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



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:

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:



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.


Buzz About Bees

Sharlene Chiu, Tricia Shi and Zachary Collins

The data says that bees are dying and colonies in many areas are declining in size. We wanted to tell this story because we believe that, although many people know bee populations have been declining, they are unaware of what they can do to help stop it.

Our audience are flower shoppers. Many varieties of flowers offer a means for bees to collect the nectar they use as an energy source. Some can be more impactful than others, allowing bees to gather nectar more easily. People who are already thinking of planting flowers can make decisions that could have an impact on bee populations in their area.

Our goals are to have them understand the problems bees are facing, recognize that planting flowers can help and aid them in picking flowers that both grow well in their area and easily allow bees to collect the nectar they need to survive.

Our sketch is an interactive display that can help localize the problem to the individual. The flow works as follows. We would set up the display in a supermarket / plant nursery / flower shop with an opening display that consists of “Did You Know” bee facts and a clickable map that invites individuals to learn more about bees in their state. Upon clicking they’ll be presented with information about the good bees do for them in their state – plants they help pollinate, honey they produce. Then it will transition to damage being done to bees – Both locally and nationally. This highlights the problem at hand and localizes it to where the individual is from. We present facts like how many colonies have declined over the past year and that bumblebees have recently been placed on the endangered species list. We will then pose that planting particular flowers can help bee populations. Then, we would allow the user to select between different flowers, pulling up a map of what counties in the state these flowers grow well in. Finally, it provides a link where one can learn more information about the problems bees are facing.

Our sketch takes a national problem and localizes to the area the individual is from. It demonstrates a simple way they can help through a platform that is very inviting and easy to use. We attempt to help them understand the existence of the bee decline and point them in the direction toward flowers that can help bees successfully collect the nectar they need. Since they are probably already thinking of purchasing flowers, showing them which kinds help could sway their decisions.

The map display we utilize is important in allowing us to get our message across. We want to provide the buyer information about what grows well in and around their local area. We present the flowers in a checkout guide manner – allowing them to select between them and see pictures of what the fully grown version looks like. Without the bees in mind, this could already be effective in helping them pick out what flowers they like. Giving them options among the kinds that help bees the most pushes them toward making a decision that could influence populations in their area. Placing it on a map familiar to them allows them to compare the locations in which they grow effectively and couldn’t easily be replicated using another form.





Food Insecurity Posters

Aina Martinez Zurita, Tricia Shi, and Zachary Collins

    The data says that there is a large section of our society that grapples with food security every day. Many people, due to a societal expectation to be able to provide for themselves and their family, feel too ashamed to reach out for help when they struggle to make ends meet.

    The Greater Boston Area has many shelters, food pantries, and churches that offer free meals, housing, training, and other resources for free. Our target audience are individuals who are struggling with food insecurity, specifically those who use public transportation near these shelters and resource centers. Many people often don’t know what is in their area or even that that it’s typical for someone in their situation to receive assistance. The goal of our posters is to demonstrate that there are locations in their local area – near and around their home and daily commute – that can help and foster a sense that reaching out to these places for help is normal.

    In the Food For Free data files, we noticed a common theme among many of the individuals in the Project Bread Status Report – prior to getting the help that lifted them off their feet, they were unaware of where to go and / or embarrassed by the need to get help. We wanted to advertise some of these shelters but in a way that utilized the personal narrative surrounding the status report interviewees in an effort to shift the viewer’s perception.

    We researched a few of the shelters near and around Boston (Rosie’s Place, Elizabeth Peabody House, and My Brother’s Table) and gathered information about the number of people they are able to serve and what public transportation stops are close by. Using the personal stories from the status report and quotes from individuals who were helped by these resource centers, we made posters that bring to the surface who these places aid. By providing a face, quotes, and information about their income and occupation, we build a very relatable image that can help people realize where they can get help and that people like them often do. At the bottom of our poster, we mention that these places serve many individuals, suggesting that going there is normal. We also provide helpful information about how to get there.

    When putting all of these components together, we have a poster that demonstrates that getting help with food insecurity is a normal act – something that others like them have done and are extremely thankful for. From far away, one can see the image of the person and the quote about the help they received. This puts the focus on someone who they can connect to. When observed up close, they can get more information about what might make the individual’s current situation similar to theirs. This can help remove any stigma about feeling alone and embarrassed. They can then get a more detailed description about the shelter or pantry including a quick blurb about its proximity and how to get there. The medium of a poster makes gathering all of this information very quick and covert, and is able to paint a clear image for how it can help them.

    If we were to take this sketch and expand it, we would interview many more individuals who go to the food shelters near and around Boston, allowing us to build many different profiles for many different people and locations. Pasting a few around an individual shelter or pantry could intercept many who could use help as they commute to work or other places around the city. This way, we would be able to hopefully change the misconceptions they have about food insecurity and the number of people it impacts.




Steps to a Better Environment

Steps to a Better Environment

Tricia Shi, Nina Lutz, Sharlene Chiu, and Zachary Collins

The data says that our collective mindset towards the environment will have a serious impact on how global carbon emissions will trend over the next few decades. If we take care of the environment, they can level off somewhere very near our current rate. If we don’t, they are expected to increase quite rapidly. We wanted to tell this story because the effects of our actions today, although not necessarily making an immediately noticeable impact, could have drastic consequences on the state of our environment just a few decades into the future. This will not only determine the world future generations live in, but even the majority of us today.

Our data visualization project is a staircase that will help people understand the impact our everyday actions can have on our carbon footprints. The shape of the staircase maps our past global carbon emissions as well as two projections for carbon emissions over the next few decades. One projection assumes we live in a world in which, “people pursue personal wealth rather than environmental quality” while the other is a world in which we place a, “strong emphasis on community initiative and social innovation to find … solutions.” Essentially, what happens if environment protection becomes a societal passion versus something we just brush under the rug. The differences are drastic.

To display this data, we wanted to create a visualization that could be interactive with the viewer while still being able to reach our audience passively. We decided that a staircase offers many metaphorical and engaging traits that would help us hammer our major points home. From a passive perspective, the shape of a staircase could easily be molded to align with the line graph representation of our data. Observing it from the side allows the viewer to make out the trends in CO2 emissions and presents it in a form that makes comparing the two models easy. The ability to view the data from various angles allows the different projections to be highlighted.

Climbing the stairs presents a very clear opportunity to get the audience engaged and quite literally feel a comparison between the two. Along the way, we present the climber with numerous facts about both past, current, and future carbon emissions. The first half of the staircase, which follows CO2 transmissions over the past few decades, presents facts related to what actions have led to the current levels and incident climb that we are making. As soon as they reach 2020, the staircase splits into two halves, one for each projection. The audience can feel the different steepness of the two set of steps and this is representative of the rising CO2 levels associated with them.

The two sides are meant to act as a parallel and present facts that demonstrate what actions we take as a society that impact environmental conditions. The half that follows the path toward high levels of CO2 showcases facts like “3 billion trees are cut down annually” and “13% of U.S. greenhouse gas emissions come from the production and transportation of food”. Things that we don’t think about impacting our global ecosystem so heavily but might observe everyday. The second half that follows the path to a better environment presents paralleled ways we can counter the other half. Facts like “planting an individual tree can help consume up to 48 lbs of carbon dioxide from the air per year” and “Eating locally grown foods avoids the high carbon output created by transporting long distances”

The ideal setting for our data visualization would be a museum. Having this staircase lead to two paralleled exhibits could further compound the comparison these two models attempt to make. The staircase that follows the projections of high CO2 levels could lead to a display on what the rising pollution levels could change (i.e. food quality, climate, and disease). The other could lead to a display of things that reducing pollution and CO2 levels would instead protect. We imagine setting this up in a museum would have a powerful effect on the people there. Going to a museum fosters a sense to explore and engage with what’s around you. Having that mindset will really maximize the potential for people to understand the information the staircase offers, both passively and interactively. Our target audience consists of children, young adults, and middle-aged adults, many of which we would find in this setting. Since museum trips are often done with families, the onus to prepare for future generations — their children’s generations — are more heightened and will allow these paralleled projections to be more profoundly felt. Placing positive connotations around acts that are good for the environment could help reach children who climb and interact with the stairs.


  4. (Spencer Weart & American Institute of Physics)

Cut a Tree — Make a Difference

Cut a Tree, Make a Difference

Divya Goel, Meghan Kokoski and Zachary Collins

Link to Flyer:


When looking through the data displayed by the World Bank, we saw an undeniable increase in carbon dioxide emissions and a drastic decrease in global forest size. We saw these two developments as very related issues, even if not necessarily correlated. The natural recycling process that plant life does with carbon dioxide is very important for reducing our global footprint. The damage we are doing at both ends of this process is concerning, and so we wanted to make a visual display that would connect these two problems in a different yet still very effective manner.


We displayed our data with a very satirical approach. It took the form of a flyer produced by a fictional company whose platform advocates deforestation and increased carbon dioxide emissions for the purposes of eliminating fresh air and increasing climate change. Quite immediately it becomes clear that this advertisement is satirical, however this perspective adds much more weight to the arguments we use our data to make.


We first propose the current issue — that trees are one of the largest reducers of carbon dioxide emissions. We highlight to the audience the effect they have on clearing the air and then turn attention toward global deforestation. We highlight the massive reduction in forest area describing it as “a great step toward increasing net emission.” Taking it in from a satirical perspective hits the audience in a much stronger manner as something that clearly shouldn’t be having much success is proving to be quite effective. We then turn it into a call to action, encouraging readers to “take the fight to their own backyards” and chopping down local trees. Highlighting the damage they can do actually highlights the positive impact they can have (i.e. planting and protecting local trees).


The major chart that we implement is an area graph displaying increased carbon emissions coupled with a tree infographic that displays the damage done to tree populations. The most flawed chart we critiqued in class was the flipped area graph displaying “Gun Deaths in Florida” created by Christine Chan. It’s deceptiveness and confusion caused it to be a very ineffective way of telling the story the author intended, however, we believe that the major fault of this chart was a lack of context and a confusing background. If those were mended, the interesting features this layout contains could be effectively used to convey a story. We decided to take a page from Nigel Holmes and inject humourous and contextual images that would make the graph’s intentions clear and give the reader the motivation to correctly understand what the chart was displaying.


We labeled our upside down area as carbon dioxide and gave it a distinctive coloring. Moreover, we inserted iconography related to forest area reduction to the bottom portion of this graph. Having movement and action occurring in this section makes it very clear that this isn’t what is being plotted in the graph. The gaseous nature of carbon dioxide makes it very clear why it may be situated in this inverted form as every object in our display has some relation to the physical item it represents. The interaction between the trees and carbon dioxide creates a clear metaphor that forests are protecting us from it, and provides meaning to the trends within the graph. Using these tools, we were able to capture the reader’s attention and display our data in a way that highlights and provides immediate meaning to both the problem at hand and the information being showcased in our graph.


Our target audience is the general individual who may consistently hear about these problems but has become desensitized to the usual and common arguments. Millennials would resonate well with the satirical nature of the flyer. Choosing to tell the story in this type of context focuses on what has went wrong, providing negative reinforcement rather than just the potential to do good. Because millennials are more likely to change their attitudes and habits moving forward, this visualization will have a more persuasive aura among them.


CO2 Emission Data and Forest Area Data:

Tree Carbon Consumption Info:

Planet Tree Total:


Data Log – Zachary Collins

  • Debit Card Purchase – Bought coffee and food at the Student Center using my debit card; The transaction’s recorded by my bank and by Dunkin’ Donuts.
  • Dining Hall Meal Swipe – Got dinner in the dining hall by swiping my ID to access my meal plan.
  • Dorm Tap In – Every time I came back to my dorm I had to tap in to recognize my entrance.
  • Facebook Messages – Sent messages to a friend about the club we are involved with using Facebook Messenger.
  • Text Messages – Sent text messages back and forth with my brother
  • Spotify Streaming – I listened to music for a little bit using Spotify
  • Twitter Use – Went on Twitter a few times; My actions (scrolling, clicking, typing, etc.) were definitely recorded
  • Search Engine Queries – Searched a few things on Google for homework
  • Overwatch Games – Played a few games of Overwatch; Game data was definitely recorded
  • Stream Celtics Game – I streamed a Celtics game using Xfinity on Campus
  • Sent Email – I sent a few emails for a club I’m a part of
  • Downloaded Problem Set – I downloaded one of my problem sets from stellar
  • Printed Problem Set – I then printed it using the Athena Cluster in my dorm
  • Posting this Blog Post – Submitting this blog post in itself is recorded on the website

NBA Math – Quick and Comparable Information

I’m definitely an avid NBA fan and a lot of the accounts I follow on Twitter are geared toward providing me with information about the league and the teams I like to keep track of. One Twitter account that I found just a few weeks ago, NBA Math, tries to provide an objective assessment of the league by crunching numbers, specifically through their TPA model that takes into account a per possession conversion of the events that occur throughout the course of games.

Their TPA model often provides a two-number evaluation of players and teams that can be broken down into an offensive and defensive score. Viewing these computations in a table ordered by greatest difference can be a great way to visualize most of the information one would want, but makes comparing quite difficult and tedious.

Many of the tweets they send overcome this by displaying the teams on a simple x-y coordinate graph where the axes represent the offensive and defensive scores.

Adjusted defensive and offensive scores for each NBA team since 1 January 2017 VIA NBA Math

While the aesthetics of the display may be bland, presenting it this way is incredibly powerful and allows a Twitter user to be able to make the quick assessments that are typically favored on a social media platform. They are on the site to get quick bursts of information and this type of data platform allows a single tweet to streamline a lot of information at an incredibly rapid rate. Seeing how various teams positions differ can be done with great ease, allowing a user to identify where there team stands and how they might need to improve relative to the rest of the league and the teams that, by popular opinion, are considered elite.

It’s very unclear how effective a model that tries to boil down performance into two numbers can be useful and effective. However, the ability of NBA Math to send out bursts of tweets in this variety can capture the attention of Twitter users easily allowing them to show off this model and try and convey the information they’re gathering about the league.

Link to Tweet: