Pre-Service Science Teachers’ Scientific Reasoning Competencies: Analysing the Impact of Contributing Factors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Scientific reasoning competencies (SRC) are one part of science teachers’ professional competencies. This study examines the contribution of three factors to the development of pre-service science teachers’ SRC: the amount of science education classes , the amount of science classes and the pre-service science teachers’ age . The factors amount of science education classes and amount of science classes have been operationalised in terms of ECTS credit points. N = 438 pre-service science teachers from six universities in Germany, Chile and Canada voluntarily and anonymously responded to an established multiple-choice instrument for assessing SRC, which has been developed by the authors and is available in German, Spanish and English. Multiple linear regression analyses show that the included factors explain a proportion of about 9% of the pre-service science teachers’ SRC. The factor amount of science classes is the only significant predictor and can be seen as an indicator of learning science content knowledge. These findings support the assumption of science content knowledge being a prerequisite for developing pre-service science teachers’ SRC.
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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 | 0.025 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it