Using Learning Analytics to Interrogate Learning Theories: An Exploration of How Students Learn to Program
Julie M. Smith · 2022
A variety of approaches have been used in computer science education research; one relatively new addition is the use of very large data sets. This dissertation will use one of these data sets in order to investigate the process by which novice students learn to program. Specifically, an iterative approach will be used to determine which learning theories are (or are not) supported by the data. The focus will be on which patterns of behavior do (or do not) lead a student to learning a programming concept.