Agregación de categorías

Vista general

Este menú nos permito elegir la estrategia de agregación que se utilizará para calcular cada calificación global de los participantes en una Categorías de calificación. Las diferentes opciones se explican nás abajo.

Las calificaciones se convierten primero en valores de porcentaje (intervalo de 0 a 1), después se agregan empleando una de las estrategias de abajo y finalmente se convierten al intervalo de elementos de la categoría asociados (entre la calificación mínima y la máxima.

Importante: Una calificación vacía es simplemente una entrada ausente en el libro de calificaciones y puede significar cosas diferentes. Por ejemplo, puede ser un participante que no ha enviado una tarea, una tarea enviada todavía no calificada por el profesorado, o una calificación eliminada manualmente del libro de calificaciones por el administrador. Se aconseja tener precaución al interpretar estas "calificaciones vacías".

Aggregation strategies

Mean of grades

The sum of all grades divided by the total number of grades.

   A1 70/100, A2 20/80, A3 10/10, category max 100:
   (0.7 + 0.25 + 1.0)/3 = 0.65 --> 65/100

Weighted mean

Each grade item can be given a weight, which is then used in the arithmetic mean aggregation to influence the importance of each item in the overall mean.

   A1 70/100 weight 10, A2 20/80 weight 5, A3 10/10 weight 3, category max 100:
   (0.7*10 + 0.25*5 + 1.0*3)/18 = 0.625 --> 62.5/100

Simple weighted mean

The difference from Weighted mean is that weight is calculated as Maximum grade - Minimum grade for each item. 100 point assignment has weight 100, 10 point assignment has weight 10.

   A1 70/100, A2 20/80, A3 10/10, category max 100:
   (0.7*100 + 0.25*80 + 1.0*10)/190 = 0.526 --> 52.6/100

Mean of grades (with extra credits)

Arithmetic mean with a twist. An old, now unsupported aggregation strategy provided here only for backward compatibility with old activities.

Median of grades

The middle grade (or the mean of the two middle grades) when grades are arranged in order of size. The advantage over the mean is that it is not affected by outliers (grades which are uncommonly far from the mean).

   A1 70/100, A2 20/80, A3 10/10, category max 100:
   0.7 + 0.25 + 1.0 --> 0.25 --> 25/100

Smallest grade

The result is the smallest grade after normalisation. It is usually used in combination with Aggregate only non-empty grades.

   A1 70/100, A2 20/80, A3 10/10, category max 100:
   min(0.7 + 0.25 + 1.0) = 0.25 --> 25/100

Highest grade

The result is the highest grade after normalisation.

   A1 70/100, A2 20/80, A3 10/10, category max 100:
   max(0.7 + 0.25 + 1.0) = 1.0 --> 100/100

Mode of grades

The mode is the grade that occurs the most frequently. It is more often used for non-numerical grades. The advantage over the mean is that it is not affected by outliers (grades which are uncommonly far from the mean). However it loses its meaning once there is more than one most frequently occurring grade (only one is kept), or when all the grades are different from each other.

   A1 70/100, A2 35/50, A3 20/80, A4 10/10, A5 7/10 category max 100:
   mode(0.7; 0.7; 0.25; 1.0; 0.7) = 0.7 --> 70/100

Sum of grades

The sum of all grade values. Scale grades are ignored. This is the only type that does not convert the grades to percentages internally. The Maximum grade of associated category item is calculated automatically as a sum of maximums from all aggregated items.

   A1 70/100, A2 20/80, A3 10/10:
   70 + 20 + 10 = 100/190