Ensayo: El aprendizaje basado en problemas para la intervención de la Enfermería con la persona adulta mayor
Bibliographic record
Abstract
Learning based on problems (LBP) arises from the Case Western Reserve University in the United States and\nMcMaster University in Canada and universities worldwide have integrated it as a methodology of teaching\nand learning in different areas of knowledge and in different races. Therefore, the University of Costa Rica\nthrough the University Teaching Department, developed the course Learning Based on Problems and aimed\nat teachers to develop teaching skills for use. After participating in this course, comes the concern for the\npresent essay, to reflect on the LBP and its application as a teaching technique in the Module Nursing\nIntervention with the older adult, part of the undergraduate course at the University of Costa Rica. LBP is a\nteaching strategy - learning, where knowledge acquisition and development of skills and attitudes are equally\nimportant, designed to facilitate student training and to develop reasoning and critical thinking, enabling it to\ncope with challenges of working life, any areas that are covered in the course.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".