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
In the civil engineering curriculum at California Polytechnic State University, San Luis Obispo, the 421 traffic engineering course in civil engineering (CE) is intended to provide students with details of driver behavior, traffic characteristics, and design considerations for addressing traffic problems. In fall 2008, this class was taught in traditional face-to-face lecture format. On the basis of student feedback and success in achieving learning outcomes, it was determined that the course should be more student centered and that there should be a two-way feedback mechanism between students and instructor throughout the quarter. The course was redesigned and taught in the new hybrid format during the fall 2009 and spring 2010 quarters. This paper discusses how lessons learned from hybrid redesign of courses in other fields can be applied to a traffic engineering course. The CE 421 hybrid format involved reduced face-to-face meeting time and included learner-centered, online activities. The material was front-loaded for the students through PowerPoint presentations with narrations so that they could come prepared for the face-to-face lectures. The online activities also included simulation and surveys, which demonstrated the variation in reaction time of drivers, and videos that demonstrated the level-of-service concept and a new type of traffic control for intersections. After these online demonstrations, students were asked to fill out a survey. The results from these surveys were then discussed in class to achieve the underlying learning outcomes. A set of questions is provided as guidance for instructors who may be considering a similar redesign of their transportation engineering courses.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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