The Curriculum and Community Environmental Restoration Science (STEM + Computer Science) Remote Learning Curriculum Use and Evaluation
Bibliographic record
Abstract
The role of classroom teachers in the development of a well-designed curriculum is paramount. For this reason, teachers were asked to participate in the use and evaluation of a remote learning environmental restoration curriculum. The purpose of the study was to determine whether the participating teachers increased their content knowledge of STEM concepts and content related to the environmental restoration, specifically in terms of New York Harbor and oyster restoration, by participating in a remote learning curriculum pilot. New York City public school teachers of grades 6 through 12 instructed their students in the remote learning computer science curriculum lessons for one semester. A reflective survey was administered to the teachers at the conclusion of the semester and the findings indicated that 89% of the participating teachers experienced an increase in their knowledge of STEM concepts and content related to harbor and oyster restoration. The study was limited by the element of time and the model can be augmented in future iterations by increasing the length of the study to a full year of school and across several grade levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".