ar simulations on handheld computers

8/8/2019 AR Simulations on Handheld Computers

1/58

1

AUGMENTED REALITY SIMULATIONS ON HANDHELD COMPUTERS

Kurt Squire

University of Wisconsin-Madison

Eric Klopfer

Teacher Education, Massachusetts Institute of Technology

For correspondence, please contact Kurt Squire ([email protected]), School of

Education, UW Madison, Madison, WI.

Phone: 608-347-7333

This research was supported with a grant from Microsoft - MIT iCampus as a part of the Games-

to-Teach Project. The authors would like to thank Henry Jenkins of MIT and Randy Hinrichs at

Microsoft Research, co-PIs of this project for their support, as well as Kodjo Hesse, Gunnar

Harboe, and Walter Holland for their hard work in the development ofEnvironmental

Detectives. Thanks to Susan Yoon for her helpful feedback on an earlier draft of this paper.

RUNNING HEAD:

AUGMENTED REALITY SIMULTATION GAMING ON HANDHELD COMPUTERS


2/58

2

Abstract

Advancements in handheld computing, particularly theirportability, social interactivity, context

sensitivity, connectivity, and individuality open new opportunities immersive learning

environments. This paper articulates the pedagogical potential ofaugmented reality simulations

in environmental engineering education by immersing students in the roles of scientists

conducting investigations. This design experiment examines if augmented reality simulation

games can be used to help students understand science as a social practice, whereby inquiry is a

process of balancing and managing resources, combining multiple data sources, and forming and

revising hypotheses in situ. We provide four case studies of secondary environmental science

students participating in the program. Positioning students in virtual investigations made

apparent their beliefs about science, and confronted simplistic beliefs about the nature of science.

Playing the game in real space also triggered students pre-existing knowledge, suggesting that

a powerful potential of augmented reality simulation games could be in their ability to connect

academic content and practices with their physical lived worlds. The game structure provided

students a narrative to think with, although students differed in their ability to create a coherent

narrative of events. We argue thatEnvironmental Detectives is one model for helping students

understand the socially situated nature of scientific practice.


3/58

3

AUGMENTED REALITY SIMULATION GAMING ON HANDHELD COMPUTERS

Introduction

The use of computer simulations is changing the very nature of scientific investigation

(Casti, 1998) and providing unique insights into the way the world works (Wolfram, 2002).

Scientists can now experiment in a virtual world of complex, dynamic systems in a way that was

impossible just years ago. These tools have led to discoveries on topics ranging from the origins

of planets to the spread of diseases through human populations. In an effort to engage students in

the authentic making of science, many science educators (e.g., Feurzeig & Roberts, 1999) have

begun using models and simulations in classrooms as well (c.f. Colella, Klopfer, & Resnick,

2001; Friedman, & diSessa, 1999; Stratford, Krajcik, & Soloway, 1998). To date, most computer

simulations have been tethered to the desktop, as they have relied on the processing power of

desktop computers, but more ubiquitous and increasingly powerful portable devices make

entirely new kinds of simulation experiences possible (Klopfer, Squire, Jenkins, & Holland,

2001).

Handheld computersportability, social interactivity, context sensitivity, connectivity, and

individuality open new opportunities for creating participatory and augmented reality simulations

where players play a part in a simulated system, coming to understand its properties through

social interactions (Colella, 1999). One possible genre of applications is augmented reality

simulations, simulations where virtual data is connected to real world locations and contexts

(Klopfer, et al., 2001). In fields such as environmental science, where investigations are

profoundly rooted in the particulars of local context, augmented reality applications invite

science educators to bring the environment into the investigation process, while exploring

phenomena impossible to produce in the real world, such as toxic chemicals flowing through


4/58

4

watersheds or diseases. By simulating a virtual investigation, educators can potentially initiate

students into environmental science as a coherent socialpractice, as opposed to a set of

disconnected procedures or body of facts. Investigating how a toxin such as Trichloroethylene

(or TCE) spreads through a watershed might be educationally valuable (particularly for

environmental engineering students who might eventually conduct such investigations) but is

obviously too dangerous to pursue. In this paper, we argue that augmented reality applications

have promise in environmental science curricula because they allow curricula developers to

design game trade-offs around core disciplinary dilemmas (Cobb et al., 2003), non-linear open-

ended dilemmas with no clear boundaries, that are central to a field. This allows students to learn

through failure, by intellectual play with robust disciplinary problems. Students reflections on

their successes and failure combined with carefully crafted collaboration allows students to

explore difficult and complex tasks while building expertise in the field.

This research study examines the potential for creating an augmented reality application

around the core of environmental science practice. Specifically, we want students to understand:

(1) trade-offs between efficiency and quality of data in conducting an investigation, (2) the

importance of synthesizing background desktop research with secondary sources and primary

data collected in the field, and (3) the necessity of continuously refining hypotheses in response

to emerging data. In short, a struggle for students studying environmental science (particularly

engineering students) is in understanding that research programs are situated in social contexts

where access to resources, affordances and constraints of tools, and, perhaps most importantly,

time shape inquiry (Bhandari & Erickson, 2005; Latour, 1987). Emerging pedagogies such as

case studies are increasingly used to help environmental engineering students understand the

socially situated nature of engineering as a practice and see the interrelationships among

variables in conducting an investigation. Within high school science curricula, these same


5/58

5

educational goals align with most state earth science inquiry standards.

Research Questions

Specifically, this design-based research study investigates: Can augmented reality

technologies be used to give students a vicarious experience of leading a virtual investigation,

using game structures and handheld technologies to scaffold their thinking into environmental

engineering practices? We hypothesize that an augmented reality game which positions players

as environmental scientists where they conduct a virtual investigation of a hypothetical toxic

spill (modeled on a similar case study), might help participants learn to see investigations as

socially situated enterprises. As such, this research study also investigates the potential of

designing learning environments using digital gaming conventions and aesthetics (e.g., character

conventions) to enlist and mobilize game players identities and aesthetic considerations

(Games-to-Teach, 2003; Gee, 2003).

Working with environmental science faculty at MIT, we developed augmented reality

simulations of a carcinogenic toxin (TCE) flowing through an urban watershed, known

collectively asEnvironmental Detectives. In a series of four case studies with approximately 75

students, we examine: (1) What practices students engage in while participating in

Environmental Detectives, specifically how they integrate real and virtual data in problem-

solving and conducting their scientific investigations; (2) How students construct the problem

(e.g., as well-defined or open-ended, authentic or inauthentic); (3) How field investigation in the

physical environment mediates students inquiry; (4) What instructional supports are useful in

supporting learning. We argue that augmented reality simulations are powerful learning tools for

understanding the socially situated nature of science, specifically in situations when educators

want thephysical environmentto be a part of students thinking and scientific reasoning.

Through presenting a series of case studies, we attempt to articulate how this pedagogical model


6/58

6

can work, while also suggesting where there are limitations in our current understandings of how

they function.

Theoretical Approach: Augmented Reality and Situated Cognition

Over the past decades, a growing number of educational theorists and researchers in the

learning sciences have argued for the importance of understanding cognition in context (e.g.,

Brown, Collins, & Diguid, 1989; Barab & Kirschner, 2001; Cognition and Technology Group at

Vanderbilt, 1990; Greeno, 1998; Kirshner & Whitson, 1996). Whereas traditional cognitive

models treat the workings of the mind as somewhat independent, a host of emerging,

complementary approaches to cognition treat cognition and context as inextricably linked. How

these different approaches construct the notion of context depends on their underlying theoretical

framework. In this paper, we use this situated model of cognition as the basis for designing a

curriculum around conducting investigations in environmental science. Specifically, we try to

use augmented realities to situate learners in emotionally compelling, cognitively complex

problem solving contexts.

Learning as Doing

Greeno (1998) introduces the notion of situativity as a way of understanding theproblem

space of a learning episode. Greeno describes problem spaces as, the understanding of a

problem by a problem solver, including a representation of the situation, the main goal, and

operators for changing situations, and strategies, plans, and knowledge of general properties and

relations in the domain (p. 7). Whereas traditional psychological models take the individual

learner operating without regards to context, situativity theorists argue that there is no such thing

as context-independent thought and behavior and that the central goal of educational psychology

is to understand performance as it occurs in socially meaningful situations, accounting for multi-


7/58

7

person communal structures, individuals goals and intentions, and tools and resources which

mediate action. Learning is always fundamentally about doing something for some purpose in a

social context equipped with tools and resources, making the minimal meaningful ontology the

who, what, where, and whys of a situation (Wertsch, 1998).

Because learning is a process of creating meaning in situ, the environment plays an

important role in the processes of knowing and learning; the environment constrains activity,

affords particular types of activity or performance, and supports performance (Dewey, 1938;

Peirce, 1868/1992; Salomon, 1993). Effective action is always situated within environmental

constraints and affordances, and a mark of expertise is ones ability to see the environment in

particular ways (c.f. Glenberg, 1999; Goodwin, 1993). If we are to take a situated view of

environmental engineering, then a primary goal is to help students learn to see the environment

as an environmental engineer might. We need to help students become attuned to the affordances

and limitations ofdoing in environmental science, particularly navigating complex problem

spaces with multiple variables and solutions. From this perspective, it is not enough for students

to know a list of facts or procedures about environmental engineering. They need robust

experiences in environmental engineering which can be the basis for future action. Indeed, from

the situated perspective, an indictment of most school-based learning is the way that information

is cleaved from direct experience in the physical world, processed and digested for learners

(Barab et al., 1999). In the case of environmental science, this means being handed prepackaged

research techniques (such as sampling strategies) or investigative design heuristics (e.g.,

investigations as social processes that involve managing budgets and constraints) without having

opportunities to develop such understandings through action and to appreciate their practical

importance. Results and procedures are handed to students ready made, divorced from the

social contexts that produce them.


8/58

8

Designing Learning Environments Based on Situated Learning Theory

Cognitive apprenticeships have been posited as one model for education as they situate

learners in complex tasks where they have access to expert cognition including the social

context of activity (Brown, Collins & Newman, 1989). Unfortunately, apprenticing students to

experts is not always feasible, particularly for secondary students or post-secondary students in

an early stage of career development, as studied here. Apprenticeships are also often long,

difficult, even exploitive. As Shaffer (2004) argues, a challenge facing contemporary learning

scientists is how to recreate the most robust learning moments of apprenticeships (which often

occur in the practicum), but in ways that are most efficacious for long-term learning. We argue

that augmented reality simulations are one possible way to engage learners in complex

investigations within a context that is socially safe and feasible.

Augmented reality approaches draw from earlier situated approaches, ranging from

problem-based learning to case-based scenarios to anchored instruction, which Barab and Duffy

(1999) call practice field approaches. However, augmented reality specifically attempts to

situate learners within the practices of environmental engineering in a manner similar to what

Shaffer (2004) calls professional practice simulations. These features provide: domain-related

practices, ownership of the inquiry, coaching and modeling of thinking skills, an opportunity for

reflection, open-ended dilemmas, scaffolding for (rather than simplification of) the dilemma,

collaborative and social work, motivation for learning context. In this case, we are using

augmented reality technologies to situate the learner in the context of an environmental science

investigation. In the context of environmental science, handheld computers allow students to

collect data while conducting complex field investigations, access authentic tools and resources,

and participate in collaborative learning practices while in the field. Whereas traditional desktop

VR applications or 3D gaming technologies such as MUVEs burden the computer with


9/58

9

reproducing reality in 3D, augmented realities exploit the affordances of the real world,

providing users layers of data that augment their experience of reality. As a result, simulations

are untethered from the desktop and learners can participate in technology-enhanced

investigations, location-based games, or participatory simulations. Because players are free to

move throughout the world, novel opportunities exist for learners to interact with the physical

environment, literally reading the landscape as they conduct environmental investigations or

historical studies.

Augmented Reality Environmental Investigations

Augmented realities attempt to build on earlier work with digital tools that attempt to use

technologies to mediate students interactions with science. Tools such as Model-It (Spitulnik,

Studer, Funkel, Gustafson, & Soloway, 1995) or Climate Watcher (Edelson, Pea, & Gomez,

1996) have been used to help learners engage in scientific modeling processes where they can

build understandings of their environment or which mediate how students encounter dilemmas,

collaborate in solving problems, and represent problem solutions (Salomon, 1993). Augmented

reality simulations attempt to build on these innovations by (a) tying a more broadly applicable

intellectual experience to a core disciplinary dilemma and scientific practice, and (b) using

computational media to help students appropriate their real surroundings for authentic simulated

investigations.

In particular, we try to use the Pocket PCs multimedia and simulation capacities for

interactive storytelling, creating contexts where learners will experience a story which can

become a narrative to think with in the study of science (c.f. Schank, 1994). Pocket PCs, which

can display video, text, and host webs of information in intranets, can create virtual worlds that

go beyond just presenting data, by providing narrative context similar to problem-based learning

or anchored instruction environments. Leveraging design techniques from role playing games


10/58

10

(c.f. Gee, 2003), we are investigating if augmented reality simulations can entice learners into

complex scientific practices through adopting the personae of scientists. We hypothesize that

opportunities exist for immersive gaming environments to recruit players into assuming new

identities as environmental investigators, scientists, and environmental activists, thereby

encouraging students to adopt ways of thinking that might be ideal preparation for future

learning.

Augmented reality applications hold particular promise in disciplines such as

environmental engineering, where spatial and contextual information are core components of

professional practice. In authentic field studies, such as investigating and remediating toxic

spills, spatial information about the distribution of the spill and location sensitive information

about the spills proximity to other parts of the environment are central to conducting an

investigation. However, the investigative process, sampling strategies, and remediation

strategies are all mediated by social factors (c.f. Dorweiler & Yakhou, 1998)1. Students often

have difficulty recognizing the situated nature of environmental engineering investigations and

learning to act effectively within the many constraints (Nepf, 2002). Yet these constraints and the

ability to adapt to them are key disciplinary practices that are manifest in several distinct ways.

First, environmental investigations are affected by resource constraints. The amount of time,

money, equipment, and human power available affects what strategies are feasible in any given

context. Second, the physical particulars of the research context drive an investigation, and

research goals are often reprioritized in relation to local context. For example, discovering a

lethal toxin in groundwater in close proximity to a major source of drinking water might be cause

for re-evaluating a research approach, whereas a similar toxin in another location that does not

use groundwater for drinking would not be. Third, there is an interplay between desktop research

1Thanks to Heidi Nepf, hydrologist and toxicologist at MIT for her help in helping us

understand these factors.


11/58

11

and collecting field data. In some cases, a knowledgeable informant can save investigators time

and money by pointing investigators to probable culprits. Finally, social constraints affect both

the investigative process and remediation strategies, as investigators need to manage how their

work is perceived by others (particularly the press). Investigators need to avoid generating

unwarranted public alarm, or in some cases, generating bad press for clients. A few

environmental educators have begun exploring how immersing students in problems based on

current events might serve as useful pedagogical models in environmental and chemical

engineering to address some of the above issues (c.f. Dorland and Buria, 1995; Patterson, 1980).

Context

This study examines the implementation of a particular augmented-reality simulation,

Environmental Detectives in three different university classes and one high school class. We

have deliberately chosen a wide range of classes in order to see how learners with different

backgrounds and affiliations toward science react to this experimental program. As such, it is

designed to illustrate the range of possible enactments of the program, rather than generate strict

comparisons. This study is a part of a larger design research agenda (Collins, 1992) exploring the

potential of augmented reality for supporting learning in environmental education .

Environmental Detectives is an augmented reality simulation game for the Pocket PC developed

by the investigating team using the Microsoft .NET compact framework.Environmental

Detectives was designed in consultation with environmental engineering faculty and is matched

to scientific inquiry learning goals in an AP level science, making it possible for use across high

school and college courses (with teachers choosing to appropriate it in different ways according

to their contexts).

Curricular Goals and Framework


12/58

12

The curricular goal ofEnvironmental Detectives is to give students an experience of

leading a complex environmental science investigation so that they can understand the socially

situated nature of scientific investigations. The game scenario was designed in consultation with

two environmental science faculty and designed around a core dilemma of environmental

science: how to conduct effective environmental investigations within social, geographic, and

temporal constraints. This scenario requires students to (1) develop sampling strategies, (2)

analyze and interpret data, (3) read and interpret scientific texts to understand the problem, and

(4) ultimately design a viable remediation plan for core constituents. Scientific investigations are

frequently presented to students as closed-ended problems with one right answer which can be

solved linearly (c.f. Zolin, R., Fruchter, R., and Levitt, 2003). Conversely, scientists in the field

continuously frame and reframe the problem in response to budgetary and time constraints, local

conditions, and what is known about the problem. As an example, researchers design sampling

strategies in relation to the chemical and physical properties of a toxin, its potential health and

environmental effects, legal issues surrounding its spread, and local conditions, such as nearby

waterways and impediments to sampling (i.e., human made physical structures or waterways).

Consistent with efforts such as the Problem- Project- Product- Process- People-based Learning

Laboratory at Stanford University (Fruchter, 2004; http://pbl.stanford.edu), our goal is to

immerse students in complex problem spaces where they draw on diverse resources, design

creative solutions, and work across complex distributed environments in solving problems.

Environmental Detectives

InEnvironmental Detectives, participants work in teams of 2-3 students playing the role

of environmental engineers investigating a simulated chemical spill within a watershed. In the

university implementations, the watershed was surrounding the students university, including a

nearby river, while for the high school students the watershed was associated with a working


13/58

13

farm located within a nature center. The high school class regularly took field trips to the nature

center, thus making it the best proxy environment comparable to the university campus. Both

real world watersheds include streams, trees, and other natural elements which are then

augmented by a simulation of an environmental disaster: in this case a toxic spill of TCE that can

potentially contaminate ground and surface water. In the university case further context was

added concerning a recent construction project on campus, while in the high school case

additional information was added concerning a possible state buyout of the farm at the nature

center. Each of these additions was done to provide locally topical information, a hallmark of

augmented realities. Moving about in the real world, the handheld computers (Pocket PCs)

provide a simulation where students can take simulated sample readings, interview virtual people

and get local geographical information (See Figure 1).

The spread of TCE is simulated on a location-aware Pocket PC, which, equipped with a

GPS device, allows players to sample chemical concentrations in the groundwater depending on

their location. For example, if the player is standing at point a, which is near the source of the

spill (See Figure 1), she might take a reading of 85 parts per billion, whereas a student standing

on the opposite end of campus (point b) might take a reading of 10 points per billion. Players are

given three reusable virtual drilling apparatuses that they can use to drill for water samples. After

drilling for a sample, players must wait three minutes for the drilling to complete and an

additional one to three minutes for a sample to be processed. These waiting periods were

designed into the game to simulate actual temporal constraints. This limits students to collect

only three samples at a time, driving them to develop sampling strategies to optimize the amount

of territory that they can cover within their limited time.

Environmental Detectives contains a multimedia database of resources which students

can access to learn more about the chemical make-up of TCE, where TCE is found on campus,


14/58

14

the health risks associated with exposure to TCE, how TCE flows through ground water, relevant

EPA regulations TCE, remediation strategies for cleaning up TCE, and the political and

economic consequences of EPA violations on campus. Students access these resources by

obtaining interviews from virtual experts who we have located at various points around the

campus in locations roughly corresponding with actual operations. That is, an expert on

hydrology would be near a building where that topic is studied, and a character with records of

where chemicals used would be located near an office that performs these functions. Because

there is not enough time to interview everyone or to drill more than a handful of wells, students

must make choices between collecting interviews, gathering background information, and

drilling wells, adjusting and reprioritizing goals as new information becomes available.

In addition to simulating an environmental investigation within complex socially situated

settings,Environmental Detectives is designed to leverage the affordances and conventions of

computer gaming to intellectually engage students in complex problem-solving by providing a

safe realm for experimenting with new ideas and new identities. Whereas in authentic

environmental engineering investigations (or learning by apprenticeship models), students

failure might result in damaged professional reputation, a waste of public resources, or in a

worse case scenario, human illness or death, games and simulations allow students to enact

strategies in a pedagogically safe space where failure is possible, if not expected, and players are

encouraged to experiment with new ideas and identities.

To be successful inEnvironmental Detectives, students must combine both the real-world

and virtual-world data to get to the bottom of the problem. The precise location of the spill is

unknowable to students, and there is no one perfect solution to remediating the problem; each

solution involves political, financial, and practical trade-offs that must be considered. Consistent

with problem-based learning frameworks (e.g., Barron et al. 1998), students use their handheld


15/58

15

computers as tools for gathering firsthand data about the location and severity of the spill, and as

a resource for accessing archives of information about toxicology, hydrology, similar cases, and

local environmental conditions.

While each participant chooses his or her own path through the informational and

geographic landscape of the game, the following describes what a typical player might

experience. By design,Environmental Detectives starts with a statement of the problem (the

potential contamination of a local water supply with a chemical) that should provoke questions

about the geographic extent and intensity of the problem (determined by collecting primary

quantitative data) and the history and future ramifications of the problem (determined through

interviews with experts). A pair of players in the game might start by walking from the initial

briefing location (where all players receive an orientation) to the site of the initial reported

measurement (which may take 5-10 minutes), and take a measure there by drilling a virtual

sampling well. After getting that reading back (reported as a unitless number, e.g., 40 rather

than 40 parts per billion), they may seek an expert who could help explain that reading.

Along the way to that location, the players might take additional samples (by drilling wells)

along some transect to try to determine a trend in the samples. After getting information on what

units the readings are reported in and thus their significance, the players could decide to seek

information from other experts on health or legal ramifications of the toxin, or perhaps

investigate from where the toxin may have come. They would also need to return to the

geographic site of their sampling wells to retrieve the readings from those locations. This

process ideally would be iterated, taking a planned array of samples, and interviewing the experts

to determine a course of action. This plan is complicated by the physical barriers (bodies of

water, fences, etc.) and geographic information (terrain, tree cover, etc.) that the players gather as

they experience the real environment around them.


16/58

16

This version ofEnvironmental Detectives takes 2-3 hours to complete, including

introduction, game play, and debriefing, although a teacher might extend or shorten the game in

order to meet her classroom needs. The simulation is designed to be flexibly adaptive, so that

teachers might easily add extension activities (such as exploring the properties of TCE, the

health effects of TCE, hydrology, water treatment plans, or similar cases) or remove activities as

local conditions suggest (See Squire, MaKinster, Barnett, et al., 2003). For example, some of the

university classes drew parallels to similar engineering studies done on toxins in the area, or

further analyzed the research methodology applied during the investigation. Similarly, the high

school class engaged in further reflection on chemical properties of the toxin and further analysis

of the watershed in which the investigation took place.

Participants

In the first phase of the project, we examinedEnvironmental Detectives in three courses

at a private technical university in the Eastern United States. One course was a freshmen

environmental engineering course; the other two were sections from an undergraduate scientific

research and writing course, each with 18-20 students. In both contexts, the game was used to

introduce students to issues around conducting real world environmental investigations and used

as a prelude for a larger research project. All three classes were two hours in length. This paper

reports findings synthesized from these classes, with the focus on a small number of groups from

two of the groups. These groups are intended to be representative of the range of student

experiences (including those who successfully engaged in the necessary practices and those who

struggled). Findings from the other course are reported elsewhere (Klopfer, Squire, & Jenkins,

2004; Klopfer & Squire, in press).

The second phase of the project took place at a nature center in an East Coast


17/58

17

metropolitan area and involved an environmental science class of 18 high school students. The

session involved roughly twenty minutes of introduction time, ninety minutes of game play and

twenty minutes of debriefing. The pedagogical goals of the game were developed with nature

center educators interested in engaging students in more robust activities than traditional fieldtrip

scavenger hunt exercises. They hoped thatEnvironmental Detectives would encourage

students to interact with the environment, geography and history of the site as well as participate

in domain-based problem solving. We chose this group because we wanted to see how students

from a non-technical background would respond to the activity. In particular, we were interested

in examining how non-engineering students would use the technology, balance the driving

problem behind the curriculum, and construct the problem of understanding toxic flows. Here

we primarily focus on two groups as case studies but also include information from other groups

and the entire class debrief. The groups we chose to focus on again represent the range of

experiences demonstrating more and less successful problem solving strategies. While the

specifics of the problem were adapted for the nature center site, the scenario was essentially the

same, and involved the same information and subject matter, making the scenario and experience

comparable to the university classes.

Methodology

In this study, we used a naturalistic case-study methodology (Stake, 1995) to gain a

holistic view of the activity that unfolded during gameplay, understand how learning occurred

through participation in these activities, and remain responsive to unanticipated issues which

might arise during the research. Because we were interested in accounting for student-computer,

student-student, and culturestudent interactions, we employed quasi-ethnographic techniques

designed to capture student actions at the molar level (Goodwin, 1994). Capturing an ecology,


18/58

18

including the many tools, resources, and social structures that characterize any particular context

of activity is challenging and still being negotiated in educational research (Engestrom & Cole,

1993). In describing a situation as a unit of analysis, Cole (1995) concentrated on practice,

activity, contexts, situations, and events. We use narrative case studies to provide a broad flow

of events that take each of these factors into consideration (c.f. Hoadley, 2002). We also use

discourse analysis (Gee, 1992) to examine more closely how students constructed and framed

problems, and to study relations between class discourses and students scientific investigations.

Specifically, we investigate: (1) The practices students engage in while participating in

Environmental Detectives, (how they integrate real and virtual data in problem-solving and

conducting their scientific investigations); (2) How students construct the problem (e.g., as well-

defined or ill-defined, authentic or inauthentic); (3) How investigation in the physical

environment mediates students inquiry; (4) What instructional supports were useful in

supporting learning.

Data Sources

Observations. Four trained researchers attended each session, and a trained researcher

followed each student team during the game, video-taping a subset of the groups and

documenting student practices in field notes. Consistent with other researchers studying

problem-based learning environments (e.g., Barron, et. al, 1998; Nelson, 1999), we paid special

attention to student discourse, examining how students framed the initial problem, constructed

goals of the activity, negotiated information in groups, planned activities, and developed shared

understandings. The text selected here for analysis was chosen because it was representative of

typical dialogue across a range of responses. We used informal, non-structured interview

questions during the exercise to confirm observations, clarify students goals and intentions, and

learn more about students handheld-mediated activities. Although the researchers were clearly


19/58

19

participant-observers in the activity, they attempted to remain unobtrusive whenever possible.

Interviews and Artifacts. We also conducted a twenty minute focus-group and exit survey

to probe students experiences in depth to document their thoughts, feelings, and attitudes toward

the experience. We also recorded students inscriptions, physical gestures, and interactions with

the Pocket PC. Additionally, we gathered and analyzed data emerging from students off-

computer activity, including written inscriptions some groups used to plan their investigation

(c.f. Roth, 1996).

Data Analysis

Two researchers viewed and analyzed all researcher field notes, video tapes, and

students projects using the constant comparative method (Glaser & Strauss, 1967), to generate

relevant themes from the data. Consistent with Stakes responsive method (1995), we paid

special attention to unexpected and unintended consequences, given the exploratory nature of

this research. After each round of videotape viewing, we developed emergent hypotheses, re-

examining and refining these hypotheses as we watched subsequent tapes looking for

disconfirming evidence or counter-hypotheses. We then wrote several case studies from both the

university and high school parts of the project to capture the key events or turning points in

students thinking.

Two of the university case studies are included here (although we also include short

excerpts from and mention of other groups). The cases are intended as a means of conveying a

flavor of activity, and providing the reader with a basis for generating contrary interpretations of

the activity. Two case studies from the high school participants are also included (while a third

additional case is reported in Klopfer, Squire, & Jenkins, 2004). In the high school cases we

focus specifically on the discourse of the groups, as well as the group presentations and debriefs

in order to understand how students frame the problem and generate meaning in situ. Given our


20/58

20

observations with the university students in this study that a driving contradiction existed

between the dual needs of doing desktop research and collecting samples we decided to focus

on this issue in greater depth in this part.

For each of the case studies we provide the synthesis of a discourse analysis (roughly 15

pages per group and not all included here), an analysis of how language enacts activities,

perspectives, and identities" (Gee, 1999, p. 4-5). Researchers transcribed the interactions of

groups that were representative (typical) of talk across the range of successful and unsuccessful

groups. Consistent with Gee (1999) we focused on how language, specifically, word choice,

cues, syntactic and prosodic markers, cohesion devices, discourse organization, contextualization

signals, and thematic organization in language created the activity. Essentially, this analysis is

toward understanding meaning, how it is made, enacted, and represented in situ. We specifically

looked for moments where meaning was negotiated and shared understandings were mobilized to

solve problems, and where meanings generated further action. Specifically, this methodology

allows us to gain insight into how participants framed the problem, constructed the reason behind

the activity, and negotiated problem-solving strategies in situ (e.g., Barab & Kirshner, 2001.

Results

The following case studies describe the results of our design experiment. We start by

describing an illustrative example, a case study of a typical group. In this first case we outline

the process of their investigation as they notably engage in (1) privileging quantitative data; (2)

framing the problem as a uni-dimensional one of tracking down the toxin to its source as

opposed to a multi-dimensional problem involving probable cause, potential health and legal

effects, and suggested remediation strategies; (3) integrating prior knowledge of the environment

with students reasoning; (4) creating emergent sampling strategies, such as triangulation. (5)


21/58

21

voting with their feet as they decided which problem-solving path to pursue. We then present

contrasting case studies ofEnvironmental Detectives in action and focus on how the activity

unfolded across groups. In particular, we examine how students constructed the activity and then

use a discourse analysis method as a basis for showing how the activity was constructed in

different settings. We argue that augmented reality simulation games are a potentially powerful

emerging medium for education in contextual settings.

University Case Studies

After a classroom briefing introducing the problem, students met at the center of campus

and learned to use their GPS and Pocket PC. Most groups immediately drilled a sample and then

picked a direction to move to, based on their theories of where toxins might have originated,

concern for downstream consequences of the toxins spread, or, in some cases, just random

guessing. Groups generally negotiated where to take the second sample from; in some cases, a

group leader, usually the person with the Pocket PC would lead the way. Across all groups,

participants frequently negotiated and debated where to go (as evinced through their talk below).

One group of three students, tailed by a researcher, headed up away from the river and

toward campus. One of the students inquired, How many samples do we need? It was not

clear whether the question was addressed to the researcher or the rest of the group, but no one

responded. The student holding the Pocket PC had previous GPS experience and started to guide

the group. He drilled for one sample and then walked to nearby locations to take two more

samples, the maximum amount of concurrent samples permitted. He chose a triangular

configuration, though when another student asked why he chose this arrangement, he cited no

particular reason.

Students retraced their steps as they waited for the required three minutes between


22/58

22

sample drilling and reading. Finally the sample was retrieved. The reading was 88. Another

student asked if 88 was good or bad. One student hypothesized that the number could be a

percentage, but no one could answer definitively. They decided to collect more data.

As they walked to collect their two drill rigs (used to take samples), a student not holding

the Pocket PC asked what the data looked like. The student with the handheld described their

current readings by pointing to three locations in physical space (as opposed to showing on the

handheld) and citing the readings. Students again debated the meanings of these readings. One

student hypothesized that the readings were in parts per million. The student holding the Pocket

PC suggested that they should go toward the higher numbers, pointing into the distance. They

walked several hundred yards through several buildings toward the higher number and placed

more drills.

This pattern of drilling to find the source before considering the meaning of numbers was

similar across groups as suggested by this exchange, taken from another group:

Lisa: The reading is 4.Ben: Its obviously good. Come on now.Lisa: I dont think it is good.Ben: Its obviously good.Lisa: Four. Like four is a bad reading. Like four on a scale of one to five. Four is real bad.Ben: On a scale of one to fifty though, four is pretty damn good.Mel: True, but what is this scale? We dont know that.Ben: We dont know that.Lisa: We have no idea. It could even be that the top one is the best.Mel: OK. So we need to dig another well.Ben: Lets get this one first [referring to an already dug well].

Most groups initially constructed the activity as a pattern recognition search for the source of the

toxin, opting to drill more samples to define some pattern rather than consult documents or

experts who could definitively tell them what levels were of concern, as they were informed at

the onset of the activity. They avoided conducting the desktop research that environmental

scientists describe as critical to these investigations. This exchange, which was typical of most


23/58

23

groups, also reflects the amount of negotiation and debate behind sampling strategies. Most

groups (typical of prominent discourse patterns in the class and in the institution) were

argumentative in thinking through results.

After several minutes, the readings from this second round of drill placements returned

from the lab. One student noted that the new readings were very high in one direction. They

walked in the direction of the higher readings, as if following a trail or scent, pausing briefly to

interview a virtual staff member in environmental policy, who happened to be nearby. The

interview yielded little information, but it did reveal that they could conduct a second interview

with a TCE supplier from facilities at a new location across campus, which they needed to visit

within the next half hour because the informant was leaving for another meeting (this event is

then triggered on their Pocket PC). They decided to immediately go to the new building

although there was no discussion about what information they hoped to find, or hypothesizing its

anticipated value. Along the way they looked at the emerging gradient and one student

hypothesized that the concentration was likely to be higher on the other side of the building (the

one they hadnt visited yet).

The second interview revealed where TCE is used on campus, and the student holding the

Pocket PC summarized the information for the others. Meanwhile, the group took another

reading. One student (not holding the Pocket PC) realized that the highest concentration

appeared to be surrounding one building and suggested that they should drill more wells there.

Another student dismissed this idea, assuring them that they had already sufficiently pinpointed

the source of the leakage to that building. Using the information from the toxin supplier

combined with pre-existing knowledge of the activities near that building (the university

machine shop is located there), he correctly identified the source of the toxin and suggested that

they obtain interviews to help interpret their data. It is worth noting that although they had spent


24/58

24

nearly 50% of their time already, the group did not know what units the readings were in (and

indeed, one student hypothesized incorrectly that they were a percentage), what levels of TCE

were dangerous, how likely the TCE was to spread throughout the environment (including into a

nearby river), or what legal repercussions the university might face if the TCE were to leak off of

university property. Most groups (all but one or two of the approximately twelve groups that we

studied) had similar problem-solving strategies, although one group, notably, stopped at a

computer and used Google to find a good deal of information on TCE (which was applicable in

this simulation that used realistic data).

Seeing another interview nearby, they headed in that direction. One student noticed the

time and paused, causing the group to stop. He suggested that they use their last 15 minutes

wisely. The Pocket PC changed hands briefly to a different group member, but was quickly

returned to the student who had held it most of the time because there was some confusion as to

where they were headed next. After several minutes of circling the building, they finally

accessed the interview which explained how groundwater flows through campus. Here they

learned that the groundwater was not used for drinking.

As the students headed back to class, they discussed the implications of their findings.

Reviewing their documents, they learned that planting trees could mitigate some of the effects of

TCE. One student looked at the building where they hypothesized the toxin originated and then

back at the river, declaring that by the time the pollution gets to the river the pollution is likely to

be highly reduced (although they had no concrete evidence to base this assertion on).

Debriefing. Each group presented their findings before the class. This group, like most,

had pinned the location of the spill down to a particular building based on following a gradient

that they had observed (which was correct) and theorized that the spill came from the machine

shop. They argued that the spill was not a problem because the groundwater is not a source for


25/58

25

drinking water, and the river was too far from the source of the pollution to be a problem. They

recommended planting trees to mitigate the problem and monitoring the situation over time.

They noted that this solution would cause little alarm in the community and not destroy the only

grassy area on campus.

Cross Group Discussions. Most of the twelve groups that we studied made similar

findings. Most relied heavily on sampling, and roughly 75% of the groups accurately determined

the location in the time allotted. Most groups also suggested the politically expedient answer of

planting trees and monitoring the situation because they saw no immediate legal or health threat.

Only three groups, which all focused on collecting interview data, correctly surmised that

regardless of whether the spill was an immediate health hazard it was a legal threat and should be

cleaned up to avoid EPA fines. Students across all the groups were very sensitive of the political

ramifications of falsely calling too much attention to the problem, given the fact that Building 3

is centrally located on campus. This concern about unduly drawing negative attention to the

university was introduced in the cover story but eagerly taken up by players as a driving factor

behind any solutions. Successful groups gathered both samples and interview data, recursively

examining what was known, reframing the research questions, and gathering new data.

For example, the following description of another group begins as they are taking their

second reading. Instead of immediately trying to pinpoint the precise location of the spill, they

located an interview with a faculty member to tell them more about TCE while they waited for

lab results.

Jenny: It just said that the results of the lab said, 30 so it might be 30 parts percubic feet.

Steve: That is not as bad as the military base in Cape Cod, so just rememberthat it can be nasty or something. (Summarizing the text from theinterview to the group): So what do you want to knowTCE is foundall over placea spill in Illinois So how fast does it move? Dependson the soil and whatnot, 1.5- to 7 feet per day, ooooh (repeating aloud,1.5 to 7 feet per day. Bill writes down the numbers).


26/58

26

Jenny: Thats not a concentration.Bill: It doesnt sound like a rate of flow; its a rate of spill.Steve: Well it just said the result from the lab is 30 so it might be30 cubic

feet I dont know.Bill: Cubic feet per day doesnt make sense either. It ought to be a rate of

spill.Steve: (Continues summarizing) We need to build a model of how TCE moves

through the groundwater lots of things to take into accountYouhave a certain mass of stuff thats been spilled, and its covering a largerand larger region everyday because of spread. As a rule of thumb youmight assume that it spreads at a rate of 150 feet per year.

Bill: Whoa, whoa, whoa per year?Steve: Per year.Bill Ok, 150 feet per year. (writes the numbers down). Okay. So, (pausing to

think), decaying at about half of its concentration. So if you start with100 parts per billion thats per... 50 parts per billion at 150 feet per year.The 30 and 70 could be possible.

This interaction, while less representative of what occurred, shows a more productive intellectual

interplay between primary and secondary data sources. Right away they query the meaning of

the readings, speculating that it could be parts per cubic feet, a concentration which they note

compares favorably to the readings found in Cape Cod (a case study they learned about via their

interview). They also read that they need to create a model of how TCE moves through the

groundwater, and subsequently compare their readings to the data they are presented from the

case study.

Next, Jenny adds that they can use this data to pinpoint the source of the spill, but new

information about phytoremediation changes the topic.

Jenny: The 30 should tell us something about the source of the spill beingcloser to the

Bill: Yeah, I think so.

Steve: (reading) What should we do about remediation TCE? Planting trees,phytoremediation.

Bill (Writing, reading? aloud what he writes). Plant trees to suck TCE out.So were nervous about the effects of TCE on the environment. Wedont know that TCE is, like infecting trees. We have higher readings,which is contradictory to

Steve: Higher reading where theres less trees. No more trees.Jenny: Because its sucking the TCE out.


27/58

27

Steve: Hold out theres more information. Its expensive and you could getwater treatment partsomething about backyard. (As Steve finishesreading, the group begins walking).

Jenny: Pumps are the best because trees dont do anything.

Here, introducing the concept of phytoremediation does two things: First, it makes the

group realize that the existence of vegetation could be affecting their results. Second, it

introduces the issue of what to do about TCE. Unlike other groups, this group realizes

that phytoremediation is a partial remedy, at best.

However, the group also realizes that they know very little about TCE as a

chemical, its health effects, or what might have caused this spill. Bill begins by

suggesting that they drill more samples, but the group realizes that this will not help them

learn about TCE. They go back and forth between querying one another on what they

know, what they need to know, and where they might find the information.

Bill: We could just start digging holes to get more information.Jenny: Since were going to the classroom, lets ask Eric (one of the in-game

characters whom they can interview).Steve: What is he going to know about TCE?Jenny: Who knows.Bill: We never learned what TCE is at all, did we? We have no ideas what its

effects are on the environment.Jenny: Trees suck it up.Steve: For all we know, TCE is just another form of water particlewe dont

know that theres anything bad about it.

Steve raises a critical point here; the group is not exactly certain why TCE is a dangerous

chemical. They know that there have been other spills, and they know that trees absorb

some amounts of it, but they are not sure in what form or concentrations it is actually

dangerous (if at all).

In the next exchange, Bill connects these concerns to his existing knowledge of

the Charles River.

Bill: We know that its in the Charles, which is already disgusting. Its


28/58

28

possible that TCE is such a ridiculously small affect compared to the bigmess of the Charles, and I have friends by the way who study theCharles River and are not impressed. So, thats a possibility. We alsoknow that the water isnt used for drinking

Jenny: We used to go canoeing on the Charles River. And we always had towatch out. People fell out of their canoe their eyes were stinging andstuff.

This exchange illustrates a common phenomenon in augmented reality games. Facing gaps in

their knowledge about chemicals, health effects, or the history of their local space, players will

frequently begin taking what they already know (or think they know) about the environment (in

this case, the fact that the Charles River is polluted and not used for drinking) and apply it to the

problem at hand. Given the importance of activating prior knowledge in learning for deep

understanding, this tendency to build connections between the game space and their existing,

lived knowledge of the space is encouraging.

In the debriefing, this group made the case that there were significant concentrations of

TCE in the groundwater and it had been there for at least a few years, as evidenced by the size of

the plume. They believed that it would soon be in the Charles River, but they were not sure of

the precise health effects. They believed that it was a cause for concern, and that some sort of

pumping would be required to remove the toxin. They were one of the few groups to advocate

cleaning the groundwater, rather than planting trees and monitoring the situation.

High School Case Studies

Most college students had framed the problem as one of collecting samples to obtain the

one correct solution of where the spill occurred, as opposed to an investigation into a socially

situated problem. However the problem-solving approach tended to differ among high school

participants. As such, we focused the subsequent investigation of high school usage on weighing

the potential value of interview data in context with the quantitative data. Also, given the broader


29/58

29

audience in these cases, we pay additional attention to the quantitative reasoning applied by the

high school students to understanding the patterns in the data. In these case studies, we focus

more specifically on group talk to examine the processes by which the problem was framed.

Across the groups we examined, four main motifs emerged in the talk: (1) Negotiating the

environment in the investigative process, (2) Within and intergroup interpreting the problem as

gathering information to complete a puzzle, (3) Discussion and problem solving which integrated

the physical world, paper-based resources, and PDA-mediated resources, and (4) emerging of

inter-group power dynamics. This section reports results primarily from two groups, which

were chosen to represent the ends of the spectrum of responses. One group (group 1) struggled

with making sense of the quantitative data patterns as well as integrating the quantitative and

qualitative information. The other group (group 2), while unable to fully address the problem,

demonstrated significant success in finding patterns in the data, and identifying where additional

research was needed. In this section we use a brief discourse analysis to examine emergent

learning practices.

In the following passage, group 1 discusses the best method for reaching an interview

with an expert who is in the horse farm. Several physical structures enter their thinking.

1. Stacey: Theres a fence there. I cant get over it.2. Gina: Then I dont know what were going to do. Were stumped. Lets call the

guy [facilitator on the walkie talkie] so we can find out what were doing.3. Stacey: What does it look like?4. Gina: Were close. Thats the thing.5. Stacey: Ok, fine. Can we go over this [barbed wire] fence?6. Gina: I dont know.7. Stacey: Maybe we can get on the other side by walking somewhere else.

8. Louis: Maybe we can walk the fence. No, there are trees.

Environmental constraints and affordances immediately had an impact on students problem

solving process. The constraints of the environment, namely fences (1,5,8) barbed wire (5), and

trees (8) guide their problem solving path. All of Ginas statements are declarative, assessing


30/58

30

their progress and directing activity, whereas other students raise ideas as suggestions, couching

them with qualifiers (i.e., maybe). The problem is about designing strategies in relation to local

environmental affordances.

Roughly ten minutes into the activity, students in this group (1) have negotiated the

particulars of the environment, with Gina having taken a lead in defining group work. They

conducted their first virtual interview and now meet another group (group 3), who asks them

how many interviews they have gathered. A shared understanding emerges whereby the point of

the activity gets framed as collecting boxes (the screen icons which correspond to virtual

interviews), akin to a scavenger hunt.

9. Girl (group 3): How many [interviews] did you get so far?10. Louis: None, nothing.11. Stacey: Weve only gotten one box. How many have you got?12. Girl (group 3): One so far. We were going for another one.13. Boy (group 3): Three. Oh. You meant the boxes?14. Gina: Did you dig?15. Boy (group 3): Yeah.16. Gina: Can you dig anywhere?17. Boy (group 3): Yeah. I think so -- I did.18. Gina: Cool. We got an interview. Thats all we did. We dont have

much time. We have to go.

The girl from group 3 initiates the conversation by asking how many they got so far, framing

the problem as one of collecting the most interviews as efficiently as possible, and establishing

the activity as one of collecting boxes. Gina turns the topic to digging, but group two offers

little information on what they dug. Gina does not pursue the conversation, and declares that the

team is running out of time and needs to go.

Shortly afterwards this group (1) sets out in pursuit of an additional site at which to dig.

Along the way they discuss the readings that they have received thus far.

Gina: So were digging a well at 144 [reading the coordinates]Stacey: And were near the chickens. [writing down notes]Gina: Sample sent to field lab. What does that mean?Stacey: Is there a location?


31/58

31

Gina: Oh no, what did we do?[Pocket PC sound effect Indicating a sample is available]Gina: Reading at whatever is 27. What does that mean? Reading at 140 94 is

27. Whatever that means.Stacey: So Im just going to say we dug a well at this spot and it was 27.Gina: Yeah.Stacey: Well, actually it was that spot. [pointing to where they dug]Gina: Yeah. And it got sent to the field lab.

Here we see that they are collecting additional data, but the incoming data are interpreted

merely as a stream of numbers. The students do not relate the readings to previous readings or to

the spatial arrangement of the readings. Here they also do not know what the numbers mean, but

do not identify that they need additional resources to ascribe this meaning. We compare this

with group 2 upon receiving their first data.

Abbey: The reading is 10.Maya: Ok.Abbey: We got a well reading of 10 so now we should find someone who can tell

us what that means cause we dont know.

Group 2 immediately identifies that they dont know what the readings mean and should

find someone that can help them with this interpretation. They go in search of someone (a

virtual character) who could possibly give them this information. A while later they get the

interview they are looking for and one of the researchers asks them about what they got our of

that interview.

Abbey: Information about wells and sending water samples to labs. But we needto get information about reading, like what the reading means. 10I haveno idea what that means.

They are able to identify that this interview gave them helpful information, but it didnt give

them the information that they need to provide some absolute meaning to the reading of 10. A

while later they obtain an additional data sample from a virtual well.

Abbey: Reading 56! Thats a lot higher than the 10. OkMaya: 15 (announcing a third new reading)


32/58

32

Abbey: 15. So it seems to be closer, higher when were near the water. And wereat a higher elevation here too. Do you want to head back?

Here Group 2 has obtained and interpreted information based on three readings (10,15,

and 56). They understand the geographic relationship of these points, such that the one that is

closest to the water source is the highest. Additionally they look at the physical landscape,

showing that the readings are highest at a high point on the landscape, which may have

implications for where the water flows.

As the groups work their way towards the end of the project, they try to interpret their

findings and decide what they are going to say when they present their recommendations and

evidence. On the way back, group 2 meets up with another group (4) and they discuss what they

have found.

Abbey: So what do you guys think, you know? About buying the land?Nick (Group 4): I didnt really find any overwhelming evidence that there is TCE

or any other toxic chemical.Abbey: Did you say you took just one reading?Nick: Yeah.Abbey: What did you get?Nick: 173?Abbey: It has a question mark. Wait, what does that Where did you?

[interprets the information in contrast to her own computer andperhaps determines that while group 4 has drilled one well, theyhave not taken a sample from that well, thus they have no realdata]

Brett: Id buy the property, because theres enough propertyAbbey: But if these animals are getting sick...? I mean liver problems?

Somethings up though. That librarian we talked to seemeddisgruntled, didnt she?

Here we see group 2 has collected more quantitative data, and made progress in

interpreting that information. Additionally they have obtained interviews from the characters

and integrated that information as well (referring to the disgruntled librarian). For group 4 there

was no connection between the disjointed (to them) information.

Similarly we pick up group 1 as they head back to the lab with the information that they


33/58

33

have collected. They have continued to struggle with making sense of the data.

Gina: I am so happy that we have at least one box.Louis: Yeah.Gina: And we have that it is the TCE chemical. That is what they think it is, so

we have something to say. I am quite happy about that.

While they are happy about collecting their information, they have not been able to

connect any of the pieces, either during the investigation or here as they attempt to offer

summative explanations.

The groups gather at the end of the experience to give their recommendations and share

evidence to the entire group. The teacher selects some groups to make oral presentations. One

of the members of the 4th

group (whom group 2 ran into before coming back) presents their

recommendation.

Nick: Ok, I think that the state should buy the land because theres studies thatshown that if theres TCE here it can be cleaned up effectively. TCE andCT and whole bunch of other chemicals can be cleaned up effectively. SoI see no overwhelming reason not to buy it because the problem issolvable.

He makes this recommendation without knowing anything about the data indicating what

is actually there, but surmises that whatever it was can be cleaned up. When asked if they found

any significant amount of any chemicals, he comments:

Nick: No, we didntLarge amounts of TCEI guess its only harmful if itslarge amounts or large exposures to it

Their teacher then asked them if they could define what large was.

Nick: No, no. We know that large is just big.

When probed further for their evidence of where they learned that the problem could be solved,

they cite a single interview.

Nick: The librarians down at the library said that at Cape CodI guess there


34/58

34

was a similar problem at the Massachusetts Military Reservationandthey cleaned it up. In Illinois also.

Their case hinges on the recommendations of one interview that they found. Subsequently the

reliability of this interview is questioned by one of the members of group 2.

Maya: The only thing about the Librarian is that she kept saying I think.. so itskinda like we werent sure if her information was exactly accurate. Thatwas just something that I noticed.

Here Maya, from group 2, shows that she is reading deeply into the information that she finds,

even questioning the language by which the librarian presents the data. Their more thorough

analysis and interpretation becomes evident in their recommendations.

Abbey: Ok, well, we didnt really come to definite conclusion. We foundreadings. One of them was right over by the water right before you go intothe tunnel and we got a reading of 50 [rounded from 56]. And our otherones were 10 and 15. So those ones are away from the water but, wecouldnt find anyone who could give us information about what thesenumbers mean, so we didnt come to any conclusion, because were notexactly sure how to interpret those, so were not sure if the land should bebought.

Their evidence shows patterns in the data, and also identifies the gaps in their information

specifically citing items where they need additional information. Unlike other groups, group 2

was very aware of the limitations of their knowledge and structured their recommendations

accordingly.

Group 1 did not participate extensively in the presentations, but did describe some of

their thought processes during the investigation.

Stacey: It was kind of confusing at first.Gina: It kinda seems like youre supposed to go on a certain path. Cause it

kinda seems like we took a reading and went to the next site, and it gaveus information about taking readings. But wed already done that. Itsjust, we had to stop

Through this dialog the group is indicating that part of their failure comes from seeing the

process as totally linear. They describe their experience as one in which they follow a path


35/58

35

through each of the different points in the game, as opposed to a dynamic process that evolves

over time as they collect more information and interpret that information.

The way in which each of the groups saw the role of the physical environment varied

greatly, potentially contributing to their success or failure in the investigation. Those who saw

the environment as a barrier, or simply couldnt incorporate the real surroundings, struggled,

whereas those who could read their physical surroundings incorporated it with the virtual

information that they collected to create a better response. Here we follow group 1 as they are

using real maps, the actual environment, and theEnvironmental Detectives-based maps

interchangeably. They just collected an interview, and are now about to get another one. The

students are concerned that they do not have enough information to solve the problem

adequately. We pick up the discussion as they decide what to do next.

19. Stacey: Lets go to that one [pointing to the learning center]. We just traipsedthrough a field.

20. Louis: I like how he [the character in the video] was standing up there [pointingtowards the house] and reading it.

21. Gina: Yeah, I know.22. Louis: He got to stand at the house and we had to stand in the water [in the field].23. Stacey: I know. I am so wet.24. Louis: My socks are so wet.25. Camera: We should head back soon.26. Gina: Yeah, it is 12:50.27. Louis: How far away is the thing [the location of the debrief]?28. Gina: Where do we have to go again?29. Stacey: Alan Morgan center? That is30. Louis: [Looking around]. Not around here.31. Stacey: Right here [points at paper map].32. Gina: And were right here [points at ppc].33. Stacey: Thats not bad.34. Louis: But we have to go through the tunnel.

35. Stacey: How are we supposed to make recommendations?36. Gina: I dont know.37. Louis: Just read off of the information that we got.38. Gina: I thought we could dilly-dally but we actually did work.39. Louis: For once.

Stacey initiates the conversation by suggesting that they go to the learning center, as the group is


36/58

36

tired of traipsing through fields, which got their socks wet. Louis notes that their path back

to the nature center will take them through the tunnel (34), a feature of the environment which

earlier had been the cause of considerable discussion, as a group of birds flew out and scared the

group. Stacey notes their lack of information (they had located several interviews, but dug few, if

any wells), and asks the group how they are supposed to make recommendations (35). As in the

other changes, Stacey queries the group for strategies, and Gina gives the response (36). Louis

(37) suggests that they just read off their information. Gina sums up the groups dilemma: they

thought that the exercise would be relatively thoughtless that they could just dilly-dally, but

instead, they actually did work, (38) which Louis agreed with (39). Students use maps (19, 31),

the real environment (20, 30), and PDA resources as tools (32) for communicating.

Later this group encounters another visitor to the site (clearly not from their class). The

visitor asks what they are doing.

Stacey: Were trying to find if there are any toxins here. Do you know of anytoxins?

Visitor: Toxins. I dont know of any toxins.Gina: It is in the game. I think it is all in the game.

The members of this team are negotiating the reality of the situation. The one team member

asks the visitor if he knows anything about toxins, as if the information were real and may be

accessible outside of the game. It is the other team member that suggests it is probably just in

the game.

In another discussion, one of the members of group 2 is pondering the dynamics of the

game.

Abbey: It would be cool if there were real people. Youve heard of SturbridgeVillage [a local living history museum]? They make candles and stuff. Itwould be cool if there were real people you could ask your own questions,you know?

This statement seems to suggest that she understands the simulated nature of the environment,


37/58

37

that the game enacts this situation just as actors do in a mock historical site and that the students

have some interest in expanding the experience beyond the virtual.

After the game and debrief are completed, the students are asked to reflect on their

experience. One of the boys from group 4 responds.

Nick: We didnt get to read everything, because we were just going (SNAPSTHREE TIME BOOM BOOM BOOM)running and getting chased bya guy with a knifewell, it was metaphorical knife. Maybe we couldhave all of the people in one room and talk to them all like arounddifferent places in the room.

Their teacher asks if they think that would have been better than the outdoor experience.

Nick: It would be more efficient, but maybe the point of it to go out and walk

around and see everything too. I dont know what the objective is, but ifthe objective is to get all the info real quick, then the best this is to do ithere [in one room].

This group has expressed that they dont know what the purpose of the outdoor portion is and

that if they were just expected to learn the information that it would have been more efficient to

give it to them. This failure to put the different pieces together the physical environment,

along with the virtual information, seems to have contributed to this teams failure to make sense

of the situation. One of the girls from group 2 responds to the same question about whether it

would be better to put everyone in one room. She suggests some things she may have learned

from doing the activity outside in the real space.

Maya: The way the water traveled? If we were up on the hill and the water wouldgo down.so we though if it was the water contaminating down

As the group debriefed, some students expressed value in working in the real world environment,

although these understandings were relatively shallow, showing the limitations of this particular

enactment for producing learning.

Cross Case Discussion


38/58

38

These cases suggest the opportunities and challenges to using handheld technologies to

situate learners in environmental engineering practices. These enactments of the curriculum

suggest how augmented reality simulations can create a compelling context for environmental

investigations. Taking learners into the field to conduct a virtual simulation enabled learners to

gain a situated experience of environmental science, although the value of this was not always

clear to students. This section further explores the significance of the activitys occurrence in a

real world location, exploring the role of the environment in students activity, challenges in

conducting virtual investigations, and the role of reflections on failure in learning within

augmented reality simulations.

The Environment in Augmented Realities

Across both high school and university students, we found that the teams had relatively

little difficulty negotiating the hybrid real and virtual components of augmented reality and

within minutes were diving into this mixed-reality environment. Students mapped virtual data

onto the real world context or pointed to locations in the real world and described the

concentrations at those locations using data and information off of the handhelds. Using maps

and computers, they continuously worked across the spatially distributed problem solving

context. More importantly, students often used knowledge of the surroundings to solve the

problem. The college students, who were more familiar with the environment than the high

school students (who were on a field trip), investigated sites of known printing presses, metal

shops, and other places with large machinery, which were identified as being associated with

TCE early on in the investigation. College students used hypotheses of the activities in each

building to guide their thinking, yet they were less personally connected to their surroundings.

Situating students activity in the physical environment where physical space is part of

the learning experience may be the strongest pedagogical value ofEnvironmental Detectives.


39/58

39

Across groups, students drew upon their existing knowledge of the terrain, chemicals, or

environmental problems associated with the area. The ease at which students synthesized

information from the physical and virtual environments suggests that a pedagogical benefit of

augmented realities may be in how it encourages learners to draw upon existing knowledge and

apply new information to understanding the world around them.

The high school cases show how the environment can function as a constrainer of action,

as in the first high school case, where students had to traverse rougher terrain. In this way,

environmental constraints affected their problem solving paths to an even greater extent. From

the first challenge of climbing a fence to the final challenge of negotiating a tunnel, students

problem solving was concrete, and specific environmental constraints (fences and trees),

affordances (such as the tunnel) and local demands (time considerations) were a part of students

thinking. Students rarely, however, used the physical environment to talk about toxin spreads, as

they framed the activity as collecting and synthesizing information rather than gathering data,

constructing a narrative and designing a solution. Indeed, the high school students generally

struggled to balance the need to gather background information with that of drilling and

sampling (as environmental engineers might predict). These students typically defined the

activity as a scavenger hunt where the moment-to-moment goal was to collect interviews as

quickly as possible. This meaning was created through both intragroup and intergroup

communications whereby students negotiated the focus of the activity as collecting information.

How and why the activity got framed as a scavenger hunt is the result of several factors,

including the nature of fieldtrip and students past experiences (as evidenced by Gina and Louis

comments that this actually was work. (38-39).

Augmented reality simulations may have communication advantages (i.e., gestures, facial

expressions) over their purely virtual counterparts. These groups debated in real time using their


40/58

40

voices, gestures and physical locations as tools. While similar representations exist in virtual

worlds, they require negotiated standards that must be adopted and accepted over time.

Emoticons in chat and hand signals by avatars are two examples of these emergent standards.

Students in augmented realities do not need to learn these standards, as evidenced by these cases,

since they employ the modes of communication with which they are the most familiar. More

importantly, group members frequently voted with their feet in determining the next location

to go. While this did not always result in democratic decision making (the person holding the

computer seemed to have a larger vote), it did make immediately apparent what peoples

opinions were and provoked critical dialog.

Conducting Virtual Investigations

A primary goal guiding the design of this project was to recreate core environmental

engineering practices (balancing multiple data sources and the evolving, competing needs of an

investigation) within a context where students could test out new ideas and identities without fear

of failure. The university and high school students encountered unique sets of difficulties in

trying to mount their investigations. Yet these different deficiencies lead to similar failures in

mirroring environmental engineering practice and ultimately determining a solution to the

problem.

The university students were driven almost exclusively by the collection of water quality

data from the wells. Most college students collected samples at the starting location or traveled to

where the initial reading was found. When students did conduct interviews, it was because

interviews were not coincidentally located near desirable sampling sites. In fact, each group

collected between 6-10 water samples before they ever determined what the units meant or what

level was considered toxic. This problem (not knowing toxic levels) was often discussed but

dismissed in favor of collecting more samples, perhaps hoping that a pattern would emerge that


41/58

41

would put the readings in perspective. In short, wherever there was a problem, the answer was to

drill more samples. The holes in students understandings were made more evident when they

presented their assessment and remediation plans. For example, several groups reported that the

TCE was unlikely to reach nearby surface water because it was far away, even though they did

not know how fast the TCE was moving or how long it had been in the ground (which might

indicate that it had already spread to the river). Other groups made assumptions about the use of

groundwater for drinking water, though they had no evidence to support these assertions.

When collecting water quality samples, the majority of un

ar simulations on handheld computers

Documents