Analysis of Learning Outcomes of a Baccalaureate Degree Program in Construction Management
Bibliographic record
Abstract
This paper presents an analysis of the learning outcomes of a four-year baccalaureate degree program in construction management. The learning outcomes usually contain an action verb, a statement of the content to be learned and a description of the context of the learning. A textual analysis is performed to assess the distribution and frequency of occurrence of action verbs and to find most frequently occurring key words in the courses. The action verbs used in the learning outcome statements are tabulated in the schema of a revised Bloom’s taxonomy. The analysis shows that although the action verbs can describe different cognition levels of the learners as they progress from 1st year to 4th year, the frequency of occurrence and distribution of the action verbs are not sufficient descriptors of the depth and breadth of the content covered. The analysis presents an approach that can be used to map learning outcomes of different courses and their correspondence with general learning outcomes of the program and to compare and standardize programs in construction management. The level of cognition and the content of cognition both are equally important when mapping courses within a program or using learning outcomes in benchmarking and standardizing two different programs.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".