Collaborative Learning Tools To Foster Inclusive Participation and Sense of Belonging in a Microbiology Outreach Partnership
Bibliographic record
Abstract
For secondary outreach programs to meet the goals of enhancing science education and attracting future scientists from underrepresented populations, we need an inclusive approach that integrates students’ knowledge and experiences in the process of doing science. I present three pedagogical tools designed by developing equitable, inclusive collaboration among microbiologist outreach mentors and high school biology students. These activities aim to foster a sense of belonging in a scientific community and serve as an entry point to the practice of inclusion. Over a one-semester course at an alternative high school, ten secondary students and their scientist mentors met weekly to design and conduct microbiology experiments together. This group of students and scientists participated in structured collaborative learning activities to: i) understand each other’s ideas about science; ii) collectively analyze their research findings; and iii) offer peer feedback. I modified the following three learning tools for use in my secondary science classroom from protocols of the National School Reform Faculty: 1) the Quotes Introduction Activity set the stage for equitable discourse between high school students and scientist mentors, while initiating important conversations about the process of biological research; 2) the Data Analysis Protocol allowed both students and mentors to contribute to the scientific process; and 3) the Feedback Carousel Activity engaged students and scientists alike in reviewing and refining poster presentations. This inclusive engagement in the social aspects of learning science can help students feel a sense of belonging and imagine their futures in the scientific community, key steps towards inclusion. The supportive system of structured feedback in these collaborative learning activities created a safe, inclusive space for secondary students to try on the role of microbiology expert, and for scientist volunteers to practice inclusive mentorship. Drawing from inclusive pedagogical tools in secondary education will help expand our capacity for inclusive science outreach and bring us closer to the goals of improving biology education and attracting future biologists at the university level.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".