New forms of deep learning on the web: Meeting the challenge of cognitive load in conditions of unfettered exploration in online multimedia environments

We claim that the Web has the potential to be a quintessential multimedia environment for complex learning, particularly in ill-structured domains. This chapter explores the cognitive load considerations associated with several aspects of deep and extended learning on the Web. We also propose the need for a reconceptualization of Cognitive Load Theory for comprehension and learning in more ill-structured conceptual arenas. This reconceptualization emphasizes the need for learning approaches that promote flexible knowledge assembly through processes of organic, reciprocal, and deep Web learning. IntroductIon The Web has the potential to become a quintessential multimedia learning environment. Both formal and informal learners are increasingly turning to the search engine as their primary source of information. For example, college students regularly use the Internet and commercial search engines (e.g., Google) before, or in lieu of, local library resources (Griffiths & Brophy, 2005; Jones, 2002; Thompson, 2003; Van Scoyoc, 2006). At the same time, the content provided to them on the Web is presented in multimedia form, often comprising various combinations of text, data, pictures, animation, audio, and video, of differing levels of interactivity. These DOI: 10.4018/978-1-60566-158-2.ch008