A New Learning Model for the Information and Knowledge Society: The Case of the Universitat Oberta de Catalunya (UOC), Spain
Bibliographic record
Abstract
When it was created in 1995, the Universitat Oberta de Catalunya (UOC) served only 200 students and offered two degrees. Today, it has expanded its activities to serve over 20,000 students and 16 official degrees. UOC also offers more than 250 continuing education courses for those wishing to pursue learning opportunities outside of UOC’s official degree programs. As an innovative university, UOC offers a new way of experiencing education, one that is capable of providing answers to an emerging global and universal knowledge society. Today’s rapidly changing world requires revised learning models that allow the widest possible access to knowledge throughout life, in a continuous, comfortable, and simple manner, irrespective of the geographical constraints. Capitalising on the intensive use of new information technologies, UOC is proactively breaking the barriers of space and time by offering an educational model of distance education based on the use of the Internet. Students of UOC’s Virtual Campus now have easy access to a useful and dynamic learning experience wherever they may be. More significantly, each student becomes the centre of a completely personalized educational process. All receive guidance from an accredited teaching team and have access to some of the most innovative didactic resources and services currently available. From the start, UOC was designed to be an exemplar of a new generation of distance education providers capable of creating cooperative interaction not only between students and professors, students and learning materials, but also among students themselves. To support this goal, flexibility, co-operation, personalisation and interactivity are the four pillars of practice upon which UOC’s model is founded. Research is also one of the main objectives UOC has achieved in recent years. Through the creation of the IN3, a research Institute focused on analysing the impact of the Internet on society, the institute is home to a virtual Ph.D. programme, and Edu Lab, which is a laboratory of educational innovation that researches the use of e-learning. The UOC is open to the world, having achieved this objective by maintaining contacts with the principal international knowledge networks. As a result, it is anticipated that the UOC will become an important actor in future e-learning initiatives.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.025 | 0.010 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".