Transforming Engineering Education Through Social Capital in Response to Hidden Curriculum
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-to-practice chapter targets prospective and current engineering educators, scholars, and leaders who are interested in learning how hidden curriculum (HC) in engineering can be transformed through social capital. HC represents the unacknowledged and often-hidden lessons or messages that hinder individuals, especially from marginalized populations, from successfully navigating their environments. HC propagates through social networks and relationships, resulting in patterns of behavior that guide how individuals navigate the structures and systems in which they are embedded. This chapter begins with an overview of HC research, discusses the connection to social capital, and introduces an HC pathways model in engineering. We introduce three HC archetypes to describe engineering stakeholders: seekers, bridgers, and agents. Seekers become aware of HC and use social capital to navigate it, bridgers surround themselves with kindred peers to support each other, and agents enact strategies and practices to challenge systems and structures. We provide example of a curriculum that aligns with these archetypes and have specific recommendations based on the US and Canada contexts for different stakeholders in engineering education.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 0.002 |
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