Beyond Cultural Responsiveness: Elevating African American STEM Education through African-Centered Models
Bibliographic record
Abstract
Researchers posit that the way science, technology, engineering, and mathematics (STEM) are taught to African Americans contributes to their underrepresentation in the STEM fields. STEM educators are increasingly utilizing culturally relevant pedagogy, culturally responsive teaching strategies, and culturally sustaining pedagogy to engage the African American STEM learner. However, these techniques are limited in addressing the holistic development, healing, and needs of African people.[1] This essay advocates for the use and study of a new educational model titled African-centered STEM education (ACSE). The authors contend that this model is effective for African American STEM learners and African people and benefits society as a whole. This essay includes an overview of the culturally relevant pedagogy framework and its variations, an explanation of the ACSE model and its advantages, and descriptions of implementations of the ACSE model and their outcomes. [1]The term “African” denotes all people of African descent..
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".