The learner-centered design is especially important because WBI programs are used by a diverse population of learners who have far more heterogeneous backgrounds in terms of their background, skills, and needs [Soloway and Pryor 1996; Chen and Macredie 2004]. This type of design argues that the development of an instruction program should be based on the learners’ point of view [Soloway et al. 1996] and should address the needs of learners [Quintana et al. 2000]. Paying attention to learner diversity has been shown to increase student motivation to learn which, in turn, may lead to improved learning performance [Larkin-Hein and Budny 2001]. Therefore, individual differences arguably become an important consideration. A number of learnercentered studies have shown that individual differences have a strong impact on the use of instruction technology [Marchionini 1995]. An analysis of existing pedagogical studies also confirms that the successful usage of instructional technology depends on the technology itself and the learners’ individual characteristics [Chou and Wang 2000]. For these reasons, research into individual differences has mushroomed over the past decade. The examined differences include cognitive styles [Workman 2004; Chen and Macredie 2004], gender differences [Beckwith et al. 2005; Roy and Chi 2003], and prior knowledge [Wang and Dwyer 2004; Mitchell et al. 2005]. Among these differences, cognitive style has been identified as one of the most pertinent factors because it refers to a user’s information processing habits, representing an individual user’s typical mode of perceiving, thinking, remembering, and solving problems [Messick 1976]. It has also been suggested that teachers should assess the cognitive styles of their students in order to design instructional strategies for optimal learning [Lee 1992].