Desarrollo y evaluación de la competencia gestión de la información en titulaciones técnicas: estudio de casos
Bibliographic record
Abstract
[SPA]Hoy en día ya no es suficiente contar con las habilidades básicas de alfabetización que teníamos antes, como saber leer o escribir. Hoy incluso no basta con saber utilizar el ordenador, el teléfono u otros medios de comunicación. Se hace necesario estar alfabetizado informacionalmente (ALFIN). Esto implica no solo saber que la información existe, sino saber como encontrarla, como utilizarla, como manipularla, como sacar provecho de ella. Así se manifestaba en 2003 Horton especialista en derecho al acceso a la información pública. Un estudiante o un profesor son alfabetos informacionales porque saben cuando y porqué necesitan información, dónde encontrarla y como valorarla, utilizarla y comunicarla de manera ética. En este trabajo se presenta el estudio de tres casos llevados a cabo con estudiantes de diversas escuelas de ingeniería en la Universidad Politécnica de Cartagena. En ellos se muestra un procedimiento sencillo para incluir en la metodología docente de cualquier área de conocimiento la formación en gestión de la información, esto es, en el acceso, recuperación, análisis, evaluación y uso de la información. Asimismo se presenta una rúbrica que permite evaluar los logros adquiridos por los estudiantes que no son sino una forma de evaluar dicha habilidad. [ENG]Nowadays, the ability to read or write is not considered anymore as a basic standard for literacy. Neither the capability to use a computer, a telephone or any other communication device is enough in a professional context. Conversely, the informational literacy has become a professional skill of utmost importance. This means that the graduate must know not only that a certain information exists, but also it's necessary to know how to find it, use it, manipulate it and get benefit from it. A student or a lecturer are skilled on informational literacy when they identify why they do need the information, and they can find it, value, use and communicate it in an ethical manner. In this work, tree different classroom methodologies employed in several Departments and Technical University of Cartagena (UPCT) are presented. The activities to develop the information literacy of the students are thoroughly explained. A rubric for the evaluation of this competency is presented.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".