Análisis descriptivo de Entornos Personales de Aprendizaje: estudio de caso en Enseñanza Obligatoria
Bibliographic record
Abstract
Existe en la actualidad la necesidad de explicar cómo aprendemos en contextos de educación formal, no formal e informal, de forma autónoma y apoyándonos en los recursos tecnológicos a nuestro alcance. Los Entornos Personales de Aprendizaje (PLE por sus siglas en inglés, Personal Learning Environment) son un constructo teórico en torno al aprendizaje que ha recibido la atención de la comunidad investigadora y educativa durante los últimos años y que ha intentado dar respuesta a esta necesidad. Los estudios de tipo práctico sobre el PLE son menos frecuentes que los de tipo teórico, por lo que es necesario complementar el corpus de investigaciones sobre PLE con trabajos que recojan datos empíricos.
 En esta línea presentamos este estudio de caso, diseñado bajo un enfoque cuantitativo de investigación y en el que llevamos a cabo el análisis descriptivo del PLE de alumnos desde 5.º de Primaria hasta 4.º de ESO de un centro escolar, con el objetivo de utilizar las conclusiones para poder elaborar un plan de actuación y mejora de las estrategias docentes.
 Se utilizó un cuestionario ad hoc y recogimos datos de 188 estudiantes. Las principales conclusiones a las que llegamos son las siguientes: la muestra analizada dice conocer y aplicar por igual todas las dimensiones de su PLE, pero lo hace de forma limitada y superficial; un factor determinante para el éxito en este tipo de proyectos es la cantidad de dispositivos disponibles, y no tanto la tipología de los mismos; la edad de los alumnos de Primaria no es impedimento para trabajar sobre sus propios PLE; los estudiantes se sienten más cómodos trabajando de forma tradicional que de formas más innovadoras; por último, la dimensión sobre la que los alumnos han demostrado tener menos conocimientos es la referente a compartir y comunicarse en red. There is nowadays a need to explain how we learn in formal, non-formal and informal contexts, in autonomous ways and supported by the available technological resources. Personal Learning Environments (PLEs) are a new theoretical construct about learning that has received the attention of both researchers and educators in the last few years and that tries to give an answer to this issue. Applied studies about PLEs are much less frequent than theoretical ones; the PLE research corpus needs to be complemented with a number of works that give some insight on practical examples of PLEs.
 In this field we present this case study, designed following the quantitative approach of investigation and where we show the descriptive analysis of PLEs of students from 5th Grade in Elementary School up to 4th Grade in Secondary School, with the aim to provide the school Administrators with a comprehensive action plan to improve teaching strategies.
 An ad hoc questionnaire was used and we collected data from 188 students. The main conclusions we have reached are the following: the sample analyzed claims to know and apply all the dimensions of their PLE equally, although this is done in a limited and superficial way; a key factor for the success of these kind of projects is the quantity of devices available, and not so much what type these are; age is not a problem for Elementary School students to work on their own PLEs; students feel more comfortable working traditionally rather than in more innovative ways; and last, the dimension related to sharing and communicating online for learning is the least developed one in these students’ PLEs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".