A Combined E-Portfolio and Microcredentialing Tool for Engineering Identities and Career Pathways
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 work in progress paper describes a study of student use of e-portfolio and micro-credentialing resources for identifying academic and professional pathways. Micro-credentials and e-portfolios are popular resources for students and engineering industry professionals to demonstrate and verify one's skills and experiences beyond the classroom. A study was conducted at NYU Tandon School of Engineering and found students lack support in identifying and developing their career pathways. This study indicates that a combined e-portfolio and micro-credentialing platform could benefit students by a) providing students with a tool to reflect on and showcase their experiences, b) matching students with upper-class and alumni mentors in career pathways they are interested in, and c) providing them with curated lists of on-
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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 | 0.003 |
| 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 | 0.002 | 0.003 |
| 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