Addressing Cognitive Differences and Gender During Problem Solving
Ivon Arroyo, Beverly P. W Oolf, Carole R. Beal · 2006
Abstract. This research evaluated the impact of supplementing user models with additional data about cognitive features of the student. Supplemental data included individual differences variables such as: developmental stage of the learner (Piagetian), spatial ability, math-facts-retrieval and gender. These differences were applied along with multimedia and customization in two intelligent tutoring systems, one for arithmetic and one for geometry. The research resulted in the general conclusion that enhancing user models with detailed information about cognitive ability led to improved response to instruction. This is especially important to consider for domains for which there are well-established group differences, such as gender differences in mathematics. 1 Customization and Multimedia Improve Learning Both customized teaching and multimedia have been shown to be effective for learning (Lepper et al., 1993; Tversky et al., 2002). Research points to the central role of one-to-one individualized instruction by a peer, parent, teacher, or other more experienced mentor and demonstrates that students learn better when teaching is customized to their learning needs (Greenfield & Lave, 1982; Lepper et al., 1993). Research suggests that novices construct deep knowledge about a domain through interaction with a more knowledgeable expert and one-to-one tutoring provides better learning results than lectures by one-two sigma (Brown et al., 1998; Ericsson et al., 1993; Graesser et