Using Design-Based Research to Develop the Learning Outcomes of a Curriculum-Based Environmental Citizen Science Project
Bibliographic record
Abstract
The Intertidal Monitoring Project (IMP) is a local, curriculum-based citizen science project intentionally designed to support the development of science competencies in elementary students. The focus of the IMP is the Research Days, where students follow an established scientific protocol to collect monitoring data on an introduced species of clam in British Columbia, Canada. The IMP represents a unique program to study because the school district funds transportation and programming costs so that all grade five students can engage in authentic place-based scientific research. A design-based research (DBR) approach was used to develop and refine the IMP activities between 2014 and 2023. This research is focused on a DBR Evaluation/Reflection phase that qualitatively assessed learning outcomes during the beta testing of a supplementary classroom activity. Student- and teacher-generated data were collected to understand the process of a class “coming to know” science and its community of practice during the IMP activities. This included student learning artefacts and a teacher interview. The findings show that participation in IMP activities: i) fostered the development of science competencies in a grade five learning community; ii) did not promote science identities; and indicated that iii) the Nature of Science (NOS) required more explicit instruction. Student-teacher-scientist partnerships (STSPs) emerged as a critical design element of curriculum-based citizen science.
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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 | 0.105 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".