A 4-stage model for training engineers and scientists to help bridge the gap between home and school

Children spend the majority of their waking hours (80%) each year outside of school (cite), yet the emphasis on education is placed primarily on teachers and school, leaving the rich resources of parents and home learning unaddressed. Knowing this, we work with parents and mentors so they can provide opportunities for their children to practice and master problem-solving skills over the course of many years through many hours of practice, but we also work with teachers to bridge the gap between home and school, and to provide a consistent message to children from primary influencers.

As we’ve described previously, we’re focused on bringing our programs to scale through the use of technology, but don’t view technology as a substitution for in-person interaction. We want to use technology to support people’s interactions with one another, and have integrated technology as one element of our 4-stage model. 

Key Elements of our Model:

1. We provide a rigorous science communication training to scientists and engineers, training them to explain the science behind their work directly to the public (or as one participant put it, explaining it to a fourth-grader). This is done by having the scientists and engineers design original, high-quality hands-on projects that they teach directly to students and parents in their local communities, providing widespread technical education.

2. The projects the scientists and engineers develop are all open-ended engineering design challenges. These challenges are designed to have “low walls and high ceilings”—to be easily accessible while also lending themselves to endless and increasingly complex iterations. The challenges are intended to help students develop their creativity, innovation, problem solving skills and persistence—skills of critical importance for the next generation of STEM innovators. 


3. We train parents so that they are informed and connected to what their child is learning. The parents are able to continue providing similar learning experiences at home (well supported by resources). Following a similar train of thought, we also train partners like libraries, after-school organizations and teachers to use our challenges, taking care to connect school and out-of-school environments. 

4. Finally, we publish the challenges the scientists and engineers have developed both online through the Curiosity Machine, and through print with our Making Machines book series. Curiosity Machine users are supported by professional scientists and engineers who volunteer (and are trained) as mentors, providing sustained virtual feedback on each project. This role also offers scientists and engineers we had trained to develop challenges and share them at Family Science courses to continue mentoring students, although in a less time-intensive way.

From Pre-K through 5th grade, we mainly focus on parents—as they spend so much time with their children compared to teachers. We host family science to involve parents with the learning process, engage them, and encourage them to continue to explore and build with their children at home. By middle school, we expand our focus to include teachers and afterschool program facilitators, engaging them and training them to use our online curriculum and technology tools in and out of classrooms. However, our main focus is on our mentors, and we emphasize the science communication training, in our four-stage model as laid out here, and in putting that model into practice. Technology can never be a substitute for in-person interaction, which is why we train our mentors so extensively, and work to make our virtual mentor feedback as personal, individualized and sustained as possible. As we scale, we understand technology’s role as one of support for people’s in-person interactions with one another, and have integrated it as one part of our model, bolstered by one-on-one virtual mentorship.


Function vs. Aesthetics in data visualization

To me there are two aspects to data communication: aesthetics and functionality. Aesthetics is obvious, it’s the visual appeal of a graphic, but functionality is less obvious. Graphics have a functional purpose, which is to highlight patterns and trends in data in a visual way. A graphic is functionally successful when it is easy to understand the patterns in the data. This seems arbitrary, but in fact it can be quantified– you can measure the time it takes someone to process different graphical representations of the same data set. From this, you can derive principles that lead to graphics that have high functional value, or short interpretation times. For more info, read Tufte (on the Iridescent reading list!).

Given my background, I’m of course approaching the issue as a scientist, and as you might guess, science is almost entirely concerned with graphic functionality. Scientists are commonly working with extremely complex and inter-related data sets, and determining patterns from such data can be tricky. Using default graphics options can lead to visual clutter when dealing with complex data, and so many scientists take a lot of care in thinking how to present their data in ways that highlights the patterns they wish to emphasize. That being said, scientists place little care in aesthetics, often providing very ugly, but easy to understand graphics.

This is something I cared a lot about in grad school. I felt that someone’s ability to understand my data and take something away from my presentation was highly dependent on my ability to present that data clearly. I could have done an absolutely stellar research project, but with poor visuals few people would be able to understand or appreciate what I had done, so I put a lot of time into understanding data visualizations. (This desire to have people understand research is not common to all scientists– some just want to do really interesting research and could care less how many other people know about it). I took several courses in science communication, had a great advisor and fellow grad students who gave great data visualization feedback, read a lot of Tufte, made science posters with Ioana, and still spend a lot of time learning how to use data visualization tools like R and Illustrator. Anyways, I don’t always nail it, but I try to do the best I can in finding the best functional way to present data.

That being said, I have very little understanding of aesthetics. I still cringe when I look at outfits I picked out for myself as a kid in old pictures, I’ve always had a horrible color sense. What this means is that I might do a really good job figuring out what elements of a graph should all be the same color to aide pattern recognition, but choose a god-awful color to represent them.

But is there a conflict between an aesthetically pretty graphic and a functionally useful graphic? Not necessarily, and I can certainly think of graphics that do both effectively, like Napolean’s march:

But often designing for one purpose in isolation of the other leads to an aesthetic graphic that has poor function, or vice versa. Also, for simple graphics like percent of yes/no responses to a question, functionality really isn’t all that important. The least functional graphic is still not that hard to interpret for simple data.

But sometimes function and aesthetics are in conflict, and there are certain decisions about graphics use when one must choose between a more functional and a more aesthetic option. A classic example is Microsoft’s Excel’s defaults plotting settings, which regularly adds features that increase aesthetic value at the cost of functional value. (A good rule of thumb for making good functional graphics is to avoid default features on Excel graphs.)

So what does this mean for how I make actual graphs? I wanted to end by sharing a few of the principles I use when creating graphics, so you can understand the choices I make. I’ll occasionally bash on Excel’s graphic choices, because I can’t help myself :) The basic Tufte-inspired idea behind all of these principles is to minimize whenever possible- if you are including something in a graph, it should be for good reason.

  • Avoid dead space- Classic Excel problem, moving titles and legends to the far edges of the figure, and reducing the size of the actual graph by default. Dead space can be avoided by including as few additional features into the graph as possible, and utilizing free space inside the graph to put legends and visual indicators.
    Example of the unfortunate Excel defaults (using made-up data)
  • Avoid clutter- Of course, but, what is clutter? It depends on what you want to show. Something might be clutter in one graphic, but a vital part of the illustration in another. Generally, the lines that pan across a graphic (as come default on Excel) are clutter- for most graphics you don’t care to know the exact value of a point, you really want to compare that point to neighboring points, or points of a different color, in which case just having a general axis to show the scale of the data is good enough. If you want to communicate the exact value of the data, for example when the data goes over a value of 5, then it might make sense to have one horizontal line at the threshold value.
  • Space and color matter- Another way of saying this is that you should minimize the steps required to interpret data by effectively using space and color to link meaning to data. We typically see a legend as the way to match color and shape to something meaningful, but it’s actually a pretty inefficient way to make that connection. First, there is space between that actual data and the thing that interprets them, forcing the eyes to go back and forth across space to connect the point in the graph with the meaning in the legend. Whenever possible, one should link the meaning of the data visually close to the data itself. If a bunch of points all clustered together all fall in one category, put that category label by those points. Same goes for color: if red corresponds to 4th grade students, think about making the words “4th grade students” colored red in the legend.
  • Pie graphs are evil- It’s a fact that humans are terrible at estimating and comparing angles and areas, but very good at linear distances. Anything that can be represented in a pie graph can be more effectively represented by a bar graph. For one data point a pie graph is ok, though still an inefficient use of space. But if you are putting multiple, related pie graphs side by side, you are doing something very, very wrong.

  • The order of data has meaning- This may seem obvious, but it’s easy to overlook. Just because you asked the questions in alphabetical order doesn’t mean they need to be put in the legend that way. Show the highest values first, so that the visual order of the data also is meaningful. It’s a lot easier to interpret sorted data on a graphic.

I’m including two examples from my graduate research that I think do a decent job of communicating patterns in data. First is a poster for a relatively mathy audience about a somewhat mathy topic.

Notice none of my graphics are clean- I’ve marked up and put points right on the graphs and illustrations. I don’t have a block of text that refers to figure 1, I tried to seamlessly go between saying things with words to saying things with pictures. I didn’t want to create visual space between where my graphs were, and where the text was that referred to the graphs. Notice how the graphs use legends. Notice the relative size and boldness of component of the graph to draw focus and emphasis. Notice the graphs on the lower right- it was hard to understand what those jargon terms in the axes referred to, so I decided to include an actual picture on the graph showing the component of the organism being measured in each row of figures.

Next is a figure from my thesis.

It shows how reproductive 4 different species of algal were throughout the year. Notice that the x-axis is not evenly spaced- they are spaced by when I actually measured the data, and because of tidal patterns I did not always measure them exactly one month apart. Notice the order of the legend corresponds to the general reproductive magnitude of the different species, which both makes it easy to link the data with species names and makes it easy to know which were most reproductive species on average—all the viewer has to do is look at the order of the legend. Notice the bottom two species are filled in icons, whereas the top two are open symbols- those species share a similarity in one dimension (being crustose or articulated). But notice that the first and third are triangles while the second and fourth are square, since those also shared similarities in a different dimension (r vs. K selected). But these are minor details for someone who was paying attention to this distinction in the text and really wants to dive in to how these dimensions effect these species. I didn’t make them prominent for a reason- they are present, but not the focus (these dimensions are actually the focus of the next graphic in my thesis). Notice error bars are the same color as the data they are related to for easy tracking, important when the bars overlap as much as they do here. 
There’s a lot to think about–but all these little pieces add up to make a functional and (maybe if I’m lucky) aesthetically interesting data visualization.

Mumbai slum girls innovating where governments can’t and markets won’t

I watched Slumdog Millionaire many years ago and cried. I grew up in India and routinely saw little, maimed beggar children on crossroads and never thought how they got there. That movie completely shattered my protective glass.
Now I have two little girls and cannot bear to watch violence against children.
So when I heard about a group of driven young girls and mothers in Dharavi (the same slum where Slumdog Millionaire was shot), I was so energized that I could finally help right some of the hellish wrongs that we perpetrate against children.
Nawneet Ranjan, a very motivated and talented young filmmaker, approached us and told us about this group of women who were making laptop bags out of old sarees and were interested in learning about technology, so that they could make apps to market their products.
He told us a little about his own journey. His initial goal was to interview the Dharavi residents for a documentary he was making. As he started talking to the women, he was struck by their entrepreneurial spirit and their desire to improve their daughters’ future. He realized that just interviewing them for the documentary was going to be heartless, if he didn’t do something to help them as well. 
That was inspiring.
And then hearing the girls talk about it in their own voices was even more inspiring.
That was last year. I shared some tablets, phones and asked Nawneet to keep in touch.

A few months later, he contacted us again and said that he had a group of 20 girls who wanted to participate in the three-month long Technovation program, and learn to create mobile apps to solve problems in their community and launch their apps on the market.
This is why this undertaking is so inspiring.
Dharavi is one of the world’s largest slums with a population greater than that of San Francisco. It is in the heart of Mumbai. Most of the girls work as house-help in people’s homes and earn $3 – a month. They go to a local government school.
They didn’t have a safe place to meet, so we helped Nawneet rent a classroom space and hook up internet, so that they could access the Technovation curriculum.

Language is a just another barrier as they are not very literate or comfortable in English.
But they have grit.
The girls’ enthusiasm to learn has inspired their mothers who have formed Mahila Mandals to help further support the girls.
The three apps that the girls are working on are to solve very real problems:

  • Water access – water comes only once a day to Dharavi and only for half an hour. Children (particularly girls) have to skip school to wait hours in line. Fights are a daily occurrence. The girls are creating an app (for a cell phone) that will help families register and secure their place in the queue. The app will notify the families (via sms) when their turn is coming up, so that children dont have to waste time waiting in lines.

  • Security – Rape in India is a huge problem and one that the country is struggling to address – ineffectually.  The girls are creating an app that will help users press a “scream” button that will notify others — through the alarm as well as through a call made to the police.
  • Health Education – Women do not have access to information — really basic information regarding personal hygiene and around more life-threatening instances, like child birth. They have no support systems or resources. The Gates blog has a great post on the state of India’s sanitation problem. The girls are working on a health education app that can provide basic health and hygiene tips to users via cell phone sms.  The Mahila Mandals want to get tablets so that more women and girls can access videos and more comprehensive health education resources.

The Dharavi girls and mothers are unusual because they have the courage to seek help and the desire to fix these problems themselves. They are also unusual in that they want to befriend technology to drive this change. They want to share their stories and problems with the rest of the world – through video blogging.

We can’t wait to hear their voices and ideas. 
That is the only true way to right the situation – not to look to governments, big corporations or nonprofits – but the girls. Empower the girls.
    Pictures and Video by Nawneet Ranjan


    How do you become a better listener?

    A researcher in the 1950s found that the total impact of a message is about 7% verbal, 38% vocal (tone of voice, inflection etc ) and 55% nonverbal. 
    Image from the Illusion of Life
    Here are some tips I have picked up along the way to read the person you are talking to.  I have found them especially useful running an organization that is distributed and virtual. We conduct most of our discussions through video on Google Hangouts, and reading body language and facial microexpressions are a key means to reading nonverbal signals.

    Body Language

    When talking to one person

    Read expressions and gestures in clusters.  The look of critical evaluation when combined with closed body language, crossed arms and legs, indicate that you may need to make a more convincing argument.

    Palms intentionally used to show open, honest speech

    Everyone knows that crossed arms and legs indicate closed body language, but I am always amazed at how many people do that in meetings and even presentations. What I did learn was to stop doing that (because it doesn’t help anyone, it just makes the other person more uncomfortable). And when I did, I realized I was more open to ideas.

    So, the piece of advice is to first check yourself from closed body language, and then to help others uncross their arms. You can do that by having them reach out for a pen or coffee mug and then create a rapport by nodding your head and mirroring, to make them feel more comfortable (and prevent further crossing).

    Talking to many people 

    The bigger the audience, the bigger the gestures need to be.

    Use wide expansive, open gestures. Don’t cross your legs or arms. That bars the audience and shuts them off. Stand confidently and welcome the audience to listen to you. Ben Horowitz does a great job illustrating this at our Technovation keynote a few years ago.

      One way to enlarging gestures is to start them from the shoulder. Wrist or elbow gestures are automatically smaller and tend to be limited in their variety, too. In fact, this is the single most common problem that drives people to “repetitive gesturing.” If you keep making the same gesture, it rapidly becomes meaningless and ultimately annoying to the audience.

        Make sure your gestures are high enough. Low gestures draw the eyes of the audience down and away from your face. They become distractions. If you watch for it, you can sometimes catch people doing a vague imitation of penguins, with their hands flipping about at their waists.

          Hands behind your back indicate reserve, some level of discomfort.


          Dr. Paul Ekman is the pioneer in this field. His book Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life is a great starting point.

          The six basic emotions are shown below. If you watch closely, you will see various (and fleeting) manifestations in people’s faces. They will give you a very accurate window into what your listener is thinking of what you are saying.


          Listen. Observe. Talk less.

          “The reality of the other person lies not in what he reveals to you,
          But what he cannot reveal to you.
          Therefore, if you would understand him,
          Listen not to what he says,
          But rather to what he does not say”
          ― Kahlil Gibran


          200 girls learning how to program mobile apps – in a 2500 year old Indian city

          Over the past few years, Iridescent has been growing and I dont have as much contact with participants as I did before. I miss that fuel.
          But thankfully, every few weeks, some stories of people come through – that just make me stop and stare in amazement.
          Like this one.
          Senthil Kumar is an engineer at Qualcomm in Bangalore. His sister, Mani Mala, is an educator in Madurai, one of the oldest cities in the world (actually 2500 years old).
          They learned about Technovation and took it upon themselves to bring Technovation to the young women of Madurai.
          The logistics of this undertaking are what makes this story of grit so inspiring. It really brings perspective to first-world petty griping!
          Some background on Madurai. It is famous primarily for its old, old, old, beautiful temples. People grow rubber and the city is known for its cultural traditions.


          That is from a tourist’s point of view. But what about its youth? They aspire just as young people all over the world. And that is the story of Senthil. I did a quick interview with him trying to understand how he became so driven and motivated. Listen and be inspired!

          Senthil and Mani Mala wanted to provide more opportunities to the young women in Madurai and recruited more than 200 women from two local universities to meet on the weekends and work through the Technovation curriculum.

          They dont have internet, but that doesn’t stop them!
          Senthil takes the night bus every Friday night from Bangalore (a 10 hour bus journey), reaches Madurai on Saturday morning. Teaches the girls. They work around the internet issue using an offline version of App Inventor. Senthil downloads the girl’s code on flash drives. He does the 10 hour night journey on Sunday night and goes straight to work on Monday.

          He has been doing this for weeks. (The Technovation program lasts 12 weeks).
          Their biggest need right now is for mentors who can help ease the load on Senthil and Mani and support the young women towards completion of their apps and business plans.
          Imagine if these young women came to Silicon Valley to present their technology solutions for a better world!


          Taking a look at the STEM Education landscape: Strengths of Engineering Skill-Based Volunteering and Online Programs that inform our work

          A literature review is a necessary component of most publications, demonstrating familiarity with the field and key research findings while also situating your work in the broader context of that research. Understanding this aim, as we crafted a proposal for an NSF AISL grant this past winter, we decided to expand our understanding of “literature” to include programs and initiatives addressing the same issues as Iridescent’s programs. We focused on the practices of: 
          1. engaging STEM mentors (particularly professional engineers) 
          2. involving parents and families in children’s learning
          3. exploring STEM content through online platforms and services
          We hoped to understand what other programs were doing to address the question of engaging underrepresented populations–to learn from and adapt their best practices–and also to understand where our work fit into this broader picture. In part, we were looking for a way to answer the question: “What makes Iridescent programs unique?”
          In conducting our review, we compiled the following tables:

          Strengths of Engineering Skill-Based Volunteering and Online Programs that inform our work


          Family Science:

          Online Learning:

          Looking at this collection of programs and organizations helped us better understand what we’re doing, and what we’re aiming to do. As we set the three categories and classified programs into those categories, we began to understand the way we combine these separate aspects. We had to look back to our early days to trace the influence of San Jose’s Family Science Nights, or the over-arching influence of the philosophy behind Engineers without Borders, or the model of online-hosted curriculum Engineering is Elementary embodies…but in collecting all of these programs into tables we were able to see our work occurring at the intersection of these categories.

          We looked at projects designed to offer online mentorship courses to university STEM students (the SUNY mentorship program; COSIA) and projects developed to produce online curriculum/content from STEM students and professionals for classrooms or websites (Portal to the Public, Engineering is Elementary; Using Science Academies Project), and saw similarity in our aims with our Engineers as Teachers program and the Curiosity Machine.
          However, we were also able to understand the unique nature of our own program–our system of teaching engineers to communicate their research to a public, non-technical audience through structured Family Science Courses (similar to San Jose Discovery Museum Family Science and Engineering Nights, or the AASS Science Nights, but consistently, over a five week course period instead of one night, and for free), and then having that continue into families’ homes, with the Curiosity Machine (which combines the Engineering curriculum and OEEDC of other sites like EiE or DIY with one-on-one mentorship). We were able to understand how the emphasis on one-on-one mentorship for Open Ended Design Challenges of the Curiosity Machine is unique for a website, but also for engineers who seek deeper connections, wanting to reach younger learners (while being mindful of realistic time commitments). 
          It was through considering the field, reviewing other programs and their practices and expertise that we were able to situate our own, and fully articulate how our chain or pipeline of programs knits together their (and our own) best practices in a unique way. In short, we had to look around to understand where we fit in.

          References: Our jumping off point for this review was Change the Equation


          What gains do children make in curiosity, creativity and persistence over 100 hours? What age can you start?

          To answer these questions, we ran a 100 hour-long summer camp – looking at nature from an engineer’s point of view. We opened the camp to a wide range of ages – all the way from 3-10. Each child was paired with an adult or a high school explainer.

          The main barriers for the littlest ones were motor control and verbalization of ideas. The former was addressed by having the high school explainer or adult serve as the “hands”. Over time as the little ones got used to the environment and people, they became more comfortable with expressing their ideas and goals.

          We based our curriculum on the Next Generation Science Standards as well as the core principles of successful games and motivation theory:

          • a sandbox to start and explore without fear of failure
          • showing the real world and exciting applications of learning (or “why” this is important)
          • providing “just-in-time” or “on demand” knowledge, encouraging students to learn as they build, instead of making them demonstrate expertise before they build.
          • giving each student choice and ownership of their learning. Students could apply their learning to design and build models of their own choosing.

          Over the course of the 100-hour camp, students experienced the following progression of skills:

          25-50 hours – Gaining Observation Skills, Familiarity with Materials, Asking questions that can be investigated

          1. Notice features, patterns, or contradictions in one’s world.

          For instance, instead of differentiating birds on the basis of color, students started to notice differences in wing beat frequencies, wing tip shapes, types of beak etc.

          1. Ask questions about the phenomena being observed

          Why is it that millipedes move slowly, but centipedes can move fast? Why do leaves on different plants and trees have different types of edges?

          1. Becoming familiar with materials and how they behave

          We use very simple, low-cost materials to lower the cost of failure. It is not a very big problem if a child breaks a few popsicle sticks while trying an idea, but the same tolerance can’t be extended if the materials or equipment are very expensive or single-use only. With practice, students learn to predict how different materials behave under varying forces, and conditions such as temperature, light, pressure, or mediums such as air, water, and oil. The most direct application of this was when the students designed and built self-ventilating animal homes using mud, sticks, leaves and water.

          1. Learn to use instruments to measure variables

          Students were exposed to a wide range of both simple and exotic measuring instruments – from humble rulers and magnifying glasses to microscopes and boroscopes.

          1. Develop an investigation plan

          For instance, for the cardboard automaton week, we showed the students various videos of automatons to inspire them. After the videos, we worked on drawing our own designs. At first the students thought that the project was easy and came up with very elaborate designs. Once they started executing, they realized that they needed simpler designs — and went back to the drawing board.


          A surprising finding was the value of kits such as “Snap Circuits”. These type of kits usually are not at all open-ended and dont give the learner any choice. However, they were valuable for the younger students to experience early success, reinforce learning and motivate them to explore using other materials (such as squishy circuits) to build designs of their own choice.

          1. Students use diagrams, maps,drawing, photographs, 3D models as tools to elaborate on and present their ideas

          We invited a scientific illustrator and artist to teach the students about picking key features and representing them in 2D. Students learned to look at a bird and represent it as a few ovals of various sizes. 


          50-100 hours Being able to apply the Engineering Design Process and gaining in persistence

          The biggest learning gain for students at this level of practice was being able to say, “lets try again” when something didn’t work. Most students get very frustrated when their model doesn’t work on the first try. It takes repeated reinforcement of the message – “Its ok! Lets try again. Now what should we change this time to try and make it work?” to develop persistence.

          1. Make and use a model to test a design and to compare the effectiveness of different solutions
          2. Students persist through failing designs and models
          3. Students compare designs through repeated testing, troubleshooting, recording and analyzing results and finally identifying the best.

          Students went through all stages of the engineering design process each day while exploring different questions regarding bird flight, beaks, animal locomotion, tree stability and structures etc.

          1. After repeated development and testing, students invent a totally new design based on the characteristics of the best design.

          The summer camp provided 100 contact hours to students who came for the full 4 weeks.  Due to the young age and lack of similar, prior experiences, the students didn’t get to the Inventor stage. Based on the programs we run at our studios in NYC and LA, we have seen that it takes ~500-700 hours of practice for students to be completely familiar with observing, framing the right investigation questions and persisting through the engineering design process to get to the Inventor level.


          Food Science: Make a pH Neutral Drink

          Are you ready to teach your kids about the building blocks of life? Excited to begin conversations about atoms and molecules? Let’s get started creating a pH neutral drink! 

          Our ingredient table

          We love teaching about science through cooking–if you missed it, check here for a discussion about the benefits of using this strategy. 


          • litmus paper (available online, or find instructions to make at home here)
          • blender

          The following are all suggestions–just choose things you have in your kitchen. Try to have a blend of some spices, sweeteners, juices, fruits and vegetables. Without a blend you won’t be able to get the drink to be pH neutral.

          • spices like cloves, or cinnamon
          • vegetables like beets, spinach, carrots
          • sweeteners like agave nectar, honey, sugar, cocoa
          • juices like apple, carrot, pomegranate
          • fruits like kiwi, oranges, apples, bananas

          Making Your pH Neutral Drink

          Making these drinks will be a fun time for your family to test their senses of taste. Talk with your children, maybe even have them taste, the earthiness of bases (think tea, cocoa) and the sourness of acids (think lemon juice, vinegar). After this, let them know that you are trying to make the drink neutral, or with an equal taste of both acids and bases.

          1. Blend different types of ingredients, tasting and making changes to mixture
          2. Once you think you have a neutral taste, test it with the litmus paper. If it is around 7 and turns purple, it’s neutral!
          3. Keep trying different variations, like one without sugar, one with lots of vegetables, etc.

          Science of a pH Neutral Drink

          Here are some science concepts you can talk about with your families while making drinks:
          • Atoms are like very small building blocks–they work together to make bigger things. There are many different types of atoms that build a diverse array of things. There are so many tastes because everything is made from different combinations of atoms.
          • Atoms form together to make molecules, we can make lots of combinations
          • Acids and bases are a type of molecule
          • We’re trying to mix our atoms and molecules together in the drinks to make it pH neutral
          • You can change the taste of a dish if it’s too bitter or sour by changing the ingredients you put in it, since each ingredient is made from different molecules. For example, if tomato juice is too sour and acidic, you can add sugar to begin making it taste more neutral.


          pH Scale (note that alkaline means base or basic)


          Food Science: Make Noodles to Test Viscoelasticity

          How do you get your children interested in science at home? What can a parent with kids of varying ages do to get everyone excited about STEM concepts? At Iridescent, we’ve learned that food is an amazing tool for elevating a child’s interest in science! Cooking is an interactive, messy and (hopefully) delicious thing you can do at home to teach science concepts and conduct experiments. Kids of all ages enjoy making food with their family–2 year olds can help stir, 10 year olds can help with reading the recipe and teenagers can help with the hard stuff, like cutting. This is the first of four posts where we’ll discuss our food science recipes.

          Ready to learn about viscoelasticity through noodle making? Happy cooking–be sure to let us know how it goes!

          Our Food Science cooking supplies 

          Teach your children how food impacts their bodies and about the property of viscoelasticity by making noodles!


          • multiple types of flour–you can try wheat, gluten free, almond flour, white flour, etc.
          • multiple types of salt–you can try pink, sea salt, table, etc.
          • water
          • wax paper

          Making the Noodles:

          Noodle making is a great way to let your children explore measurements and different kneading/pulling techniques. Have them guess how much flour, salt and water to add to their mixtures and encourage variation. Giving them this freedom will greatly impact the way the noodles taste and their viscoelasticity–hopefully kids will start making the connection that different mixtures will produce varied results. So, in the vein of exploration, I’ll only give very basic instructions for this recipe.
          1. Mix your ingredients into a bowl, guessing how much of each will work best and adapting the measurements as you go.
          2. Knead everything together until dough isn’t terribly sticky
          3. Place dough on wax paper and pull the noodles into the shapes you’d like
          4. Put noodles in boiling water, boil until they float to the top
          5. Pull them out, let cool and enjoy!
          6. Make a new and improved mixture

          Science of Noodle Making

          Here are some ideas you can talk with your children about during noodle making:
          Checking the viscosity (notice the lack of elasticity)
          of different ingredients
          • Basic conversation about chemicals and the periodic table–food is a chemical that we put into our bodies to help build muscles and skin. Different types of food, i.e. proteins, sugars, grains, will create different results for our bodies.
          • The “chemicals” in noodles are starch and protein. Starch is special because it gives us lots of energy, protein helps us to strengthen our bones and muscles. Proteins also help us build enzymes, which do lots of things in our body like digest foods and make new cells. 
          • Viscoelasticity is a concept we see in noodles. Visco is the ability to resist deformation, elasticity is the ability to change back into into their original state after being deformed. When we pull noodles, we rearrange their molecular components and eventually will change their shape from a big dough ball to a recognizable noodle.