The Introduction of Open and Free Academic Courses in Conservation of Cultural Heritage in Greece
Bibliographic record
Abstract
The 4-year Bachelor Degree in Conservation-Restoration at the Technological Educational Institute (TEI) of Athens has the difficult task of preparing its students to become professional Conservator-Restorers with knowledge and skills in six specializations of either archaeological (objects) conservation or in conservation works of art. Thus, the academic staff of the Department has the challenge to prepare its students to be qualified in practice and knowledge of many specializations of conservation of Cultural Heritage (CH) within its 4 year program. To meet this demand, many members of the academic staff are participating in a project co-financed by Greece and the European Union (European Social Fund) called ‘Open Academic Courses’ (2013-2015). The goal is to prepare their course material in Greek as freely accessible digital educational content in the form of thirteen PowerPoint lectures with or without video lectures per course offered via the open source eLearning platform ‘Open eClass’ hosted by the TEI of Athens. The paper describes how the courses were prepared, the challenges involved in its preparation, as well as the benefits to the students.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".