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I am trying to analyse a Serious Game for students learning.

In one of the game levels, There are multiple positions like Player Position (x, y, z), enemy position (x, y, z), Player shot at position (x, y, z). Other features like items acquired,

How do I use these for analysis, for e.g. to categorize some students as "more-exploring" than others.

I am sorry if the question is not clear. But I am just confused with the project.

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Either do unsupervised learning with something like k-means clustering or DBScan where you attempt to segment students into groups and see if you can discern any insights based on the cluster generated or pick a threshold for certain categories, create a class column and label each student, and do a classification model.

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  • $\begingroup$ okay, thanks a lot. I will try to do the k-means clustering and DBScan and see. Do you mean to label each student manually by "create a class column and label each student" ? $\endgroup$ Feb 6 '20 at 13:05
  • $\begingroup$ yes, that is how you create a supervised dataset $\endgroup$
    – Victor Ng
    Feb 6 '20 at 15:16
  • $\begingroup$ if this answer helped you, please accept it $\endgroup$
    – Victor Ng
    Feb 19 '20 at 18:29

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