  In programming education, it makes a difference whether you are dealing with
beginners or advanced students. As our future students will become even more
tech-savvy, it is necessary to assess programming skills appropriately and
quickly to protect them from boredom and optimally support the learning
process. In this work, we advocate for the use of slice-based cohesion metrics
to assess the process of program construction in a learning analytics setting.
We argue that semantically related parts during program construction are an
essential part of programming skills. Therefore, we propose using cohesion
metrics on the level of variables to identify programmers' trains of thought
based on the cohesion of semantically related parts during program
construction.

Software Engineering