Analítica del aprendizaje en Moodle FAQ

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Here are some common questions about Moodle Learning Analytics. You may also find it helpful to visit the Moodle Learning Analytics Working Group site.

¿Comenzaré a obtener predicciones tan pronto como habilite el modelo?

Static models do not require training, and will begin to deliver insights as soon as they are enabled (and the circumstances that trigger the model occur). Machine-learning based learning analytics models, such as Estudiantes en riesgo de abandonar, must be trained on your site data before they can generate predictions. The Moodle Learning Analytics machine-learning engine needs historical data (previous courses or other activity, depending on the model), so it will need to be enabled on a production site or a copy of your production site. The model training process happens in the background once the model is enabled on your Moodle site. Once the model has been trained, you will start to receive predictions about current courses or other components. See Gestión de analítica for more information on how to manage notifications.

¿Hay alguna manera de exportar e importar datos de modelo entre sitios?

Los datos de entrenamiento del modelo pueden ser exportados desde un sitio y colocados en el directorio de datos del modelo de un sitio nuevo. This consists of a file of calculated target and indicator values for each sample examined by the model, along with some header information. No personally identifying information is included, but one row per sample (e.g. per course enrolment and analysis interval) is included. We are working to collect model data from many sites to construct a training set we can provide with Moodle installations. Please see How to Participate in Learning Analytics Data Collection for more details.

¿Hay alguna manera de exportar e importar entre sitios las configuraciones de un modelo?

¡Nueva característica
en Moodle 3.7!
Yes. Models can be created and tested on one site, and can be exportados with weights and imported to a new site. This data does not reference individual users or courses in any way, and can be safely shared with researchers or other sites. On the new site, a model can be re-trained after import, or the imported model weights can be tested on historical site data to evaluate the accuracy of the model on the new site. We are working to collect model configuration and weighting data from many sites to construct a pre-trained model we can provide with Moodle installations. Please see How to Participate in Learning Analytics Data Collection for more details.

¿Cómo puedo deshabilitar las notificaciones de la Analítica del Aprendizaje de Moodle, o restringirlas a ciertos usuarios, mientras conservo habilitados los modelos para propósitos de prueba?

Notifications go to users with the "analytics:listinsights" capability in the context of the prediction-- what this means for the Estudiantes en riesgo de abandonar model is that notifications go to teachers in each course. What you can do is modify the "Teacher" role (editingteacher) to remove that capability. Currently that capability is also turned on for Managers by default. If you want to restrict the notifications to a few individuals, make a new role with just this capability, and assign that role to the individuals you wish to grant permission to in each context.

¿Qué tan exactas son las predicciones del modelo?

This varies depending on the quality and quantity of site data (including how many activities are in each course and what percentage of the course is conducted online in Moodle). See Uso de analítica: Revisar resultados de evaluación for more details on how to review model accuracy.

¿Cómo puedo crear mis propios modelos de Analítica del Aprendizaje?

New machine learning models can be created by using the Analytics API, by importing an exported model from another site, or by using the ¡Nueva característica
en Moodle 3.7!
new web UI in 3.7. For more information, see Uso de analítica: Crear y editar modelos. (Note: "static" models cannot be created using the web UI at this time.)

Vea también