Posted on

Creativity Behind Jugaad Innovation

In 2001, when an earthquake caused extensive damage in rural Gujarat, Mansukh Prajapati, a potter, found his inspiration. Reading the caption, “Poor man’s fridge broken!”, under the picture of a broken earthen clay pot in a newspaper, sparked an idea in him. “Why  not use clay, he thought, to make a real fridge for villagers – one that looks like a typical fridge, but is more affordable and doesn’t need electricity?”

Prajapati experimented with different clay designs over several months and ultimately created Mitticool – a refrigerator that doesn’t use electricity and is significantly more affordable for villagers who don’t always have access to electricity. The refrigerator quickly became popular and his company now creates many other clay products.

This kind of innovation – born out of a desire to solve relevant problems in the cheapest way possible – has come to be called Jugaad innovation. Jugaad, a Hindi word, means a resourceful hack using available or frugal resources. Examples of Jugaad innovation abound in many developing countries like India, China and Brazil.

What is fascinating about Jugaad or frugal innovation, is not just the creativity behind it, but also that it is tied closely to reverse innovation. Reverse innovation refers to the trend of innovation from low-income markets entering and disrupting wealthier markets, a change from the typical flow of innovation. Trends show that in the 21st century more innovation, a large part of which is Jugaad innovation, is coming from developing markets with the potential to move into developed markets.

Radjou, Prabhu and Ahuja, who researched frugal innovation and popularized the phrase Jugaad innovation, identified six principles that underlie jugaad that include seeking opportunity in adversity, keeping things simple and thinking flexibly.

While some of the principles relate to having the right mindset, from a cognitive perspective, flexible and simplistic thinking is key to frugal innovation. Some creativity techniques that can help spur frugal thinking are:

Subtraction

While typical innovation adds more features and complexity, frugal innovation works by removing key components and then figuring out a way to make the idea work. For example, I recently gave a challenge to a group of middle schoolers to design a washing machine that doesn’t use electricity. By removing a central part of the product, students were forced to think in different ways to manually rotate a barrel. They came up with several different ideas like connecting the barrel to a stationary bicycle or using a pumping mechanism like that in a salad spinner.

Substitution

Another way to generate low cost solutions is to try and substitute with simpler or cheaper materials. Trying to find a substitute is the other side of the coin to typical divergent thinking. This approach can also lead to ideas that work well enough but at a much lower cost. For example, one student idea for a different challenge was to reuse discarded (and cleaned) socks to make low cost diaper linings.

Jugaad represents the best of creativity – being able to find a solution or a way out despite extreme resource constraints. And developing the skills and mindset for such innovation is becoming increasingly important for companies to solve important problems and stay relevant.

Posted on

3 Simple Ways To Build Scientific Creativity

In 1911, Elizabeth Kenny, a nurse in Australian Outback, was called upon to take care of a little girl who she thought had infantile paralysis. She wrote to her mentor, Dr. McDonnell, for advice who wired her back with a message to treat “according to the symptoms as they present themselves.”

Not realizing that the girl really had polio, Elizabeth started finding ways to alleviate the symptoms. She noticed that the girl’s muscles were very tense, so she used hot compresses which she theorized would help relax the muscles. The girl found instant relief from the hot compresses and they reduced her muscle spasms. Next, she saw that the girl could barely move her limbs. Once again, she hypothesized that the muscles needed retraining and increased blood flow. So she started a regime of motion therapy and massage (an approach that later evolved into physical therapy). The results were dramatic and the girl recovered and was able to walk again!

In comparison, the conventional approach to treating polio at the time was to immobilize the limbs by attaching splints which pretty much ensured that patients would not be able to fully recover their mobility. Elizabeth went on to treat many more polio patients, despite being rebuffed by the medical establishment. It took the medical community several decades to acknowledge that her methods of treating polio were indeed effective.

Not knowing that she was actually treating polio, turned out to be a blessing for Elizabeth. It led her to create fresh hypotheses based on what she observed, come up with creative techniques and test them.

Most advancements in science came by because of creative leaps in generating hypotheses or designing better experiments. Creativity plays an integral role in all real-world science explorations – from problem finding to generating and testing hypotheses. As psychologists, David Klahr and Kevin Dunbar who proposed the Dual Space Search in Science approach,  explain, “The successful scientist, like the successful explorer, must master two related skills: knowing where to look and understanding what is seen. The first skill – experimental design – involves the design of experimental and observational procedures. The second skill – hypothesis formation – involves the formation and evaluation of theory.”

So, how do we build some of this scientific creativity among younger students?

Research in scientific creativity can be viewed as an interaction between general creativity skills and science knowledge and skills. Here are a few simple approaches to build scientific creativity among students.

Problem Finding

Problem finding in general is considered a core aspect of creativity, and it extends to all domains including arts, math and even science. Real-world problem finding is more predictive of creative achievement than standard measures of divergent thinking.

One way to encourage problem finding in science is to have students list problems they want to explore in a science topic. For example, give students an exercise to think of as many research topics as they can, on subjects like the behavior of ants or the growth of plants. The idea is to give them a chance to think of what they already know and discover areas they want to extend their understanding in. 

Hypotheses Generation

The ability to generate many alternative hypotheses is related to success in science. However, research shows that children tend to get stuck focusing on a single hypothesis. One approach to build the ability to generate multiple hypotheses is to present a partially-defined experimental scenario or setup, and ask students to generate as many hypotheses as they can.  For example, give students an adjustable ramp and different balls as the setup to explore connections between different variables like height, weight, speed and time. That could lead to hypotheses around what happens when you roll different weight balls or change the height of the ramp and so on. 

Scientific Imagination

Scientific imagination is one of the key aspects in the scientific creativity model proposed by Hu and Adey. Einstein had often mentioned how imagining himself chasing a beam of light gave him the insights that eventually led to the development of special relativity. The role of such imagination in science, which is different from creative imagination, is now considered valuable.

One way to build scientific imagination is to give students story writing tasks on topics like “what if there was no gravity” or “the sun is losing its light”. The goal isn’t to just write an imaginative story but to get students to use their scientific knowledge to guide their story. 

Posted on

Asking Meaningful Questions in Science

In early 1820s, the French scientist and mathematician, Joseph Fourier, asked himself a very simple question: what determines the average temperature on Earth? Or in other words, when the Sun’s rays strike the Earth, why doesn’t the Earth keep getting hot?

Asking these questions made Fourier realize that the Earth’s heated surface emits invisible radiation (infrared radiation). And while he did not have the tools then to prove this, he also intuited that the Earth’s atmosphere plays a role in keeping the Earth warm. It took other scientists and their probing questions – like John Tyndall (what is the relation between density of gas and heat absorbed?) and Svante Arrhenius (how strongly is radiation absorbed by carbon dioxide?) – that finally proved that the presence of carbon dioxide and other greenhouse gases play a crucial role in warming the Earth.

Good questioning has always played a role in leading to creative breakthroughs in pretty much every domain from arts to sciences. It’s a thinking skill that underlies critical, creative and complex problem solving.

Unfortunately, research studies in science have found that not only does the number of questions students ask drop with grade level, fewer students ask questions of high cognitive level.

Simpler questions tend to seek or clarify factual information and are essential to build an understanding of the science topic. However, once there is sufficient familiarity with the topic, higher cognitive level questions can lead to a deeper understanding, creative and inventive applications and even transformation of the field. These “wonderment” questions try to find connections between concepts or extend the area by identifying additional aspects to explore.

Research studies have found that teaching students how to ask good questions can be quite effective. Students who received instruction or were provided a framework to ask research questions were able to generate more higher level questions than those who didn’t.

Model Based Inquiry (MBI), a more authentic way to teach science, also provides a natural way to structure the questioning process. A model, in general, is a representation of bigger system or phenomenon. It describes the different components, the relationships between the components and the mechanisms (that are often hidden) that underlie these relationships.

Another way to look at a model is that it tries to clarify three types of questions – what, how and why. The “what” questions correspond to the different components in the system. The “how” questions correspond to the relationships, or how different components affect each other. Finally, the “why” questions try to get to the bottom of how different relationships work.

All of these questions have the potential of changing the model thereby improving our understanding of the phenomenon. These model-based questions will typically lead to higher level, research questions in science.

Using the scientific model as a starting point to generate more high level questions can be an effective strategy in science education. As Professor Chin, who researches students’ learning approaches is science, says, “As educators, we know that the skill in the art of questioning is essential to teaching well. However, with the emphasis today on active learning, critical and creative thinking, skill in the art of questioning is also critical to learning well.” Using MBI has the potential to make this process more structured and less intimidating in the classroom.

Posted on

Model Based Inquiry For An Authentic Science Education

During a period of six months in 1821, Michael Faraday conducted a series of well-thought out experiments that broke some of the earlier theories about electricity and resulted in the first electrical motor. A few months before that, Oersted had discovered that electrical current flowing through a wire, could affect the orientation of a magnetic compass nearby. Over several experiments, Faraday showed that the magnetic field produced by the electrical current was circular in nature, and that electricity and magnetism could be used to produce motion.

But equally important is the experiments he chose not to do. For instance, he didn’t run an experiment to see the effect of electricity on the magnet under different light conditions. Why? Because it would not make sense to do so given what scientists knew about the nature of electricity.

The existing models that scientists had about electrical current had nothing to do with light. The prevailing notion of electricity at that time was that it was a material fluid as opposed to an energetic condition and completely independent from magnetism. So the experiments that Faraday designed were carefully constructed to either confirm or refute existing models of electricity and magnetism. And that’s what led him to advance the field of electromagnetism.

Unfortunately, the Scientific Method (TSM) as taught in schools today often misses this finer point.

To do a science fair project students often pick a question from a pre-existing list or construct one hastily with no real rationale based on their understanding of how the system or phenomenon works. The emphasis is on following the steps in the scientific process which effectively makes the whole exercise a guessing game with no deeper learning attached to it.

In a study of science education in schools, researchers looked at how middle school students in a classroom were approaching inquiry experiments on plants. Students came up with several ideas like feeding the plant coke, using various kinds of dyes or different types of soil. However, the teacher never asked why any of those questions make sense.  As the authors explain, “Do these students have any reason to believe (or hypothesize) that the physiology of a plant will respond in particular ways to these features in their environment? Because such questions are arbitrary—i.e., make no sense without the context of at least a beginning model for understanding the phenomenon—then any hypotheses emerging from these questions are likely to be little more than poorly informed guesses.”

In fact the most creative parts of science – generating hypotheses, theorizing from observations and designing experiments – get lost in the traditional approach of strictly following the scientific method.

So what exactly is Model Based Inquiry (MBI)? Using MBI allows students to develop “defensible explanations of the way the natural world works”, and it uses four kinds of conversations (often in an iterative fashion):

  • Organizing Prior Information: Without knowing something about a subject, or in other words without a starting model, constructing any hypothesis is like a shot in the dark. So the first step is to list out any information you already have – what the different components and elements are and how they related to each other.
  • Generating a Testable Hypothesis: Once students have an initial model, the next step is to generate hypotheses that are grounded in the model. The idea is to generate competing hypotheses to test specific aspects of the model, that can help deepen understanding of the underlying concept.
  • Seeking Evidence: This part of the conversation is around figuring out what kinds of data to collect to test the model, which can then be used to support an argument.
  • Constructing a Scientific Argument: The final conversation which is often missing in practice, is to tie it back to the model to support or refute specific claims about the model.

While at a high level this may look similar to the scientific method, the focus on the model during the process makes a big difference.

The scientific method, while being a very useful tool for structured thinking, has the side effect of oversimplifying science in education and going further away from how real scientists actually reason and think in science. Incorporating MBI has the potential to change how students relate to science and engage them at a deeper level.  

Posted on

Cognitive Underpinnings of Creative Thinking

50,000 years ago humans shared the land with other hominins like the Neanderthals and the Denisovans. But somehow, over the course of the next 30,000 years, every other hominin species went extinct while the modern day humans saw huge growth and advancement.

Some people point to the development of language and tools that gave us a Darwinian edge. But evidence of language and tools, some of which were fairly sophisticated, have been found in Neanderthals and the other hominins. So what made us special?

According to Thomas Suddendorf, professor and author, what set us apart was not language or tools, rudimentary forms of which exist in other animals, but our ability to do open-ended imagination and make connections between different concepts. This enabled us to do mental “time travel”, going back in time and in the future, and allowed us to foresee and plan for our survival. In addition, making connections allowed us to find novel and interesting solutions to problems that we faced.

From a cognitive perspective, our brain allows us to voluntarily think of a concept which then triggers another concept, which in turn triggers the next one and so on, leading to a stream of thought, something that likely doesn’t exist in other animals. As Professor Liane Gabora explains, “With this ‘self-triggered recall and rehearsal loop’ we could now activate and re-activate visions and dreams, such that with each successive conception of them they were looked at from a different angle, embedded a little more firmly in the constraints of reality as we know it, and potentially turned into a form in which they could be realized.”

This cognitive ability is the direct result of how our brain stores information associatively, and is the reason why humans are able to come up with novel and creative ideas.

Think about how a computer stores information. To store the word “apple” in computer memory, each word is broken down to its letters and each letter in turn is converted to its binary code and stored. For example, the binary code for “a” is “01100001”, for “p” is “01110000” and so on. That’s not how human brains store information.

Human brains store each concept as a whole, connected to other concepts. So the word “apple” is stored as a concept by itself and is linked to other concepts with different kinds of links. So “apple” might be connected to “fruit” by a thing to category link, to “red” by a thing to property link, or “rash” by a cause and effect link if someone is allergic to apples. These links have different strengths in the brain so the dominant link for one person might be apple to red, but apple to fruit for someone else.

When you consciously think of an idea, your brain automatically activates some of the connecting ideas and brings them into your consciousness, leading to a stream of thought.

This also explains why it is sometimes hard to think of new ideas or solutions. As we think about a problem, some of these links get reinforced and strengthened making it hard to change perspective or think in a different direction. In other words, “These same pathways, however, also become the mental ruts that make it difficult to reorganize the information mentally so as to see it from a different perspective.”

The associative nature of the brain also comes into play when it encounters ideas that are not related. To see how this works, look at the two words below:

                          Bananas                            Vomit

If you are like most people, the moment you read the two words, your brain automatically tried to connect the unrelated words with a causal connection, forming a scenario where eating bananas led to vomiting, leaving you with a somewhat unpleasant feeling. 

You didn’t have to consciously think of this, your brain did the work of finding the best possible connection between the two words.

These two aspects of the associative nature of our brain – activating connected ideas and finding connections between random ideas – are what make it possible for us to think creatively. In fact, most creative thinking techniques rely on these two underlying mechanisms in one form or the other to generate novel ideas.

  1. Traversing Connected Ideas: Techniques like “Slice and Dice” and “Cherry Split” in Thinkertoys or segmentation in TRIZ, work by forcing the brain to traverse different paths in the associative network by explicitly listing out the triggers.
  2. Adding a Random Component: By simply introducing a random element into the mix, the brain automatically tries to find the best way to incorporate the random element into the solution. Techniques like the “Brute Think” and “Hall of Fame” in Thinkertoys are an example of such an approach.

What made us come so far is likely because of our unique cognitive strengths – how we store and process information in our brains, combine different ideas and run mental simulations. These strengths allowed us to solve problems, make inventions and build on each others ideas, and they just might turn out to be key for our future as well.