Abstract Individual differences in skill acquisition are influenced by several architectural factors. According to Ackerman’s theory, general intelligence, speed of proceduralization and psycho- motor speed influence different stages of skill acquisition. Ackerman tested this theory by correlating performance on an Air Traffic Controller (ATC) task with tests on specific abili- ties. The present study discusses an ACT-R model of the ATC task in which the relevant abilities can be manipulated directly, providing additional support for the theory. Keywords: Skill acquisition, Air Traffic Control, Individual differences, ACT-R Introduction Skill acquisition is usually characterized as going through three stages: a cognitive stage, an associative stage and an autonomous stage (Fitts, 1964). The three stages can be char- acterized by moving from conscious, slow and error-prone to unconscious, fast and error-free. Anderson (1982) explains these three stages in terms of a transition from declarative knowledge to procedural knowledge. In the cognitive stage knowledge is declarative and needs to be interpreted. Inter- preting knowledge is slow, and may lead to errors if the rele- vant knowledge cannot be retrieved at the right time. Procedural knowledge on the other hand is compiled and therefore fast and free of errors, and can be associated with the autonomous stage. The associate stage is an in-between stage, during which part of the knowledge is declarative and another part compiled. A problem in the study of complex problem solving, espe- cially in a learning context, is the vastness of individual dif- ferences. In order to study the acquisition of complex skills, it is a good research strategy to have a theory of individual differences. From the perspective of the cognitive architec- ture, there are two sources of individual differences: archi- tectural differences and knowledge differences (Taatgen, 1999a). Architectural differences are differences in the cog- nitive architecture itself. In terms of an architecture like ACT-R, architectural differences can be tied to global param- eters. For example, working-memory capacity is tied to the W-parameter in ACT-R, the parameter that controls the amount of spreading activation. Individual differences in working-memory capacity can be explained by estimating a different value of W for each individual (Lovett, Reder & Lebiere, 1997). Differences in knowledge are based on the idea that people have different problem solving strategies. In terms of a cognitive model, this means individualized mod- els have different initial contents of declarative and proce- dural memory. In this paper I will focus on architectural differences. Ack- erman (1988, 1990) identified three sources: general intelli- gence, perceptual speed, and psychomotor abilities. According to Ackerman, each of these three abilities corre- lates with a different stage of skill acquisition. In the cogni- tive stage, general intelligence is the most important aspect, as an adequate representation of the task needs to be formed. In the associative stage, the knowledge compilation process (which Ackerman associates with perceptual speed) will dominate performance, so individual differences in that aspect will become important. In the final autonomous stage, all knowledge is proceduralized, and differences in psycho- motor abilities will be the most important factor. Figure 1 illustrates the general predictions of the theory. Ackerman (1998; 1990) gathered evidence for this theory by correlating learning behavior on a complex task (the Kan- fer-Ackerman Air Traffic Controller task 1 , KA-ATC) with r practice r practice r practice General ability Perceptual Speed Ability Psychomotor Ability Figure 1: Predicted ability-performance correlations accord- ing to Ackerman. (adapted from Ackerman, 1988). A Model of Individual Differences in Learning Air Traffic Control Niels A. Taatgen (niels@ai.rug.nl) Artificial Intelligence, University of Groningen Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands 211 Taatgen, N. (2001). A model of individual differences in learning air traffic control. In E. M. Altmann & A. Cleeremans & C. D. Schunn & W. D. Gray (Eds.), Fourth International Conference on Cognitive Modeling (pp. 211-216). Mahwah, NJ: Lawrence Erlbaum A