Exploring the value of a BioBlitz as a biodiversity education tool in a post-secondary environment
Bibliographic record
Abstract
Biodiversity education is widely considered a necessary component of protecting global biodiversity by helping to change harmful attitudes and actions. BioBlitz events, rapid surveys of all living things in a defined area over a set period, are becoming a widely used practice for biodiversity education. The aim of this study was to evaluate the use of a campus BioBlitz as a place-based experiential learning experience for early undergraduate science students by having students work alongside naturalist experts to build skills in species observation and identification using the iNaturalist app. We surveyed students about their perceptions of the BioBlitz experience. Eighty two percent of students agreed that the BioBlitz provided valuable hands-on learning, they valued learning outside of a traditional classroom, and felt they learned new knowledge about species identification. Many students reported a heightened sense of environmental stewardship and a positive sense of place on campus. We conclude with a discussion of the benefits of a campus BioBlitz in overcoming many of the emerging challenges associated with outdoor field-based education.Supplemental data for this article is available online at https://doi.org/10.1080/13504622.2021.1960953 .
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".