Internet Based Interactive Construction Management Learning System
Bibliographic record
Abstract
The Del E. Webb School of Construction is currently involved in a three-year project aimed at enhancing the construction management education.The primary undertaking of this project-in its second year-is to incorporate practical content in the construction curricula thus bridging the gap between the classroom and the construction site.Enhancements are being accomplished by developing 1) an Internet-based Interactive Construction Management Learning System (ICMLS) and 2) an advising and mentorship program that will enhance practitioner-involvement.The Interactive Learning System uses interactive and adaptive learning environments to train students in the areas of construction methods, equipment and processes.This system is being developed using multimedia; Internet based computing; Virtual Reality Modeling Language (VRML); databases; and discrete-event simulation.This paper will provide an update on the design, development and implementation of ICMLS.Lessons learned and tools utilized that may be helpful in other branches of engineering and non-engineering fields will be described.The project team envisions that the successful completion of this project will lead to a number of benefits including: 1) improved recruitment, retention, and program completion for the construction management program; 2) "jobready" graduates that can be successfully employed in the construction industry; and 3) enhanced practitioner involvement and construction industry input. Introduction and BackgroundPreparing students for the challenges of managing large construction projects is an important responsibility and a difficult task 15 .The instruction methods used in the majority of construction engineering and management curricula rely, for the most part, on traditional methods such as exposing students to applied science courses.These traditional teaching methods, however, are often not fully adequate in providing students with all the skills necessary to solve the real world problems Page 5.396.1
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.021 |
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".