Improving Student Success for Diverse Students Utilizing Competency-Based Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research aims to conduct exploratory research on the myriad issues that traditionally underserved students face in average higher education settings and poses a potential curricula and pedagogical solution. Particularly within the humanities, subjectivity can sometimes be infused into the curricula and pedagogy, and student assessment; and may impact student examination scores and overall success. In assessing student work through competency-based education (CBE), underserved students can inject their own experiences into the learning environment. Such participation potentially yields significant learning experiences for the entire teaching-learning pipeline and everyone involved (student, teacher, and classmates). Essentially, the utilization of CBE can allow traditionally underserved students to experience their education at their own pace. CBE has the potential to more sufficiently tend to the holistic needs of the student as well.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it