Enhancing learning outcomes by introducing BIM in civil engineering studies – experiences from a university college in Norway
Bibliographic record
Abstract
It is a challenge to introduce building information modeling (BIM), as demanded from the industry, in an already packed curriculum for higher engineering education. There is therefore a need for alternative ways to include BIM in the curriculum, while at the same time strengthening -rather than supplantingthe traditional engineering subjects. The purpose of this study is increased understanding of how BIM can be integrated as part of an engineering curriculum in an efficient way. The study is based on an evaluation of the 'Introduction to Building Professions' course given to all civil engineering students in their first semester of the bachelor's degree programme at Oslo and Akershus University College of Applied Sciences in Norway. Autodesk Revit was used as BIM-based software in the designing of a two-family timber dwelling, a compulsory group project in the course. Data for this paper are collected from multiple sources: a net-based questionnaire, course evaluations, interviews with students and teachers, and assessment of students' project work. Selected factors in Active Learning theories are used as a theoretical lens for analyzing the data in a systematic way. BIM enabled a design and 'virtual construction' process where students held professional roles in a design team, and contributed with their expertise toward a holistic solution. The students reported that the hands-on modeling with BIMbased software led to increased understanding of design parameters, load distribution, and construction detailing, as well as information requirements for collaboration within a design team. We conclude that BIM in higher engineering education can support understanding of professional content, which is the primary learning outcome. Software proficiency is seen as a necessary yet subordinate skill in higher education and should not be graded as a separate task. Use of BIM-based software should, however, be integrated to enhance problem understanding and relevant information processing. This integrated approach can lead to a more widespread implementation of BIM to support active learning in higher education.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".