Abstract: The advancement of data science has been prompting the shift of research paradigms in various fields, including psychology, management etc.Investigations on the large empirical datasets have uncovered astonishing regularities and universalities which cannot be revealed through classic methods. This paper aims to explore the fundamental differences in air traffic controllers' information seeking behavior based on the analysis of their eye movements' data. The faceLAB is used to collect eye movements' data recorded from 14 air traffic controllers. Statistical analysis and multifractal detrended fluctuation analysis (MF-DFA) are carried out to investigate the fundamental properties of eye movements. The analytical results show that 1) expert controllers have longer mean fixation duration, less fixation points, shorter mean saccadic duration, and smaller mean saccadic velocity than novices; 2) Controllers' fixation time series, saccadic duration time series, and saccadic amplitude time series, allexhibit multifractal characteristics, and multifractal singularity spectrum demonstrates that there are stronger fluctuations in novices' fixation activities. Our workindicates thatcontroller's information seeking dynamics are different.Work experience does have a significant impact on controllers' behavior.