior of Grade 8 students researching an inquiry‐based class history project. Kuhlthau's 7‐stage Information Search Process (ISP) model forms the conceptual framework for the study. The aim of the study was to define an end game for the ISP model by answering the following question: How do the student participants' feelings, thoughts, and information behavior lead to the construction of new knowledge? Study findings tentatively indicate that knowledge construction results from an iterative process between the student and information, which can be divided into 3 phases. In the first phase, the students formulate questions from their previous knowledge to start knowledge construction; in the second phase, newly found topic information causes students to ask questions; and in the third phase, the students answer the questions asked by this newly found topic information. Based on these results and Kuhlthau's own ISP stage 7 assessment definition of the ISP model end game, we propose a model of knowledge construction inserted as an extra row in the ISP model framework.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".