Minimum entropy collaborative groupings
DISORDER
We have defined a network of dissimilarities that represent a classroom and describe the relations between the students. We have also defined an SBM that is a way of splitting the students into different groups. Since there is a wide variety of possible SBMs that we can use (i.e., students in a classroom can be grouped in several ways), we need a measure in order to determine how heterogeneous the groups are, and we propose the entropy measure. Entropy is a measure that comes from the field of thermodynamics, it can be used to measure the degree of disorder that a state may have in a system of atoms or molecules. In network science, entropy has been used before with SBMs [Our approach is called Minimum Entropy Collaborative Grouping (MECG) because we obtain collaborative groups by minimizing the entropy of the network system. Since we are dealing with a weighted network, we use the approach by Peixoto [Read a list of students containing numerical information about CHAEA or LML learning styles/patterns and gender.Build dissimilarity weighted network.Repeat 100 iterations:
Propose an initial random partition of the students with Compute entropy of this SBM partition.Repeat Switch 2 students from different groups.Compute entropy Accept the change if Check local minimum entropy with global minimum entropy, saving new group partition if new global minimum entropy has been found.Show global minimum entropy group partition.The code is available online [