Helping Students Learn More Expert Framing of Complex Causal Dynamics in Ecosystems Using EcoMUVE

Research suggests that students make a different set of assumptions about the nature of the complex causal dynamics and systemic structure than ecosystems scientists do when reasoning about ecosystems dynamics (e.g. Grotzer & Basca, 2003; Hmelo-Silver, Pfeffer, & Malhotra, 2003). For instance, students are likely to assume that causes and effects behave in an event-like fashion, to act locally and within an abbreviated time span, and to assume obvious and observable causes. Seventh and eighth graders’ (n = 81) causal assumptions were tested early and late in the learning process as they worked with a Multi-user Virtual Environments (MUVE) called Eco-MUVE designed to simulate ecosystems patterns and structural causalities. The affordances designed into the Eco-MUVE enabled students to test their initial causal assumptions and to realize their limited explanatory power for solving an ecological problem posed within the virtual environment. Students’ later reasoning revealed shifts towards more expert framing of ecosystems causal dynamics for some of the ecosystems features such as action at a distance. INTRODUCTION Reasoning about complex causality is critical to learning about ecosystems, but research has demonstrated that students have difficulty conceptualizing ecosystems as systems and thinking about the inherent causal dynamics. Research shows that students often bring a limiting set of assumptions to their causal reasoning about ecosystems concepts (e.g. Grotzer & Basca, 2003; Hmelo-Silver, Pfeffer, & Malhotra, 2003)—ones that differ substantially from those of ecosystems scientists (e.g. Walker & Salt, 2006). A growing body of research in cognitive science underscores students’ tendency to focus on events not steady states or processes (e.g. Ferrari & Chi, 1998), to assume local causes and effects, immediate time frames, to focus on obvious causes in lieu of non-obvious causes when both are available (e.g. Grotzer, 2004). A deep understanding of ecosystems concepts requires the understanding that ecosystems often are scaled such that one can have action at a distance, where impacts are felt far from their causes. There are often long time delays between causes and their effects, and often causes are non-obvious or act in concert with obvious causes. They may be distributed across many actors in space and time or due to natural causes without anthropogenic causes. The causal features inherent to ecosystem processes and relationships make it difficult to understand the dynamics involved in concepts such as energy transfer, matter recycling, decomposition, and the interaction between biotic and abiotic factors. Most middle school science curricula do not address these learning problems. EcoMUVE is a multi-user virtual environment designed to support student learning of complex causality in ecosystems through a middle school ecosystems curriculum. It provides situated learning through immersion in a rich, interactive environment. Prior research with MUVEs for education (Clarke, Ketelhut, Nelson, & Dede, 2006) has found that MUVEs can be an effective platform for science inquiry. Addressing the ecological problems designed within EcoMUVE require students to realize the constraints of their limiting assumptions and to adopt new patterns of thinking about the ecosystem in order to solve them. EcoMUVE has affordances built in to scaffold students in this regard as discussed below. Situating causal concepts in the context of a MUVE-based “real-world” environmental problem and helping them to discover the limits of their initial causal assumptions should help them to shift towards more scientifically valid ways of approaching ecosystem problems. THEORETICAL UNDERPINNINGS Tensions Between Everyday Patterns and Expert Patterns of Causal Reasoning Our every day causal reasoning looks different from that of ecosystems scientists in a number of ways that can impact how deeply and well students learn to perceive and reason about ecosystems dynamics (Grotzer, in press). Each of these tensions pulls against more expert reasoning. Obvious vs. Non-Obvious Causes: Significant research has investigated how learners of different ages attend to obvious versus non-obvious variables. The causal learning research suggests that even very young children will search for a non-obvious cause when there is no obvious cause available (e.g. Shultz & Sommerville, 2006). Most children pursue a deterministic path and do not allow for causeless effects. However, these studies have focused on lab experiments where their attention is focused and the time frame for detection is constrained. Further, in the study of ecosystems, there may be many candidate obvious causes that are not necessarily the actual cause but that have salience for their ability to draw attention in ways that non-obvious causes are not able. A rich literature on multiple sufficient causes suggests that even adults are unlikely to pursue additional potential causes when a salient obvious possibility exists (See Grotzer, in press for a review.) So the question becomes not one of whether students can detect non-obvious causes when no obvious cause exists, but rather, are they able to look beyond obvious potential causes to continue their search for non-obvious possibilities. The science education research which focuses on more complex and confounded instances of causation reveals the many difficulties that students have when detecting causes that are non-obvious, abstract, or inferred in some respects (e.g. Frederiksen & White, 2000). Spatially Local versus Action at a Distance: Physical contiguity or proximity is one of the factors that we use to assess the existence of causal relationships. Infants are surprised by the notion of action at a distance—the idea that causes and effects can impact each other without touching. Early Piagetian research focused on billiard ball type causality where there was physical contiguity between causes and effects (Piaget, 1929). Spelke and colleagues demonstrated in research using shadows that infants reveal surprise when shadows move in concert with the object that they relate to without touching (Spelke, Phillips & woodward, 1995). By preschool, children do come to accept the notion of action at a distance (Kushnir & Gopnik; Schultz, 1982; Schulz & Gopnik, 2004) These shifts correlate with children’s learning about causal domains beyond the physical to include psychological and social events and with amassing more experience in a world with different causal mechanisms such as clickers and remote controls (Sobel & Buchanan, 2009). However, in all of this research, it appears that the default assumption is to expect contiguity and to overrule it when covariation data suggests the need to, preferring deterministic causes even if there was not contact over probabilistic ones that did (Kushnir & Gopnik, 2007). When the concept of action at a distance is considered in ecosystems science, it is on a very different scale. Rather than focusing on whether there is physical causation or not, the reasoner needs to consider a problem space with a very different set of parameters. Water sheds can extend many, many miles. The boundaries of the problem space can be action at a vast distance. Event-Based versus Process-Oriented Causality: Our everyday notions of causality tend to be event-like (Grotzer, in press). The characterization is fundamental to how many philosophers and causal theorists define causes and effects (Sloman, 2005). However, this characterization departs from the way that the sciences typically construe causal systems. Being able to reason about processes and what are referred to as “pulse” and “press” disturbances to balance and flux over time and are characterized by resilience. Pulse disturbances refer to short-term oscillations where the system undergoes sudden changes but that do not result in significant modifications to the system and press disturbances refer to continuous disturbances that result in more permanent change (Bender, Case, & Gilpin, 1984). Note that these are characterized more by shifts in dynamic than by events. Chi and colleagues (1997; Ferrari & Chi, 1998) have argued that one of the difficulties that students have in learning science is that they often assign the wrong “ontological status” to concepts, for instance, treating processes as event-like. They distinguish between events and equilibration, arguing that events often have distinct actions with a beginning, middle, and an end. These actions are often contingent or causal, and that they unfold in a sequential order. Events are “goal-directed’ and are completed when the goal is achieved. In contrast, equilibration often involves many actions occurring at once. The actions can be random and independent and they have a net effect at a systems level. A continuous dynamic is in play. Multi-user Virtual Environments Dede and colleagues (Dede, 2009) have built and investigated a number of Multi-User Virtual Environments or MUVEs. These are 3-d worlds that offer a simulated immersive experience to students. Each student in the world has an avatar that allows them to move through the world and see through the eyes of. The world can be set up so that it offers affordances that the real world cannot. In this way, the MUVE has the potential to scaffold students towards more expert performance. It also holds greater potential for transfer given the similarities at both the surface and deep structural level between the real world and the simulated world (Goldstone & Sakamoto, 2003). MUVEs are often built upon a problem-based learning platform. Centered on an ill-structured, complex problem, students identify questions involved in solving the problem and gather the information necessary to solve the problem. Unlike other PBL curricular that begin with a problem, EcoMUVE is designed so that an ecological issue arises over time. This is to support students in having an op