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Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
Prototyping in place ii
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Prototyping in place ii

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  • Be chill.
  • In the past, if you wanted to play a location-based game like Geocaching you needed heavy and expensive GPS equipment. But with the widespread adoption of location-aware mobile devices, anyone with a Smartphone can play Location-based games. Popular games like myTown and Foursqure were created to meet the needs of a growing market. Extant applications, like Facebook, incorporated location to increase their appeal.
  • In many ways, Geocaching is the quintissential location-based game. A cache, or a waterproof container containing a logbook where players sign their name, is the central artifact in geocaching. Caches are hidden at different places around the world marked by GPS coordinates.
  • Players then use location-aware mobile devices to find different caches and “check into” them by signing the logbook and returning the cache to its initial position.
  • What if a geocaching game were created but instead of waterproof boxes, plants were used as “caches” for players to check into?
  • This is the premise behind Floracaching, a geocaching game for citizen science initially developed by Eric Graham and other researchers at CENS .
  • Scientists are particularly interested in plant phenology data, or data such as the date that a plant starts to flower, or the date that a plant starts to lose its leaves. Over time, if enough of this data is gathered, scientists can begin to form hypotheses about things like the dissemination of allergens and climate change.
  • Unfortunately, Floracaching existed only as the beta version of an Android mobile application and had significant issues with location-awareness. When some of the researchers met Eric Graham in 2011 we considered working together to update the Floracaching app. It quickly became apparent that building something new was going to be easier and possibly more effective than trying to fix old code. However, we weren’t sure about how to begin building a mobile, social location-based application.
  • There are a number of characteristics of location based apps and games that distinguish them from traditional desktop games and applications. A moble interface is unique in terms of size and portability. Instead of playing out in a single room, mobile games can be played anywhere a user can carry a smartphone. Because of these and other differences, the activities utilized in mobile games– especially mobile location-based games– are different. Many LBAGs support in-game social interaction, but over the course of gameplay players may interact with others who are not playing the game as well. Finally, lBAGs play out over longer time frames– typically days, or even weeks, instead of hours or days.
  • Previous researchers have looked at many these factors, and designed both toolkits and frameworks for prototyping different aspects of them. For example, “My Experience” is a toolkit for gathering subjective and objective field data on mobile devices. However, no approach have been suggested for LBAGs address all five factors and support multiple phases of prototyping.
  • And so, we developed PLACE as an approach to prototyping the crucial aspects of location-based apps and games: namely, location, activities, collective experience, and experience over time. PLACE is scalable. PLACE is a mixed-fidelity approach because any aspect of a prototype can be characterized as lower-or higher- fidelity at any given time. Place is scalable, because prototypes generally increase in fidelity over time.
  • This last part is key. “If you understand this graphic you understand the core ideas behind PLACE.”
  • PLACE is a set of elements, but also a set of principles, or best practices that correspond to the different aspects of location-based games.
  • 6 sessions total. Phase I, Phase II. Phase I split gorups, Phase 2 total. Two universities.This allowed us to schedule our relatively short sessions based on each groups expertise. For example, we spent more time describing how to scan QR codes with our plant experts, and more time describing how to classify plants with our group of technology enthusiasts.
  • Even though we held 6 total sessions, this was not an experimental design. We used the six sessions to generate independent data about to unique user groups. Conducting multiple sessions also allowed us to use the lessons learned from one evaluation session to influence both design of the floracaching game and the design of future evaluation sessions.
  • Lets return to the idea of a floracache, or a single plant of interest, to illustrate how PLACE can scale up over time.
  • In Phase I, floracaches consisted of plant mounts or high resolution photos of plant mounts attached to QR codes, which users scanned with their mobile phones to check in to the floracache. Early sessions were held indoors, and floracaches were placed on the walls of a building. We typically used two floors of a building and clustered some plants to represent forests in our phase I prototyping sessions. Phase I sessions were short and relatively structured.
  • In phase II, we took the experience outside and began to use actual trees to represent floracaches. However, we still used QR codes for checking in. The QR codes in this phase were placed on a garden stake adjacent to the plant. Location was scaled up to be an entire university campus. Activities were refined slightly. Time frame was increased to a week. To increase the fidelity of collective experience, we encouraged users to play with their family and friends and we let other users join halfway through the prototyping phase.
  • This is our Phase III prototype, which we began working with in early April and is not described in this paper. In this prototype, the QR codes are gone and unmarked trees serve as floracaches, as in the final version of the game. Location is increased to an entire metro area. The majority of activities carried over from Phase I to Phase II. Time and collective experience are nearly identical to the conditions of the final floracaching game.
  • Make “l” “m” and “h” low. Put in other slide before this one. Take out “Iteration in design” talk a bit about activities here
  • As mentioned earlier, PLACE is both an approach and a key set of principles. These are principles that we identified as crucial to protoptying LBAGs and evaluated while Prototyping PLACE. We present our “results” by describing how each of these key principles played out in our work.
  • In Phase I, we included a dicotomous key to help users classify plants because we thought it would help our users. Our technology experts found the key annoying, time consuming, and too technical to be of use. Our plant experts already knew how to classify the majority of the plants that they visited. By starting small and caling up the fidelity, we learned that a dicotomous key was unnecessary in the lowest-fidelity protoytpe, when the key consisted solely of a printed out sheet of paper with classificaiton. This saved us considerable time coding a dicotomousclassificaiton key for later stages of the app.
  • What people liked or didn’t like about the game itself, not just the game’s look and feel.
  • Treating participants as co-designers increased the quality of insights that we received. For example, tecnology experts extrapolated on both their own needs and the needs of plant experts, saying things like “well I didn’t want to validate a user’s identificaiton but if I knew something about plants I probably might.” More importantly, users really enjoyed the prototyping experience. The used both surveys and focus groups to thank us for letting them to be a part of their work, which probably happens less frequently with traditional usability testing. A few users also came back to participate in higher-flidelity sessions.
  • In the image on the left, it’s very clear where the floracache is because it’s marked with a garden stake containing a QR code. On the image on the right, the Floracache “Birch tree #26” could refer to any of these trees, and google maps granularity is insufficient to point to a single tree. As many researchers before us, testing in a representative space exposed us to issues with our prototype that we woudn’t have encountered in classroom sessions alone. Now, when it’s necessary to distinguish between similar plants, we include descriptions like “the one directly to the left of the park bench” to point to designate the Floracache.
  • The picture on the right shows an alfalfa plant. Alfalfa is the name of a character in the movie Little rascals, and one of our participants made this connection by leaving the movie title “little rascals” in the comments section. Other users told us in surveys and focus groups that they thought this was really cool and liked using comments to talk to other players. WE didn’t predict that this type of social interaction would take place, and likely would not have discovered it if we hadn’t tried so hard to represent authentic social experience.
  • Our last principle is “represent time authentically”. In our weeklong session, we started to see how people would use Floracaching in their day to day lives. This graph shows two distinct types of check in patterns. Users 1 and 3, represented by blue and green, checked into one floracache every few hours. This suggests intermittent use, like by photographing plants while walking to class. User 2, represented by the red line, checked into 5 floraachines in a single hour during the evening. This suggested that Floracaching was a sort of destination activity played during free time and not while doing other things.
  • We have recently cemented a collaboration with Project Budburst, a citizen science project with no mobile application but a very large user base of about 16,000 people. Floracaching has been rebranded as “Biotracker” and will now serve as the official Budburst mobile app to generate plant phenology data for the project budburst database. You can see our Phase III prototypine of Floracaching by following the link below.One area that we’re interested in exploring further is mobile applications for fitness. In terms of evaluating PLACE, we hope other researchers will try out.
  • Add in: you’re collaborating with project budbrust because they have a large user base. Not too . “it-er-i-tive”. Jenny really hates the black and white. UX testing talk more about.
  • ”.
  • ”.
  • Transcript

    • 1. Prototyping in PLACE: A Scalable Approach to Developing Location-Based Apps and Games Anne Bowser*, Derek Hansen+, Matthew Reid+, Jocelyn Raphael+, Ryan Gamett+, Yurong He*, Dana Rotman* & Jennifer Preece* *University of Maryland +Brigham Young University
    • 2. Overview Location-based apps and games (LBAGs)
    • 3. Geocaching Basics
    • 4. Geocaching Basics
    • 5. Geocaching…
    • 6. Floracaching
    • 7. Floracaching
    • 8. Floracaching
    • 9. LBAGs are different.
    • 10. Project Descriptiion Application domain My Experience (toolkit) Capture field data with a context aware platform General prototyping and evaluation ContextPhone (toolkit) Provide context by simulating GPS General prototyping and evaluation; Pervasive computing ActivityDesigner (toolkit + framework) Consider real life activities as they play out over time in realistic locations Ubiquitous computing Trajectories (framework) Consider how users move through space, time, activities, and interfaces Augmented reality Prior Research
    • 11. A scalable, mixed-fidelity approach to Prototyping Location, Activities, and Collective Experience over Time Introducing PLACE:
    • 12. Interface Scalable 5 ways
    • 13. PLACE Principle Elements 1 Start small and scale up the fidelity All 2 Treat participants as co-designers All 3 Test in a representative space Location 4 Focus on activities more than interfaces Activities 5 Respect authentic social experience Collective Experience 6 Represent time Authentically Time Elements & Principles
    • 14. Plant experts Technology experts Plant experts Technology experts Mixed group Mixed group Evaluating PLACE with Floracaching Phase I Phase II Key University A University B
    • 15. Session Participants* Demographics University A Phase I 7 (2) Male: 1, Female: 6 Plant Experts: 7 University A Phase I 7 Male: 7, Female: 0 Plant Experts: 0 University B Phase I 9 (1) Male: 2, Female: 7 Plant Experts: 9 University B Phase I 11 (2) Male: 4, Female: 7 Plant Experts: 0 University A Phase II 14 (2) Male: 9, Female: 5 Plant Experts: 2 University B Phase II 10 (2) Male: 1, Female: 9 Plant Experts: 5 All sessions 58 Male: 24, Female: 34 Plant Experts: 22 *Including (design team) Method
    • 16. Method Qualitative Research Observation Focus groups Surveys Behavioral trace
    • 17. A sample floracache
    • 18. A sample floracache lowest-fidelity (Single building)
    • 19. A sample floracache mid-fidelity (College campus)
    • 20. A sample floracache highest-fidelity (Metro area)
    • 21. Lowest- fidelity Mid- fidelity Highest- fidelity Introducing PLACE
    • 22. Lowest- fidelity Mid- fidelity Highest- fidelity PLACE in action
    • 23. Lowest- fidelity Mid- fidelity High- fidelity PLACE in action ✚ Highest- fidelity
    • 24. Results What can we learn from prototyping with PLACE? PLACE Principle Elements 1 Start small and scale up the fidelity All 2 Treat participants as co-designers All 3 Test in a representative space Location 4 Focus on activities more than interfaces Activities 5 Respect authentic social experience Collective Experience 6 Represent time authentically Time
    • 25. #1: Start small and scale up the fidelity Classification of Key Evergreen Trees in Utah 1. a. Leaves scaly-like; cones are small; blue and berry-like…………………………… go to 2 b. Leaves needle-like; cones are large and brown……………………………………… go to 3 2. a. Leaves rough; berry-like cones are about 1 inch in diameter; trunk is forked………………….……………………………go to 17 b. Leaves smooth; berry-like cones less than 1 inch; trunk has central stem…...Mountain Pine
    • 26. #2: Focus on activities over interfaces
    • 27. #3: Treat participants as co- designers
    • 28. #4: Test in a representative space
    • 29. #5: Respect authentic social experience
    • 30. 0 1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Numberofcheckins Time (hours) User 1 User 2 User 3 #6: Represent time authentically
    • 31. Future Work http://biotracker.byu.edu
    • 32. Prototyping Location, Activities, and Collective Experience over Time • PLACE is an iterative, mixed-fidelity approach • Researchers should scale up PLACE in accordance with their unique needs • PLACE can be used with other frameworks or toolkits • PLACE does not incorporate traditional usability testing
    • 33. Acknowledgements Thank you Biotracker Researchers; Project Budburst; co-design participants; Eric Graham This work was funded by NSF grant SES 0968456
    • 34. Thank you! Who’s feeling curious today?

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