A Pliant-Based Software Tool for Courseware Development
Bibliographic record
Abstract
The increasing importance of e-learning has been a boosting element for the emergence of Internet-based educational tools. As we move into the information age, tremendous efforts are made in the development of new information and communication technologies for educational purposes. The ultimate goal is to facilitate e-learning methodologies and acquisition. The chapter’s contribution is in the area of open source software for technology-enhanced learning. First, we report on the capabilities of Pliant, a novel software framework for Web-based courseware development. Pliant’ design features upon which e-learning capabilities are built are presented, showing that Pliant has some advantages over existing software, including flexibility, efficiency, and universal usability. A case study of the use of Pliant in the project “Multilanguage Database for Localization” developed at the CUSB School of Translation is presented. Second, we present Academia,3 a Pliant-based courseware development Web portal, and its use in translation studies at CUSB. Request access from your librarian to read this chapter's full text.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.025 |
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".