Raising the Bar for Civil Engineering Education: Systems Thinking Approach
Bibliographic record
Abstract
The civil engineering profession has been undergoing an identity search. With the advent of information technology and the global market, competition from engineering offices elsewhere and from other local professions is unprecedented. Technical engineering knowledge is no longer a guarantee for career success; rather a combination of numerous professional skills is required. The growing unease of civil engineers about their undefined role in the knowledge economy has led many to question civil engineering education. Although there is a push to enhance the humanistic and business aspects of the curriculum, there is a shove in the opposite direction to strengthen the technical content and keep abreast of technical change. Discussion of this socioeconomic problem within the ASCE forum has often used linear deterministic thinking that is characteristic of technical problems. Social and economic systems are usually more complex and harder to understand than technological systems. If we start making new policies to address the problems of the profession based on fuzzy, incomplete, and imprecise mental models, we may end up with counterintuitive results. This paper proposes a systems thinking approach to the reform of civil engineering education based on System Dynamics modeling, a feedback-based object-oriented modeling paradigm. Such a tool can capture the dynamic nature of complex systems and the nonlinear feedback loops that are often responsible for counterintuitive results of policy making.
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.
How this classification was reachedexpand
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 | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".