The Process of Facilitating Knowledge Acquisition and Retention: An Inquiry into Magnetic Poles with Challenging Questions
Bibliographic record
Abstract
The current research is to give an example to the inquiry-based science teaching implementations for facilitating knowledge acquisition and retention in a short period of time. Thus, the aim of the research is to transfer of acquired knowledge into different situations using sequential inquiry activities, which have challenging questions for inquiry about what the magnetic pole is and how to discover it. The research was designed as a pre-experimental, one-group pre-test/post-test (N=65) with a retention-test. Sequential inquiry-based science activities were applied to provide a series of developmentally appropriate experiences and discussions, which concretely scaffold participant’s ideas of magnetism. According to the results, the participants interpreted the magnets and magnetic poles regarding their functions. The common view of the participants was that a magnetic pole should be at the ends. This view is associated with upper-lower or internal-external surfaces for a ring magnet. Finally, with a sphere magnet, both upper-lower or internal-external surfaces have lost their functions and the inquiry begins with the question “How to find the poles of a magnet?” In that process, students get to engage and feel that they do not know something that they should know.
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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 | 0.027 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".