Asynchronous gaze sharing: towards a dynamic help system to support learners during program comprehension

To participate in a society of a rapidly changing world, learning fundamentals of programming is important. However, learning to program is challenging for many novices and reading source code is one major obstacle in this challenge. The primary research objective of my dissertation is developing a help system based on historical and interactive eye tracking data to help novices master program comprehension. Helping novices requires detecting problematic situations while solving programming tasks using a classifier to split novices into successful/unsuccessful participants based on the answers given to program comprehension tasks. One set of features of this classifier is the story reading and execution reading order. The first step in my dissertation is creating a classifier for the reading order problem. The current status of this step is analyzing eye tracking datasets of novices and experts.