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This article uses a dataset of answers to questions to generate studentsimilarity networks. Two similarity functions to determine the weights betweeneach pair of students are used, one that assumes a power-law distribution ofanswers response times, and one that does not. The resulting networks are thenclustered using different community finding algorithms and their resultingmodularity is compared.

Student similarity network clustering -- Does the time it takes for an answer to be selected follow a power-law?