Can experts interpret a map’s content more efficiently? Kristien Ooms 1 , Philippe De Maeyer 1 , Veerle Fack 2 1 Ghent University, Department of Geography Krijgslaan 281, S8, B-9000, Ghent, Belgium 2 Ghent University, Department of Applied Mathematics and Computer Science Krijgslaan 281, S9, B-9000, Ghent, Belgium {Kristien.Ooms, Philippe.DeMaeyer, Veerle.Fack}@UGent.be ABSTRACT This paper describes the statistical comparison of the results from an experiment with a ‘between user’-design. The first group of participants consists out of novices whereas the second group consists out of experts which have experience in map use and have had training in cartography. The same stimuli (twenty screen maps) are presented in a random order to the participants who have to locate a number of labels on the map image. The participants are asked to indicate when they located a name by a button action, resulting in a time measurement. Furthermore, the participant’s eye movements are registered during the whole test. The combined information reveals a same trend in the time intervals needed to locate the subsequent labels in both user groups. However, the experts are significantly faster in locating the names on the map (P  0.010). The recorded eye movements further confirm and explain this finding: the expert’s fixations are significantly shorter (P  0.001) and can consequently have more fixations per second (P  0.001). This means that an expert can interpret the map content more efficiently and can thus search a larger part of the map in the same amount of time. BACKGROUND AND OBJECTIVES The main goal of this research is to improve the quality of maps with a focus on how the information should be presented to the user to allow an efficient interpretation of its content. Therefore, insights are needed in how users perceive the information presented to them, which is in turn related to how map readers store this information internally and thus to their cognitive map (Downs and Stea, 1977; MacEachren, 2004; Montello, 2002; Slocum et al., 2001). Harrower (2007) stated that the current bottleneck for creating acceptable animated maps is no longer caused by the hardware, software or data, but by the limited visual and cognitive processing capabilities of the map user. In his article, Harrower (2007) also describes the Cognitive Load Theory (CLT) in relation to information processing and learning, which involves the long-term memory and working memory. These terms are crucial to understand how persons, including map users, process and store the information presented to them. The effectiveness or quality of a map can be enhanced by reducing the complexity of the map and remove unnecessary distractions from it. This results in a reduction of the user’s cognitive load (both the intrinsic and extraneous cognitive load), creating extra room for the third type of cognitive load which is associated with learning: the germane cognitive load. Furthermore, ‘map users’ cannot be considered as one homogeneous group: different categories of users and individual user differences have to be taken into account. These differences in gender, age, background knowledge, experiences, etc. may have an influence