Using the Multi-Display Teaching System to Lower Cognitive Load

Introduction Teaching materials have diversified from traditional paper and whiteboards into multimedia formats often presented on projection screens. Studies (Lai, 1998; Mayer, 1993, 1997; Mayer & Gallini, 1990; Mayer & Sims, 1994) have shown that integrated multimedia instructional material is beneficial for learning. Similarly, combining text with dynamic multimedia (such as animation or videos) can result in better learning (Chanlin, 1997; Lai, 2000; Poohkay & Szabo, 1995; Rieber, 1990). To explain findings like these, Daft and Lengel (1984, 1986) proposed information richness theory, which indicates that richer communication media convey information more effectively. Liu, Liao, and Pratt (2009) integrated the technology acceptance model with information richness theory and found that the learner's degree of concentration increases as presentation formats become more diverse. These new forms of teaching materials, which integrate text, graphics, video, and audio, have been shown to engage the audience much more effectively than traditional means, promoting reading interest and willingness to learn (Vichuda, Ramamurthy, & Haseman, 2001). However, the often limited display space available for projection devices and software that is not user friendly to operate often result in multimedia instructional material being less effective. Instructional materials must often be split into separate pieces in order to fit into available display space. As multi-monitor displays mature, the corresponding software requires prior limits to be transcended and a more flexible environment for multimedia instructional material design to be constructed. This research is aimed to develop a system that supports the presentation and operation of multimedia instructional materials on multiple screens. With properly designed material, the cognitive load of learners can be effectively lowered through the use of this multi-display teaching system. Theories of cognitive load There are three main types of cognitive load according to previous theoretical work: intrinsic cognitive load, extraneous cognitive load, and germane cognitive load (Gerjets, Scheiter, & Cierniak, 2009; Miller 1956, Sweller, Van Merrienboer, & Paas, 1998). Intrinsic cognitive load involves the difficulties inherent in the information itself (stemming from the complexity or difficulty of or the interaction between the material to be learned) and the learners' degree of expertise (knowledge base or experience) (Sweller et al., 1998). If elements of knowledge are isolated and do not connect with other elements, intrinsic cognitive load will be lower due to this low element interactivity. Conversely, if information is not easily taught on its own and requires complex connections with other elements, learning will require more working memory (a higher intrinsic cognitive load) due to this high element interactivity. Take learning language for instance: intrinsic cognitive load is low when learners simply learn the meanings of vocabulary items that exist in a language (which has low element interactivity). When learning grammar, in contrast, element interactivity increases, because grammar constitutes the connections among vocabulary items and involves interactions in their meaning. Thus, the same teaching materials may make learners with good related-and-basic knowledge feel that the material is simple and incur little intrinsic cognitive load, while others feel that it is hard and incur more. In this way, intrinsic cognitive load is mainly affected by the connections among elements of the learning objective and by the learner's intellectual level. Intrinsic cognitive load is hard to alter by means of an instructional design for the reasons that it is mainly caused by learned objects itself (Kalyuga, 2009; Paas, Tuovinen, Tabbers, & Van Gerven, 2003). Extraneous cognitive load mainly comes from bad material design or low-quality interfaces, which cause learners to consume additional cognitive resources on unrelated information processing during the learning activity (Paas et al. …