Metacognitive engagement during field‐trip experiences: A case study of students in an amusement park physics program
Bibliographic record
Abstract
Abstract This article reports on a study that investigated students' metacognitive engagement in both out‐of‐school and classroom settings, as they participated in an amusement park physics program. Students from two schools that participated in the program worked in groups to collectively solve novel physics problems that engaged their individual metacognition. Their conversations and behavioral dispositions during problem‐solving were digitally audio‐recorded on devices that they wore or placed on the tables where groups worked on the assigned physics problems. The students also maintained reflection journals on the strategies they employed to manage their own understanding as well as learning processes. Prior to the amusement park physics discourse, the students completed a specially developed questionnaire instrument. This provided signposts of the students' metacognitive engagement during group problem‐solving at the park and subsequent related physics learning tasks back in the classroom. This data, added to field notes arising from observations, and formal and informal interviews during post‐visit learning activities provided the data corpus on the students' metacognitive engagement. Analysis of this data revealed three types of metacognitive engagement during group learning tasks: collaborative and consensus‐seeking, highly argumentative, and eclectic, resulting from high levels of dissonance. In both cases, evidence of individual students' deeper understandings, which manifested through students' cognitive and social behaviors, demonstrated the invocation of metacognition to varying degrees. The novel physics problems tackled by the students created situations where discrepancies between their prior knowledge and the direct experiences enabled them to explicate their thinking through dispositions of behavior. © 2008 Wiley Periodicals, Inc. J Res Sci Teach 46: 265–288, 2009
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| 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".