Using Computer Simulation To Teach Technical Aspects Of Construction In A Liberal Arts Setting
Bibliographic record
Abstract
The general education curriculum at Liberal Arts colleges requires students to take courses in history, literature, civilization, social sciences, sciences, and cultural diversity.These courses comprise almost a third of the entire curriculum.All students, including engineering students, are required to take these courses to fulfill the general education component of their curriculum.In this day and age where technology plays an integral role in people's daily lives, it seems odd that, although engineering students are required to take almost a third of their courses on nonengineering topics, the liberal arts students are not required to take any engineering or technologyoriented courses.Engineering courses are deemed too technical for the non-engineers to take.At such colleges, the freshman-writing course is considered to be a venue to introduce young students to a mature level of analytical reading, thinking, discussion, and writing.A new experiment is being developed to make available to both engineering and non-engineering students a technical module on construction technology.The module is designed to introduce the liberal arts students in particular to highly technical aspects of the construction industry.It aims at allowing students to acquire appreciation for the complicated and carefully coordinated effort associated with the construction of sophisticated structures.Several types of structures and methods of construction techniques will be presented.The role played by different structural components in carrying and resisting expected loads will be discussed in detail.The structures covered in this module are suspension and cable-stayed bridges, towers, domes and shells, sea platforms, dams, tunnels and monuments.Each of these structures has its own special features, and their construction involves certain challenges that must be tackled in a well-planned manner.For non-engineering students, the module intends to make a meaningful contribution to their comprehension of the complicated nature of construction.This will be coupled with assigned technical readings on simple principles of load-supporting structural components.It is hoped that this module will serve as an eye opener for those who have never had any exposure to the building industry.It is also anticipated that the technical content planned for this course will help nonengineering students achieve a reasonable level of understanding of what could be a life-long useful knowledge.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".