Promoting Science Communication with Children’s Literature as a High-Impact Practice (HIP) Assessment
Bibliographic record
Abstract
To emphasize the importance of public outreach and science communication within STEM, and to foster in students a greater appreciative understanding of the scientific content within their courses, the Science Library Project has students creating children’s books about key course content. At the end of this project, the student writer-publishers are able to display their critical and creative work as they collaborate with local teachers in a networked conversation about science and multimodal communication. This innovative pedagogical approach to assessment is important both inside and outside of the Sciences because it participates in High Impact Practice (HIP) pedagogy to have students invest a significant amount of time and effort over an extended period of time as they participate in frequent, timely, and constructive feedback and, most importantly, have the opportunity to discover the relevance of their learning through real-world applications in the public demonstration of their book projects. This practical paper shares our approach to creating and implementing the Science Library Project that activates written and visual communication modes to motivate Science learners to engage with course concepts in deeper and creative ways.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".