E-learning infrastructure for software engineering education : steps in ontology modeling for SWEBOK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Guide to the Software Engineering Body of Knowledge (SWEBOK) has been developed to represent an international consensus formed through broad public participation in the review process and is now close to final approval as ISO/IEC TR 19759. This guide constitutes an integrated structuring of a large set of software engineering concepts developed individually over the past forty years from a large number of distinct viewpoints. The absence of a recognized consensus on software engineering terminology has been a challenging task in building the SWEBOK Guide and in achieving this international consensus. This paper presents a first ontological approach to building domain-specific ontologies as a part of the Semantic Web, and shows how it can be used to build the SWEBOK ontology and to increase its internal consistency and clarity. Finally, new ideas on how a SWEBOK ontology can help in developing an e-learning system on software engineering
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it