A TALE OF TWO PEDAGOGICAL PERSPECTIVES: A LITERATURE REVIEW OF WRITING PROGRAM ADMINISTRATION WITHIN ENGINEERING PROGRAMS
Bibliographic record
Abstract
Abstract –While communication and writing programs are typically housed in humanities-focused departments, engineering programs often employ full-time writing specialists to teach their students effective communication in engineering-specific contexts. However, bringing together humanities-focused writing instruction within a science-focused engineering program has some inherent complications in administering a program within a program. The challenge of these writing programs is the misunderstanding that can arise between communication faculty and engineering faculty and administration. The opportunities and challenges embedded within communication and writing pedagogy is not always understood by the engineering-educated administrators, nor sold particularly well by the communication faculty. These challenges are made evident when we see that the modern conversation around engineering communication has morphed from convincing a composition audience to broaden their conception of writing for the unique writing needs of their engineering students, to a post-outcomes based world where engineering identity and culture are the center of curricular discussions aimed at fellow engineering educators. While the complete history of writing program administration in engineering education is much longer, this literature review explores key works in the last 25 years to demonstrate themes in current curricular programming challenges in administering writing and communication programs within engineering departments in Canada and the United States.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".