Data underlying the BSc thesis: The influence of assessment type on students' learning gain in k-means clustering

This study aimed to investigate the influence of assessment types on students' learning gain in k-means clustering. The learning gain was calculated using the difference between the pre- and post-test scores, where 7 was the highest possible score on the tests (normalised gain, adapted from Hake's formula). Data was collected from 20 participants, the complete dataset includes the individual learning gain of participants.