Identifying Lines and Interpreting Vertical Jumps in Eye Tracking Studies of Reading Text and Code

Abstract

Eye tracking studies have shown that reading code, in contradistinction to reading text, includes many vertical jumps. As different lines of code may have quite different functions (e.g., variable definition, flow control, or computation), it is important to accurately identify the lines being read. We design experiments that require a specific line of text to be scrutinized. Using the distribution of gazes around this line, we then calculate how the precision with which we can identify the line being read depends on the font size and spacing. The results indicate that, even after correcting for systematic bias, unnaturally large fonts and spacing may be required for reliable line identification. Interestingly, during the experiments, the participants also repeatedly re-checked their task and if they were looking at the correct line, leading to vertical jumps similar to those observed when reading code. This suggests that observed reading patterns may be “inefficient,” in the sense that participants feel the need to repeat actions beyond the minimal number apparently required for the task. This may have implications regarding the interpretation of reading patterns. In particular, reading does not reflect only the extraction of information from the text or code. Rather, reading patterns may also reflect other types of activities, such as getting a general orientation, and searching for specific locations in the context of performing a particular task.