APRENDIZAJE BASADO EN PROBLEMAS PROBLEM - BASED LEARNING
Bibliographic record
Abstract
From its beginnings, in the Medicine School at McMaster University (Canada), the Problem-Based Learning appears like an innovating educative proposal, that is characterized so that the learning is student centered, promoting significant learning as well as the development of a number of important skills and abilities in the present professional surroundings. The process is developed on the basis of small work groups which go through a cooperative learning process, in order to search for a track to solve an initial complex and challenging problem, proposed by the teacher, with the objective to propitiate the self-learning of the students. The professor becomes a facilitator of the learning process. Although this educative proposal was originated and it was adopted first in the Medicine Schools of different prestigious universities, the reached achievements of the method have motivated its implementation in a great variety of institutions and careers anywhere in the world.
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 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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".