EcoRace: How a Board Game Can Influence Eco-Friendly Car Purchases

By Paul Choi and Miguel Garrido

For several decades, motor vehicles have been a major source of greenhouse gas (GHG) emissions and pollution in the US. According to the EPA, in 2015 the transportation sector accounted for about 27 percent of total U.S. GHG emissions, second only to the electricity sector. Scientists have long emphasized the adverse effects of vehicle emissions, since GHG emissions cause global warming and drive climate change. Accordingly, U.S. public policy has in recent years aimed to increase the fuel efficiency of motor vehicles.

Yet the effects of vehicle emissions on human health remain significant. Air pollution poses a major risk to public health, and major studies have established a strong link between vehicle emissions and illnesses such as asthma, cardiovascular disease, diabetes, and lung cancer. However, consumer surveys indicate that most car buyers don’t consider these health effects when making purchasing decisions.

Moreover, fuel efficiency ranked 8th out of the top 10 factors that consumers consider when buying cars. This is troubling given that the fuel economy of a vehicle is a high-leverage point that can substantially reduce tailpipe emissions and thus improve public health.

EcoRace: A Board Game to Influence Car-Buying Decisions

We designed a board game called EcoRace to address the two primary problems outlined above. First, fuel efficiency is currently not one of the primary factors that consumers take into account when buying a new car. Second, although the effects of vehicle emissions on global warming have been well publicized, the impact on human health remains unclear or unknown to a lot of people.

EcoRace is a game played with two teams of two players each (it is cooperative among teammates yet competitive among teams). Each team has six cars (3 cars per player) of different fuel efficiencies: low, medium, and high. The objective of the game is to get all six cars to the finish line before the other team.

The rules of the game are simple: first, one player chooses a car to move and rolls the die. The player then moves the car on the board by the number displayed on the die multiplied by the MPG of the car (1 for low, 2 for medium, and 3 for high fuel efficiency). Then a player from the second team choose a car to move and rolls the die, and teams take turns in this way to move around the blocks.

To promote cooperation among teammates, players can choose to move two cars together if they land on the same square (this is an analogy to carpooling in the real world). Hence, strategic decisions about moving specific cars and waiting for your teammate to go move together occur throughout the game.

Additionally, the game includes 12 specific “Chance” blocks, which require the player that lands on them to pick up a Chance Card and read the instructions. The Chance Cards are data-driven and provide impactful statistics on the health effects of vehicles emissions. They reward fuel efficient cars and punish low fuel economy cars.

Audience and goals

The primary audience for this board game is young millennials who are considering buying a new car. We picked this demographic because their car-buying behavior can yield important insights about the future of vehicle emissions in this country. On one hand, studies indicate that the recent recession, coupled with the meltdown of the auto industry in 2009 and the rise of ride-hailing apps such as Uber, caused a stark decline in car ownership rates among millennials. Yet on the other hand, recent data indicate that millennials aren’t ditching car ownership altogether – they are simply delaying it.

However, surveys indicate that the health impacts of vehicle emissions, and fuel efficiency in general, are not key factors that millennials take into account when making purchasing decisions. Instead, they focus on features such as navigation system, satellite radio, Bluetooth, and mobile integration.

Our goals for EcoRace are thus threefold, each corresponding to a different time horizon. In the short run, we hope that millennials who play this game will understand the link between vehicle emissions and health problems. We believe this link is critical to making fuel efficiency a key buying factor, since that is the primary mechanism though which tailpipe emissions (and adverse health effects) can be reduced.

Our medium-term goal for EcoRace is to actually influence eco-friendly car-buying decisions among millennials. Specifically, we aim to make fuel efficiency a top factor (at least in the top 3 features) that they consider when buying a vehicle. In the long term, our hope is that millennials will choose to drive their fuel-efficient cars less and even ditch gasoline cars altogether, instead opting for electric cars or public transportation (our final thoughts below expand on this idea).

Data: Making heath information central to the game

As mentioned above, the health impact of vehicle emissions is the key theme of EcoRace, and we chose to make the health information central to the game by directly incorporating it into the Chance Cards, thus influencing the actual decisions that players make when moving their pieces along the board. An example of a chance card is:

Hazardous air pollutants (toxics) have been linked to birth defects, cancer, and other serious illnesses. The EPA estimates that the air toxics emitted from cars and trucks account for 50% of all cancers caused by air pollution. Your vehicle missions have contributed to increased cancer rates in your community.

If your fuel efficiency is low:  go back 3 spaces

If your fuel efficiency is medium:  go back 2 spaces

If your fuel efficiency is high, go back 1 space

Our chance cards cover a broad range of health impacts associated with vehicle emissions, from asthma to cardiovascular disease to diabetes to lung cancer, all summarized in a data-driven manner.

Testing the game

We tested EcoRace internally first, simulating several games using an early prototype to iterate and improve the pedagogical experience of the game. We then tested the game with four real players (from our target audience of millennials interested in buying a car in the near future). First, the players played a version of the game that was purely competitive (one vs. one), which did yield insights into the learning impact of the Chance Cards (understanding the link between vehicle emissions and human health, and incorporating fuel efficiency into purchasing criteria). However, the competitive aspect of the game did not enable us to promote cooperation, which more broadly speaks to the idea that working and coordinating with others (e.g. carpooling) can be a very effective means of reducing vehicle emissions.

As such, in our second round of testing, we incorporated a cooperative aspect to the game. Now two players would be assigned to each team, and each team would have to work together to strategize their moves along the way (e.g. which cars to move first, which squares to try to land on in order to carpool, etc.). We tested this second version of the game with four players and found that participants directly took into account the benefits of carpooling (e.g. moving two cars at the same time in this context) while still learning about the health impacts of different fuel efficiency levels among their cars. In the end, players viewed their least efficient cars as a nuisance and wished they could only drive cars with a high gas mileage.

To measure the success (or failure) of our game, we performed a simple pre-post interview to gauge the participants’ views regarding fuel efficiency. First, before they even knew what game they were going to play, we asked them to name the car they were most likely to buy (at least the general type) in the near future. Second, after they played one round of the game, we asked them the same question. According to our interviews, all of them said that fuel efficiency would likely be a key purchasing factor. Two of the interviewees even mentioned that learning about the adverse health impact of vehicle emissions would influence their future car-buying decisions, since they were thinking of having children soon.

Benefits of the game and concluding thoughts

EcoRace is a game designed to influence eco-friendly car buying by linking the adverse health effects of vehicle emissions to fuel efficiency. We believe it is effective because it promotes and rewards cooperation, raises awareness about fuel economy and its effects on public health, and provides data-driven mini-stories (in the form of Chance Cards) as part of a broader narrative (making it from home to the beach, which is the finish line in the game). It does so in a playful manner that still retains the key concepts we want millennials to understand about fuel efficiency.

As possible next steps, EcoRace can be improved in several ways. First, the link between the cars in the game to those in real life can be strengthened. Specifically, different car profiles can be developed that correspond to actual vehicle and truck types that consumers can buy, rather than abstract objects that simply have fuel efficiency levels of low, medium, and high. Second, more testing can be done to identify the target audience for this game. Millennials may be too broad a term, and the game may be more effective if we targeted a narrowly defined user (such as kids of a certain age range). Third, the game itself would have to be adopted by key customers in our target sector in order to actually make a difference. These are all possible directions that future enhancements can take with respect to EcoRace. However, we believe the version we’ve developed presents an effective and innovative way of influencing eco-friendly car-buying decisions.

Slide presentation located here

Data Sources:

http://www.nytimes.com/2010/01/13/health/research/13exhaust.html

https://www.healtheffects.org/system/files/SR17TrafficReview_Exec_Summary.pdf

http://www.ucsusa.org/clean-vehicles/vehicles-air-pollution-and-human-health#.WRziI8Zw-Uk

http://www.ucsusa.org/clean-vehicles/vehicles-air-pollution-and-human-health/cars-trucks-air-pollution#.WRzum8Zw-Uk

http://www.energyresourcefulness.org/Health%20Effects%20of%20Gasoline%20and%20Diesel.html

https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions

https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions#transportation

https://oemsolutions.agameautotrader.com/wp-content/uploads/2013/05/Millennials-Next-Gen-Car-Buyer.pdf

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1240770/

http://www.euro.who.int/__data/assets/pdf_file/0006/74715/E86650.pdf

http://www.ehrn.co.za/download/lecture_series_06.pdf

 

 

 

 

Hubway Class of 2017: Final Project

By Meghan Kokoski, Mikayla Murphy, Kimberly Yu, and Margaret Yu

Methodology

The main data source we used was the Hubway trips dataset, which contains the start station, end station, timings, and other information for every Hubway ride ever taken.

Early on, we identified that our primary audience was MIT students without a Hubway membership, and that our goal was to encourage these students to purchase annual Hubway memberships. To achieve this goal, we created a set of posters for the Infinite Corridor. Each poster focuses on a specific Hubway bike that plays a certain character in the “Hubway Class of 2017”. The characters were carefully chosen to emphasize unique parts of MIT culture (so as to be relatable to MIT students) while also having a strong data-driven story. We chose to represent the class of 2017 as the MIT class of 2017 is just about to graduate, making it the most current and relatable class. As such, we used Hubway data from September 2016 through February 2017 (the latest available Hubway data as of now).

Our first character was the Hacker bike, which is the Hubway bike that had the most trips at night. Using the dataset, we found that Bike 1738 had the most trips that started between 10 pm and 6 am, with 54 trips.

The second character was the Course 6 bike, which was the bike that had the most trips to or from the Hubway station at the Stata Center. Stata houses most of the Course 6 classes and professors, and Course 6 is the largest major at MIT, so we thought it would be especially relatable to most MIT students. Bike 1382 had the most trips to and from the Stata Center station, with 49 trips (24 trips starting from Stata and 25 trips ending at Stata) .

The third bike was the Greek bike, which was the bike that made the most trips from the main MIT campus to the two stations closest to the MIT Greek houses across the river. The MIT stations were defined as the Stata Center station and the Mass Ave/Amherst St station, and the Greek stations were defined as the Kenmore Square station and the Beacon St/Mass Ave station. Bike 640 had the most trips between these stations with 55 trips.

The last bike was the Firehosed bike, which was defined as the bike that was most busy (aka took the most trips). Being hosed is very relatable to MIT students, so we hoped they’d empathize with Bike 1395, which took 701 total trips between September 2016 and February 2017.

To support each of the stories, we added a second layer of information about biking and Hubway linked to each character. For example, for the Firehosed bike, we added facts about how biking and being outdoors decreases stress, because hosed students are often stressed. For the Course 6 bike, we talked about the environmental impacts that biking has, as Course 6’s are trying to change the world technologically, so why not change the world environmentally too? For the Hacker bike, we added facts about safety, as safety is an important part of the Hacker Code of Ethics, and for the Greek bike, we focused on the time savings, as students who live across the river often complain about the commute time required.

Impact

The four Hubway Class of 2017 posters would be displayed on bulletin boards in the Infinite. Our audience is MIT students who are potential annual Hubway subscribers. Our goals are to raise awareness of the Hubway service, increase Hubway annual memberships, and lower CO2 levels.

We interviewed twelve MIT students who do not have an annual Hubway membership. Before showing them the posters, we asked them the following pre-questions:

  1. If you bike, do you own a bike?
  2. Have you heard of Hubway?
  3. Have you ever used Hubway before?
  4. Do you have a Hubway annual membership?
  5. If not, how likely are you to get a Hubway annual membership? (1 – not likely to 5 – very likely)
  6. If not, why do you not have a Hubway membership? Why do you not already have a bike?
  7. If you had to go to Harvard Square, how would you usually get there? (bike, bus, T, car, walk, etc.)
  8. Which of these methods of exercising are you most likely to do this weekend: jogging, walking, biking, or something else?
  9. How useful do you think biking is? (1 – not useful to 5 – most useful)

We then showed them the posters and asked them to imagine them displayed in the Infinite. After they examined the posters, we asked the following post-questions:

  1. (If they didn’t already have Hubway) How likely are you now to get a Hubway annual membership? (1 – not likely to 5 – very likely)
  2. After seeing these posters, are you more likely to bike to Harvard Square? (1 – less likely to 5 – more likely)
  3. Are you more likely to go cycling as a form of exercise this weekend? (1 – less likely to 5 – more likely)
  4. How useful do you think biking is? (1 – not useful to 5 – most useful)
  5. What do you like about the posters? What do you think is most effective?
  6. What do you not like about the posters? What do you think is least effective?
  7. Did we address your concerns about using Hubway?

From the pre-questions, we found that most MIT students have heard of Hubway but are not very likely to get a Hubway membership. The primary reason they do not have a membership is that they seldom go off-campus. We also found that MIT students would most likely take the bus or walk to Harvard Square from MIT, and would most likely walk to exercise over the weekend. They all agree that biking is very useful. After viewing the posters, they were slightly more likely to get a Hubway annual membership. The posters did not affect the likelihood of biking to Harvard Square or cycling to exercise over the weekend. However, their perception of the usefulness of biking increased slightly.

From the feedback on our posters, we learned that MIT students felt more connected to the Hubway service because of the MIT-affiliated bike names and the cute designs. The Course 6 bike and the Firehosed Bike appealed to the most people because they directly addressed the impact of Hubway use on climate change and health. MIT students liked the color scheme and found the layout of the information easy to follow, and the quick facts easy to learn. However, they thought some posters had a lot of text, and they probably wouldn’t stop to read the posters in the Infinite. Although the time comparison was helpful for understanding the usefulness of biking, some people thought it would not be worth it to arrive at an event sweaty from biking, which only saves 2 minutes. MIT students who were not very familiar with Hubway had difficulty understanding the bike id numbers. They were also concerned about the station locations, and one student mentioned how, according to a friend’s experience, the Hubway bike pedals don’t accommodate short people. For the most part, our posters were able to address MIT students’ concerns, particularly in terms of saving time and improving health, and made people seriously consider why they do not have a Hubway annual membership.

Itinerarie

Sharlene Chiu, Lawrence Sun, Tricia Shi, and Zachary Collins

 

Methodology

For our final project, we iterated on the participatory game sketch the “Amazing Race,” changing the name to “Itinerarie.” The data shows that personal vehicles produce a large amount of carbon emissions. Choosing public transportation or other more environmentally friendly modes of transportation can have a major impact on air pollution. Convenience, time and cost are factors that make picking the “greenest” forms of transportation not always practical. There are times, however, in which we can reasonably select between a variety of options. The amount of carbon emissions we can prevent is actually quite shocking. If everyone were to think of the environment when making these decisions, the aggregate results could be huge. Our fully realized sketch is a text-based game that forces our audience, i.e. MIT students, to think of these trade-offs and understand how their decisions impact the environment. We created a web application as the medium for the game to be played, allowing people to play it via their personal computers or mobile devices.

Link to Game: https://itinerarie.herokuapp.com/

At the start of the game, users are presented a list of seven activities such as “Grocery Shopping at Shaws” and “Visiting the Museum of Fine Arts.” Users are told to select three activities they may perform in the upcoming weekend. Then, for each one, the game asks users how they would get there. Users can select between walking, biking (through Hubway), using public transportation, and calling an Uber. Beside each transportation option are the associated estimated prices and travel times. After selecting the mode of transportation for each activity, users are then reminded that the environment is important and are told to repick keeping it in mind as well. The same activities and transportation options are shown again, but this time with the approximate carbon emissions alongside each option as well. Finally, the user is shown the difference and resulting impact changing such decisions would have.

The data used to build the app came from a variety of sources. For each of the destinations, we needed to obtain the cost, time, and carbon emissions associated with each of the given modes of transportation. We also utilized other measurements such as the amount of carbon absorbed by a tree per year in creating our results page.

We obtained, from a report done by the Federal Transit Administration, the average pounds of carbon dioxide per passenger mile released from private auto and public transit. We operated under the assumption that the carbon contribution of walking and biking was zero. We used Hubway, Uber, and MBTA estimated fares when taking trips to find the associated price for each of the possible destinations we incorporated. We operated under the assumption that walking comes with no monetary cost. We used Google Maps to gather the estimated time it would take to walk, bike, use public transportation, or drive to each of the destinations we provided. All of our metrics used the Student Center as the starting point. Finally, using the fact that a mature tree consumes up to 48 pounds of carbon dioxide per year, we were able to convert computed carbon emissions into the number of “trees worth of work” per day. All of our computed numbers and metrics can be found in the following Google Sheets file.

Link to Data File: https://docs.google.com/spreadsheets/d/1rgv9Ryvrx7l6KThole9vDhEYG0xEXWgd2HBasIgi1xE/edit#gid=0

 

Impact

We wanted our project to change the way users think about how their transportation choices impact the environment. In the short term, we hope to reveal to them how much each of the prescribed options emits, clarifying why always taking an Uber might not be the most environmentally conscious choice, especially over time. In the long term, we hope to convince them to make the more environmentally friendly transportation decision when they can reasonably do so. Just as we bring to light in our project, if everyone made these choices, we would save a considerable amount of pollution from entering the atmosphere.

Our target audience for this project are MIT students. This allows us to focus in on a group that will often go to the same places and make the same transportation decisions. Using the Student Center as a point of reference allowed us to produce numbers that both make sense and are applicable to everyone who we expect to play the game.

To gauge the impact our game could have, we performed two sets of systemized tests. For a more general and loose experiment, we sent the link to our web app and an anonymous survey to many of the dorm mailing lists. This experiment was used to gauge participant reactions to playing the game. Our web app logged over 200 plays and we received over 130 responses to our survey. We used Google Analytics to record the actions and selections users made.

As users played our web app, we recorded the modes of transportation used but not the locations they specified for anonymity. Below is a table tabulating the selections our users made:

First Run Second Run Change
Walk 310 359 +15.80%
Biking (Hubway) 31 70 +125.80%
Public Transport 201 140 -30.30%
Car (Uber) 63 37 -41.30%


From the data we can see that once the users are made aware of the impact of their decisions on CO2 emissions, they decrease car and public transportation usage in favor of walking and biking. Public transportation usage decreased less than Uber usage did as it is less harmful to the environment. The data tells us that on their second run, users had on average
35% less carbon emissions than their first run, demonstrating that once users learn more about CO2 emissions they can effectively make use of their knowledge to make better decisions.

Based on the anonymous survey results, we concluded that the game indeed met our short-term goal of improving how well people understood the impacts of their transportation decisions. Prior to playing the game, about 77.8% of participants had at least an okay understanding of transportation carbon emissions. Afterward, that percentage increased to 82.5% of people understanding at least a good amount about the impact of their transportation decisions.

Interestingly, the number of people who marked the two option which indicated the highest knowledge decreased after playing the game. 50.4% of users said they had a solid intuition or knew everything coming into the game, but only 42.6% marked similar options after playing the game. This is most likely a case of where users thought they knew a lot going in, but once they saw the data they realized they knew less than they thought, in which case our game still meets our goal as users are still becoming more knowledgeable about the impact of their transportation decision.

Some survey respondents critiqued the effectiveness of the web app in terms of educating users and inspiring better transportation decisions. However, these respondents tended to walk and bike to different places, so their transportation decisions are already generally environmentally friendly.

For a more controlled experiment, we set up our web app in Lobby 10 and got people to play the game. We first asked them a few questions to get a better understanding of how they make transportation decisions. They then played the game and were asked a few more questions to gauge their reactions to the game and the effect it might have had.

Prior to playing the game, we asked participants what form of transportation would they go to use when trying to visit a local place off campus. After playing, we asked them if they felt their knowledge on the information displayed changed. We also asked the initial question again to see if their answer changed.

We found that when people were flagged down to play the game and answer our questions, they rushed and weren’t really engaged. When people came over voluntarily, the game proved short enough for them to stay focused while completing it. Those who generally would walk or bike did not really change their opinions after playing the game. While they thought they gained a better understanding of the numbers presented, their choice of transportation remained walking or biking. They did not find playing the game very meaningful. One user, who selected walking for every option, said that, “I don’t know how useful this is….. I obviously know that cars are less eco friendly than walking or biking and I don’t feel like the actual numbers changed my opinion all that much. Sorry– it was a beautiful app, though.”

Those that said prior to playing that they tend to Uber, even close by, were more surprised by the numbers presented. They felt that the tree analogy opened their eyes to show how even small changes in transportation actually amount to a lot. Most, however, said that, while they might be more conscious of the effects, they probably won’t change the way they’d get around in the long term. One user remarked that, “It’s kind of scary the numbers if you live this lifestyle, like the number of trees,” but said that after playing they’ll likely still Uber to get around.

Overall we felt that the prototype of our game met our short term goal of making users more conscious of how their transportation decisions impact the environment. The “trees worth of work” analogy rang home with many and seemed to at least make them think about how they’ll make choices in the future. It does seem that it wasn’t very successful at meeting our long term goal of getting users to change the way they’ll make decisions in the future. Many admitted, that although the numbers surprised them, they’ll probably still make the same choices in the long term. We think that making the game provide more personalized tips or using it to help destigmatize the downfalls of “greener” transportation options might help us move toward better achieving our long term aims.

Presentation: https://docs.google.com/presentation/d/1OQkbw-zwaQ3KyszTqNHx0M1SEdtnN6UBe5CZyTPW8kc/edit?usp=sharing

Extending and Reworking “Polar Bear and Glaciers: Seal Your Survival”

by Margaret Tian, Tina Quach, Tony Zeng, Willie Zhu

Depiction of our game in progress.

Intro

Our project was a physical board game titled “Polar Bears: Seal Your Survival” that aimed to teach kids about the impact of global warming on the Arctic. We focused on making the game engaging, by emphasizing interactivity. The board game format is well-suited for kids, because the short play sessions are able to hold their attention, while still teaching them about global warming. See images of our game in this deck of slides.

The rules of our board game are linked here. We generally modeled our game off of Candyland. In each round, the players were pregnant polar bears trying to gather enough food to survive the winter by collecting 8 seals before reaching the end of the game. There were 3 rounds overall that corresponded to the summers in 2012, 2014, and 2016 in the Bering sea. Our board featured two types of tiles: water and ice. The number of ice tiles decreased between rounds to symbolize the melting polar ice caps. Players rolled two dice to move, and drew a corresponding ice or water card. The ice cards generally gave better results than water cards (i.e. more likely to gain seals or experience other good events) since it’s easier for polar bears to hunt and survive on ice.

To give kids an idea of how melting Arctic ice connected to the rest of the world and generally educate them on fighting global warming in their daily lives, we also mixed in “fight global warming” cards into each deck. These cards had questions about global warming that all players had to work together to answer. If correct, players would either gain seals or add ice onto their board. A lot of time was spent calibrating the distributions of cards to make the game challenging yet still enjoyable.

Methodology/Data

Our data sources included NASA Arctic ice coverage data and many online articles about global warming, polar bears, arctic wildlife, and climate change.

We worked with NASA Arctic ice coverage data (csv) in order to correlate difficulty of our game with shrinking ice caps. We used ice cap data from summers in the Bering Sea in 2012, 2014, and 2016. Without needing to clean the dataset, we found that the amount of ice decreased 25% from 2012 to 2014 and 15% to 2014 to 2016.

The area of ice caps during summertime in the Bering Sea decreased 25% from 2012 to 2014 and 15% to 2014 to 2016.
The area of ice caps during summertime in the Bering Sea decreased 25% from 2012 to 2014 and 15% to 2014 to 2016. 

The changes between each “round” of our board game were based on ice cap data. The depicted decrease in ice from 2012 to 2014 to 2016 is reflected in our game as users start off with all tiles as ice and must add water tiles in every round (reducing access to ice tiles). This affects game difficulty because ice tiles have more cards with positive consequences (such as +1 seal or +2 seal) than water tiles do. Our game started with 70 tiles of ice, which decreased to 54 and then 36 ice tiles.

We also pulled from online sources–ranging from news websites to advocacy groups websites to informational websites about animal habitats–to get facts on polar bears and global warming. With the intention of integrating these facts into our ice, water, and global warming cards as well as the rules of the game, we compiled a database of card content that can be seen in this spreadsheet, which includes citations and links to our data sources. This research affected our rules–we determined that users would need about 8 seals to survive per round based on the fact that pregnant polar bears need to 400 lbs of fat to survive the winter and each seal is on average 50 lbs.

Analyzing our Impact

Audience

Our audience is 11 – 14 year olds who like animals may have heard about the impact global warming has on animals, but have not really internalized its devastating impact and ways in which they can try to fight it. Our overall aim is to use the specific example of melting ice caps and polar bears to teach these youth about how global warming hurts the animals they care about.

Goals

Our goals can be broken down into short term, medium term and long term goals:

Short term:

  • Players should recognize that global warming causes melting ice that impacts wildlife.
  • Players know at least 3 ways you can fight global warming.

Medium term

  • Players will tell their parents and/or friends about global warming.
  • Players should believe that they can make a difference against global warming.

Long term

  • Players will change their behavior to work against global warming (e.g. choosing eco-friendly transportation, reducing overconsumption and waste, etc.)

Play Testing

In order to evaluate the impact of our board game in promoting a fight against global warming and strong understanding of global warming’s impact on Arctic wildlife, we ran through one full gameplay session with three 7th grade kids from the local Cambridge area.

We found that these 7th graders had fun with the game–upon finishing the game, their immediate response was that they would play it again. However, we did notice that kids didn’t really read the facts that came along with every card in the game (drawn on each turn). Only one of the kids glanced at facts on cards.

However, another aspect of the game, adding water tiles in 3 successive rounds to model increasing difficulty over time, was effective, as one kid commented that they didn’t like water tiles because they made it harder to win, just as melting ice makes it harder for polar bears to hunt. Additionally, global warming cards that were meant to encourage the kids to engage with questions of global warming’s impact and the actions they can take, were harder than intended. This supports our game’s potential for impact in that these hard questions, although potentially discouraging, can really teach those that play the game. Play testing also revealed that, it’s a challenge to make kids consume information if it is optional to–even if the information has been integrated into a game as in ours.

Evaluation

In addition to analyzing the gameplay, we also asked our players some questions before the game and some questions after the game (see chart below for the Q & A).

We met short term goal of players understanding why global warming was bad for the animals in the Arctic, but we fell short in convincing them that effects on the Arctic changed the entire globe. This information is largely concentrated in the global warming cards, which the kids didn’t have a chance to really engage with given that they only played the game once. We also met medium term goal–all three kids said they would discuss global warming with friends and family. We must note that these kids were already predisposed to this since they were working on a sustainability project themselves. It’s too early to tell if the long term goal of the players changing their behavior to combat global warming has been or will be achieved.

Points to consider for future improvements are that players learned best through experience rather than words – so if there’s a lesson we want to drive home, we should build that into the win condition. While we initially thought the game should be collaborative, our test players insisted that the game would be much more fun if it were competitive.

 

BEFORE THE GAME
Question Answer 1 Answer 2 Answer 3
What do you know about global warming and its impact on the Arctic? Temp inc decreases and ice caps melt and less land for the polar bears not much will be in the water as the ice melts
Why do you think the Arctic matters? animals live there and they can’t switch to a different environment
How do you think you can combat global warming? Do you do anything day-to-day? unplug chargers drive less, bike or walk drive less, public transportation
AFTER THE GAME
One sentence – how did you feel about the game? fun and can laugh at it fun fun
Is there anything that stuck out in particular? ice cards are good water cards are bad
How do you think you can combat global warming? too arctic focused learned stuff about global warming (mostly arctic related)
Do you think you’d talk to your friends and family about global warming? yes yes yes
Would you play this game again? And if so, with who would play with their friends would play with their friends would play with their friends

 

Guess Your Green

Team Members: Erick Friis, Krithi Chandrakasan, Aina Martinez Zurita, Sam Resnick

The US fuel economy measurement dataset shows many surprising and non intuitive values for different car models. We want to tell this story, because we believe there is a disparity between perceived and actual fuel economy among car owners.

For our participatory data game we designed an interactive visual game on a mall display board that allows users to guess the relative efficiency of their car and compare this prediction with the true efficiency. The game initially prompts users to enter a prediction with the question “How efficient is your car?” and then allows them to input the make and model of their specific car to determine the accuracy of the prediction. Users will have to walk around to the other side of the kiosk to view the results creating an element of suspense. In addition to showing the disparity between the prediction and reality the game will also display similar vehicles that are more fuel efficient. This data will aggregate over many user interactions and will show the greyed out predictions of other users. This will create a graphic that is developed in real time and grows over the course of the day.

Our target audience for the game is individuals who go to malls, typically middle to upper class Americans. While more progressive and environmentally motivated individuals are likely to participate, we envision more widespread participation due to the unique and interactive aspects of the game. The game is applicable to both people with average incomes who drive vehicles like the Toyota Camry, and wealthier individuals who drive luxury cars like the Mercedes G550.  The participatory data game caters itself to the needs and desires of the particular user, based on what car they enter.  If they enter an average family vehicle, the system shows alternatives with similar safety rating, but if they pick a luxury or sports car, the system shows vehicles with similar horsepower.  The choice of a mall kiosk was especially important, as they are often located at high traffic locations and have great visibility to consumers.  Additionally, malls are typically located in suburbs where the primary mode of transportation is a car – think Long Island.

Our goals are to show that individuals generally believe they are more “green” than they are in actuality, as well as to motivate individuals to be more conscious of fuel efficiency and emissions when purchasing their next vehicle. Our interactive game does a great job of accomplishing the first goal by showing real time data on beliefs that are collected from many consumers at the mall. The second goal is accomplished with the call to action prompting users to be more conscious while also giving them specific vehicles to consider when making their next purchase.

Personal Resume Data Visualization

Team Member:  Siyang(Autumn) Jing

The Personal Resume Visualization is designed to tell my personal story in an interesting and clear way. This resume is used for job interviews, whose audience is interviewers. Because both the interviewer and I are designers, the goal is that the visualization map is beautiful and easy to understand.

Though refection of my personal experiences, I categorize my data to three layers, which are concluded as three key words, brad global view, professional achievements as well as reliable and efficient personality. The first layer, the outer one, talked about the first key word, global view. This associated with my education background, my practice, the activities the teaching experience and awards. The middle layer is my design projects throughout my academic career. The project are labeled with professional tags, which will make my work type very clear to the audience. The inner layer illustrated my special personalities, which will benefit my future career. All the three layers will tell the audience my personal story.

It is not only a personal data visualization for me, but also an opportunity to reflect on myself and make progress in the future.

 

Architecture and Related Services Occupation Share

-what data is being shown

The data show the occupations by share in the architecture and related services.

-who you think the audience is

The audience are architects, people who have the related jobs, people who are interested in the architecture and related services, people who study the structure of the architecture related occupations, and people who want to start business related to architecture etc.

-what you think the goals of the data presentation are

The goal of this map is to show there are many related services of architecture, and what are the Percentage of those services in the industry chain. Secondly, the map creator also categories the occupations by management, business, science and art; Sales and office occupations; Service occupations; production, transportation and material moving occupations; natural resources, construction and maintenance occupations; Military specific occupations. In addition, the complicated map indicate the innate association of one occupation with another.

-whether you think it is effective or not and why

It is very effective in terms of showing the percentages of each occupation take in the whole industry. And the category is very clear. It is very helpful to understand the relationships and thus better refine this architecture related industry. It is also good that the audience could click on each occupation to see the population and the salaries. However, I find some of the information are too small to read. In addition, I could not understand the logic of how the map creator associate one occupation with another and why the order of the occupations are like these.

https://datausa.io/profile/cip/0406/