The Impact of the 5E Teaching Model on Changes in Neuroscience, Drug Addiction, and Research Methods Knowledge of Science Teachers Attending California’s ARISE Professional Development Workshops
Bibliographic record
Abstract
<p>This study examined how science teachers’ knowledge of research methods, neuroscience and drug addiction changed through their participation in a 5-day summer science institute. The data for this study evolved from a four-year NIH funded science education project called Addiction Research and Investigation for Science Educators (ARISE). Findings were based on pre- and post-test evaluation data from three annual cohorts in June 2010, 2011 and 2012. Researchers found significant improvement in teacher knowledge overall and on all subscales. Teachers with lower pre-test scores showed the greatest gain in post-test scores. What made this in-service unique was that the 5E pedagogical model was used to teach the teachers and demonstrate 5E instruction in the science classroom. Through the use of the 5E teaching method, we found that teachers in our cohorts with the least skill had higher rates of gain. A strategy that has been used extensively to teach science to children, this model moves away from didactic methods of in-service pedagogy. These findings suggest that the 5E model could be an effective way to teach teachers as well as students, particularly new and or less skilled teachers, who often tend to have high numbers of English Learner (EL) students in their classes.</p>
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".