Last Generation Solar Cells in Outer Space: A STEM Outreach Project with Middle and High School Students in Colombia
Bibliographic record
Abstract
As part of an unprecedented collaborative outreach effort, we implemented an innovative STEM outreach project, where more than 80 middle and high school students from different traditionally underrepresented school districts in Colombia -with no previous knowledge on material science or photovoltaics- created Last Generation Solar Cells (LGSCs) that were part of several suborbital spaceflight missions. As a result, the students were able to contrast visual and instrumental data obtained from the solar cells and modules that were launched to space with similar samples that remained on earth to measure the degradation that occurs during spaceflight conditions. At the same time, the students that participated were able to cultivate their curiosity, strengthen their scientific skills and increase their interest in pursuing careers in STEM fields. These experiences were possible thanks to an extraordinary collaborative network between public and private entities and the use of project-based education as a powerful driver of development, especially for low-to-middle-income countries, such as Colombia. Here, we share our methodology for constructing photovoltaic devices in rural settings, and we show the progression and impact of this novel scientific outreach project.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".