Supporting Discovery-Based Learning within Simulations

This paper begins by presenting an overview of visualization in education, followed by two main theoretical frameworks to guide research: Dual coding theory and mental model theory. These ideas are used to frame design and research questions for educational simulations. Two main areas of simulation research are then reviewed: the use of different feedback representations and challenges faced by learners in discovery learning approaches. Research shows that discovery learning within simulations is very difficult for students, but can be effectively supported with the use of different simulation representations and creative designs to the simulation’s interface. This research suggests that representation matters but is very context sensitive. Over the past 15 years I have studied children and adults using educational simulations based on various pedagogical (e.g. inductive and deductive learning) and philosophical approaches (i.e. constructivist and objectivist). My goal in this short paper is to summarize some of this research and also provide some of the background that frames my research questions. As an instructional technologist, I have been influenced by the use of instruction to shape learning, but as someone who accepts a constructivist orientation to learning, I know that instruction is but one path to learning. When given little or no instructional support, I am interested in the strategies that people use to learn given the opportunities of an interactive simulation. Even more important, I am interested in those times when they run into problems and need help. My goal is not to withhold instruction from them, but to gain a better understanding of when instructional support is unnecessary or, conversely, most needed. The general conclusions I have drawn from this research and experience are not neat and tidy. I am unable to say that simulations are “better” than other learning approaches. One of the most important conclusions is simply that learning with simulations is heavily context-bound. This does not frustrate me, but rather intrigues me. It reminds me that human cognition and motivation are among the most complex phenomenon we can study. As a researcher, it generates curiosity leading to more research. Yet, as an educator, I admit that I grow restless at times when design principles prove elusive. This paper is presented in three sections. First, I present a brief overview of visualization in education. Second, I present two theories relevant to my work: Dual-coding theory, a well-established and studied theory that offers much guidance in deciding when and how to design visualization for educational materials; and mental models, a theory that attempts to model and explain human understanding of complex phenomena. I hope these first two sections give workshop participants some useful visualization background, at least for the design of highly visual educational simulations. Third, I address interactive multimedia, basing most of my discussion on the use of simulations. However, I also consider how attributes of microworlds can influence simulation design. Visualization in Education: A Primer There is a tendency to use armchair methods of deciding when, where, and how to incorporate graphics in instructional and training strategies and materials. This can lead to unexpected results. Research is just beginning to demonstrate conditions under which static and animated graphics are generally effective, as well as those where graphics serve no purpose or, worse, do harm (Levin, Anglin, & Carney, 1987). For example, consider the cultural symbolism of the owl. Many American teachers like to adorn their classrooms with fanciful images of a friendly wise owl to symbolize an educated person. Yet, an owl often represents an evil omen for many Native Americans, leading some students to be alienated by such graphics. All teachers should carefully consider the impact of such innocent graphics on all their students. Like most issues in education, the use of graphics represents a qualitative, not quantitative, issue. It is not simply a question of how many graphics are used that determines their effectiveness.