8.2 EcoMUVE: Immersive Authentic Simulations for Learning Ecosystems Science
8.2.2 Blending VR into Features of the MUVE-Based Pond Curriculum
listed above. (For reasons of space, the detailed results of the numerous studies we have conducted are referenced in our citations rather than summarized here.)
8.2.2 Blending VR into Features of the MUVE-Based Pond Curriculum
Moving through the Pond virtual environment offers an opportunity to realize its features (Fig.8.2). Avatars can walk uphill to the housing development and down along a drainage ditch where water isflowing into the pond; VR potentially pro- vides a way to reinforce students’ perceptions of the topography, which is very important in understanding the dynamics of a watershed.
The map icon displayed in Fig.8.2’s upper-right-hand corner is helpful in navigating through the overall environment. The various toolbars provide options for collecting data and moving through various modalities in the world. Having so many interface icons could be difficult to view in VR and would also likely undercut a sense of presence; a VR interface that, as desired, reveals and conceals these activity options would be necessary.
Virtual agents (for instance, a park ranger, a local dog walker, and a landscaper) offer pieces of information (Fig.8.3). Physical artifacts, such as a bag of fertilizer, also provide valuable data.
The interface for providing substantial amounts of information—and for dis- playing the chat shown in Fig.8.2—is based on large dialogue boxes, which in VR would be distracting and possibly difficult to read. Finding ways in VR to com- municate this information requires alternative interface modalities, such as audio communication, as well as simultaneous storage of complex information for later perusal. In our EcoXPT extension of EcoMUVE, for example, we use a team-notebook that enables easily sharing information about the pond with related comments. Gardner’s chapter provides additional illustrations of immersive com- munication tools, and Kraemer’s chapter discusses the importance of collaboration in learning.
Linked visual representations reinforce abstract concepts (Kamarainen, Metcalf, Grotzer, & Dede, 2015); students can measure pond turbidity and link the mea- surements to their experiences by seeing how murky the water looks on different days (Fig.8.4). Using a“submarine”tool, they can also shrink to microscope size to see organisms within the pond that are invisible at normal scale (Fig.8.5).
Slater’s chapter discusses the value this type of virtual embodiment provides.
Fig. 8.2 Students can collect water, weather, and population data, as well as chat with members of their research team
The submarine tool is implemented so that students can travel directly up and down in the pond, to observe organisms at various depths, and can turn in a circle at any vantage point—but cannot navigate immersively into the water. While this experience is currently implemented in 2-D (looking through a submarine window), Fig. 8.3 Talking to Manny and observing the bags of fertilizer
Fig. 8.4 Visual changes in turbidity of the pond on different days
reimplementing in VR would reduce the number of times students switch interface-modalities.
Students measure environmental variables to collaboratively complete a Data Table that numerically reveals changes over time (Fig.8.6); they can then display longitudinal graphs showing correlations among the data they have collected (Fig.8.7). These are easier to view and to manipulate through a monitor-based interface, and VR offers no interpretive advantage.
Fig. 8.5 The submarine tool allows students to see and identify microscopic organisms
Fig. 8.6 The data table guides students in what to measure over time
Based on entries in the Field Guide (Fig.8.8) from organisms they have found, students can also construct a Food Web to show the flow of energy through the ecosystem (Fig.8.9). In addition, they can view an Atom Tracker feature to show the flow of matter over time (Fig.8.10). Both of these dynamics, not apparent through sensory information, are important in understanding the causality of ecosystems.
The Food Web tool is implemented outside of the virtual ecosystem, and is easier to use without VR, since no immersion is involved. Both the Field Guide and Fig. 8.7 Graphs display correlations in how variables change over time
Fig. 8.8 Thefield guide provides information on organisms studentsfind
the Atom Tracker display complex visual and alphanumeric information not easily processed at the current image resolutions possible in VR. Since leaving VR would disrupt theflow of activity and interpretation, the gist of this information can be communicated via audio descriptions, as well as simultaneous storage of these artifacts for later viewing in detail.
Students can use six interactive learning quests (Fig.8.11), implemented outside the virtual world, to learn more about content related to pond dynamics (Chlorophyll a, Turbidity, pH, Nitrates and Phosphates, Dissolved Oxygen, and Bacteria). There is no educational advantage from monitor-based viewing to porting these to VR.
The Pond curriculum uses a“jigsaw”pedagogy; students work in teams of four (Table8.1) and are given roles (e.g., botanist, microscopic specialist).
Each student then performs data collection specific to his or her role in the virtual pond ecosystem, sharing this data with teammates within the immersive interface via tables and graphs. (As discussed later, collaboration in world is pos- sible in the VR version only if it is implemented via a server.) Each team works collaboratively to analyze the combined data and understand the ecosystem inter- relationships. The curriculum culminates in each team creating an evidence-based concept map representing their understanding of the causal relationships in ecosystem and presenting it to the class (Fig.8.12).
A video showing the“look and feel”of EcoMUVE is available athttp://ecolearn.
gse.harvard.edu/ecoMUVE/video.php.
Overall, the curriculum offers complementary opportunities for observational field-work and interpretive lab-work. This is an example of the rich activities Fig. 8.9 Students develop a food web for the pond ecosystem to show energyflows
Fig. 8.10 An oxygen molecule describes a stage of its journey through the ecosystem
Fig. 8.11 Screenshot from interactive learning quest for chlorophyll
Klopfer describes in his chapter. As a general design principle, VR is not necessary and often cumbersome for data-based lab-work and related scientific briefings (e.g., the Field Guide, Atom Tracker, Learning Quests, and Food Web and Concept Mapping tools), but can selectively enhance the observationalfield-work. Creating a link from what is collected in thefield (immersed in the virtual world) to what is interpretable in the lab (face-to-face interactions using monitor-based resources) is important. In-world, students could use a Notebook tool to store observations (e.g., Table 8.1 Students work in teams of four with complementary data collection roles
Naturalist Microscopic
specialist
Water chemist Private investigator Collect population
data for the pond organisms on different days:
largemouth bass, bluegill, minnows, and great blue herons
Collect population data for the microscopic organisms in the pond on different days: bacteria, bluegreen algae, and green algae
Collect water measurement data on different days:
water temperature, dissolved oxygen, phosphates, nitrates, turbidity, pH, and Chlorophyll a
Observe the weather on different days;
collect
measurements of air temperature, cloud cover, and wind speed
Use thefield guide to learn about the differentfish species
Use thefield guide to learn about the bluegreen algae, green algae and bacteria
Review your notes from the learning quests on chlorophyll, turbidity, pH, nitrates and phosphates, and dissolved oxygen
Talk to the landscaper, golf course manager, utility worker, ranger, birdwatcher, and other people near the pond Use the graphs to
look at thefish population data.
How did each population change over time? Write down your ideas about why
Use the graphs to look at the algae population data.
How did it change over time. Write down your ideas about why
Use the graphs to look at each of the measurements you collected. Describe in words how each measurement changes over time
Write down observations about the pond and surrounding area.
Take notes about changes you observed over time Use the graphs to
look at the heron population data.
How it change over time? Write down your ideas about why
Use the graphs to look at the bacteria population data.
How did it change over time. Write down your ideas about why
Write down any ideas about why the water measurements might have changed, and how the changes might relate to other things happening around the pond
Use the graphs to look at weather data.
How do air temperature, cloud cover, and wind speed change over time? Write down your ideas about why
Use the atom tracker tofind out what happens to the oxygen atom, the carbon atom, and the phosphorus atom on different days
Work together to create a concept map that represents the causal relationships of the pond ecosystem based on the whole team’s observations
images captured of phenomena; interactions with in-world characters; information from the data-table, Atom Tracker, and Field Guide) for later interpretation.
A teachers’ guide is available for helping students learn via the EcoMUVE curriculum, including an overview of the ecosystems content, causal understanding goals, pedagogical methods, technical information and a detailed day-by-day lesson plan (Metcalf, Kamarainen, Tutwiler, Grotzer, & Dede, 2013). This would be modified to highlight the types of learning opportunities VR makes uniquely available.