High School Intervention for Influenza Biology and Epidemics/Pandemics: Impact on Conceptual Understanding among Adolescents
Bibliographic record
Abstract
Understanding real-life issues such as influenza epidemiology may be of particular interest to the development of scientific knowledge and initiation of conceptual changes about viruses and their life cycles for high school students. The goal of this research project was to foster the development of adolescents' conceptual understanding of viruses and influenza biology. Thus, the project included two components: 1) pre- and posttests to determine students' conceptions about influenza biology, epidemics/pandemics, and vaccination; and 2) design an intervention that supports conceptual change to promote improvements in influenza knowledge based on these primary conceptions. Thirty-five female students from a high school biology class participated in a series of instructional activities and pre- and posttest assessments. Results from the pretest indicated that high school students exhibit a limited understanding of concepts related to viruses. Six weeks after an intervention that promoted active learning, results from a posttest showed that conceptions about influenza are more accurately related to the provided scientific knowledge. Although adolescents have nonscientific models to explain influenza biology, we showed that a carefully designed intervention can affect students' knowledge as well as influence the implementation of health education programs in secondary schools.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".