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Design Research
at NC State University
Enhancing statistical learning through mixed
reality museum experiences
Academic Research, Interaction Design, Prototyping
Award Winner at the 2022 NC State University
Graduate Research Symposium
Purpose & Overview
The Master of Graphic and Experience Design (MGXD) degree culminates in a yearlong design research project. My project focus stemmed from a long-term interest in how we learn and delight in science and mathematics.
A review of existing literature and materials revealed that some of the best and most engaging ways for students to engage with science and mathematics remain largely undervalued and underexplored. The output of this project is a complete walkthrough of a potential mixed reality informal learning experience, as well as considerations for future research. This project was a winner at the 2022 Graduate Research Symposium at NC State University.
Context
Statistical literacy, or the ability to understand and interpret data, has become increasingly important to navigating our data-driven society. While many efforts have focused on improving formal learning experiences in statistics, research points towards informal learning outside of the classroom as a crucial component of the general public’s understanding of science and mathematics. This presents a rich opportunity to enhance statistical learning for young students through the design of compelling informal learning experiences.
Drawing from the framework for statistics and data science education from the National Council of Teachers of Mathematics, this investigation explores the ways in which a mixed reality museum experience can engage middle school-age learners with the stages of the statistical problem-solving process.
Research
The project began with a full literature review, including relevant theories and precedents to flesh out the problem space. Many problems with statistical numeracy are attributed to “unfavorable methods” of teaching statistics in formal learning environments. The museum is uniquely situated to provide informal learning experiences that are experiment-driven, fluid, and playful.
Design Phase
The design portion of the project consists of four studies, which explore four different stages of the statistical investigative process. Each study from one through three forms one component of the designed museum experience; Study Four will draw from the previous studies to form a complete experience prototype.
Study 1: Exploring data collection in a projection mapped environment
Study One explores how a projection mapped floor can encourage visitors to consider potential statistical variation in the context of water quality in a river system.
Representational styles were a key component of this study. An abstract, waving grid indicates areas within the projected environment with a greater or lesser degree of deviation from the average. As the visitor moves through and interacts with the environment, bright yellow components are used to denote elements for the learner to make use of, experiment with, or to otherwise indicate points of relevance.
Visitors are also provided with a variety of ways to engage with the environment that vary in length and in degree of experimentation. The visitor can passively walk through and observe a magnified view of the water below, or can take a more active approach in collecting samples or manipulating variables physically to see their impact on the scene in real time.
A major focus of this study was how graphical representation could affect the visitor's interpretation and their perception of the affordances and intended uses of objects or graphics. Three-dimensional icons of factors impacting water quality invite visitors to move, touch, and act upon their surroundings (active/experimental); more abstract, graphical components are to instruct or indicate (passive/observational).
The projection mapped farm (above) transitions from an abstract, icon-like yellow to a more natural coloration when it is activated and begins to act upon the environment. The storyboard above demonstrates its potential use by a visitor to experiment with how manipulating variables can affect results. The result of this study was a variety of different storyboards representing different ways for visitors to act within the floor environment.
Study 2.1: Diving into data with interactive touch tables
Study Two explores the next phase of the experience, in which a visitor takes a water quality sample away from the floor area to further explore the data. This stage of the statistical investigative process involves understanding and explaining sources of variability in the data; what variables contributed to the distribution seen in the data collected, and in what ways?
The Investigation Station design invites a visitor to place a collected sample on the table. A component of the sample then appears in a microscope view to the left, and a life-sized view of the area the sample was collected from is viewable to the right. The visitor can switch between each of four water quality components in the sample viewer by moving a selection disc.
The design guides a learner from the specifics of their own sample outwards to the context. This contextualization is crucial to understanding statistical investigations and prompts the visitor to dig deeply and think critically about a data point or a data set while allowing their own curiosity to guide their explorations.
Study 2.2: Immersion in data with interactive walls
The Distribution Aquarium invites learners to walk along a distribution visual to add and explore a sample. The visitor can see a spectrum of water quality represented along the wall, from the poorest water quality within the river system at the left to the best at the right.
One aim of this study was to explore how data might be visualized differently from traditional statistical representations, such as distribution curves or graphs.
In this design, the user is directed by indicators on the floor which direction they must travel along the wall to place their sample. The visitor is challenged to consider not only the data distribution, but the spectrum of the samples that compose and contextualize the data.
The data itself is not shown in a typical distribution, as this example water quality data is not composed of single, numerically quantifiable variables. Instead, each sample appears as a circle within the correct water quality category, from "Very Poor" to "Very High" water quality.
Over time, these samples fade, allowing visitors to view shifts in the average and the spread as they occur. This diagram shows the effect as a theoretical average shifts from "left" to "right".
The visitor can dive in to a particular data point through touch interactions with the wall. Within the sample circles, they can see magnified views of a select number of water quality indicators, and discover more in-depth information about how each indicator contributes to the sample's overall placement along the spectrum of water quality.
The goal of the wall is not to provide for robust statistical investigations. To the contrary — the goal of the wall is to provide an impression that data can tell a story. The distribution of samples on the wall, paired with the lively aquarium visuals, give the visitor a dynamic portrait of the overall health of the river system. The ability to dig into a sample provides the visitor with the general understanding that the variables that contribute to overall metrics can be deep and complex, always warranting careful exploration.
Study 3: Signage and movement provide context
This study explored how signage and movement through the installation can aid the learner in interpreting data through narrative framing. The goal of this study was to identify potential interpretive elements and determine which could best provide a narrative to encourage learners to work through the four steps of the GAISE II statistical problem solving process in their own way. Specifically, this study addresses Stage 3, which asks the learner to interpret results through contextualizing.
This study involved whiteboarding, writing, and sketching as methods of working through the considerations for signage and visitor movement within the experience.
The ultimate outcome of this study were three interrelated categories for narrative framing of the experience: story, signage, and pathways.
Story involves the content of text or graphics provided to help visitors understand and navigate the experience. The overarching story of the experience should focus on statistics and data; despite the use of water quality data as a grounding example, the textual content should focus on the main ideas of statistical problem solving.
Signage involves the location of interpretational content as well as its degree of interactivity, overall appearance, and timing, if animated or interactive. The content and design of text should not assume that visitors read all or any text in its entirety. Large text will be seen by most visitors and should frame main ideas. Small text will be read by visitors who want to "look closer" and should provide information intended to be supplemental. Text content should accommodate nonlinear reading and a range of reading levels.
Pathways involves considerations concerning how the visitor moves through the space and how this may augment interpretation of the experience. While the layout of the room can encourage movement that will make for a cohesive experience, designs should never assume linearity. Different signage may be visible depending on the visitor's direction of movement, providing just-in-time framing of the experience.
Study Four
The fourth and final study focused on how the combined elements of the previous three studies — an interactive projected floor, a touch wall, and narrative-focused signage — come together to produce a complete informal learning experience involving the statistical problem-solving process.
While Study Four incorporates the previous three studies, it is also intended to address its own discrete stage of the statistical problem solving process as described by the GAISE II framework, which asks learners to anticipate variability through the act of asking statistical investigative questions. While this step is the first in the four stages of the framework, it neatly addresses the purpose of the experience as a whole — to encourage learners to begin to ask statistical questions, and to spark curiosity about how data is used to understand the world around us.
The narrative of the experience is designed to convey that data tells a story. The exact story that data tells depends on what questions we ask and how we try to answer them. Following the experience, visitors should understand that data varies based on factors that can be explored through the process of asking and answering questions.
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