The STEM games

We often speak about the sorry state of STEM (Science, Technology, Engineering, and Mathematics) and STEM education in India. We recognize the problem, but do not appear to have a strategy to improve the situation. This is not to say there are no honest attempts at improvement, but they have, at best, worked in minimal conditions.

In this short note, I present a model-driven picture with the hope that this may help us understand the problem and, hopefully, find a road toward good STEM policy and practice.

Game as a Model

A game is a rule-following activity, where both the players and spectators are immersed. Such a game, in the absence of spectators (or audience), is not sustainable. It is dependent upon spectators, and that too, many more spectators than players.

Although spectators may not have sufficient proficiency at playing the game, their participation, from the sidelines, is crucial. The rules and the actions taken by the players of the game are also understood by the spectators, and their feedback during the period of play, and in their review, is instrumental.

Some of the senior players, who are well-versed and have a comprehensive understanding of the rules of the game, become umpires. There is one other subcategory of players, the coaches, who are typically active or retired players themselves.

Spectators need to be players themselves, at any level, but understanding the rules of the game at some level of proficiency is necessary. Most games share similar patterns, and if we ever played at least one game, it is not difficult to play or appreciate other games.

Let us take STEM as a set of games scientists, engineers and mathematicians play. All those who have played a couple of STEM games at least once, and understood some rules of the game, will constitute the STEM spectators. The editors of the journals, senior STEM players, are equivalent to umpires, who understand the rules of STEM games very well.

A Pyramid Representation

A representation of a game-system as a pyramid may provide some light on the need and relationship between the spectators, the players and the umpires in a game. A pyramid model also offers a good clue about where each of the agents of the game-system emerges.


In the representation, borrowed from an ecological pyramid, the base of the pyramid includes people, who form the primary support system, followed by spectators, players, and umpires. It is essential to keep in mind that the spectators also know the game, though they may not be as proficient as the players. The umpires are not only proficient in the game, but they are also skilled in judging, indeed, often framing the rules of the game.

The pyramid representation also suggests the population of the game system, in the decreasing order of people, spectators, players, and umpires. About the proficiency of the game, the order is inverse.

A Lesson from Cricket

Let us take the cricket game-system. India is one of the top-ranking countries in the world, producing several world-class cricketers. Cricket game is arguably one of the instances where India has achieved excellence. There are vast numbers of people who understand the game as well as those who play the game. The base of the pyramid for cricket, therefore, in this model, is strong and bulky.

If the national team is kept captive in a remote island with the intention to destroy the game, another team will take their place in no time with similar proficiency. There is sufficient buffer in a resilient system, and cricket in India is one such. This is an example of how equity generates excellence.

However, if the national champions of the STEM game of India are kept captive in a remote island, with the intention to destroy STEM in India, another leading team will take a few generations to reach the proficiency level of the leading players. Whichever team finds itself immediately as a replacement will be far less proficient.

We do not have a resilient STEM game-system. If a similar situation were to arise in another leading STEM country hypothetically, it would not take generations to create new STEM champions. There are plenty of potential team members of comparable proficiency available.


Using the game model, the reasons for not being able to play the STEM game proficiently emerge in quick order.

Where do people learn to play cricket in India? Anywhere that looks like a ground. Not in a classroom. Where do students learn to play the STEM game? They do not play STEM game at all, they read about STEM game in a school, and do not play it, either in a ‘lab’ or in a ‘garage.’ We in India do not cover the ‘T’ and ‘E’ of STEM in our school education. In this scenario, a ‘lab’ is a formal experimental space, whereas a ‘garage’ is an informal one.

Consider the coaching system in place for games: the coach is necessarily a player, either active or retired. In India, for the STEM game, this is not true. The majority of STEM teachers are neither players nor spectators of STEM game.

Spectators of a game are possible only if they understand the rules of the game and play some game at any level of proficiency. We do not expose our students to any of the rules of the STEM game, nor do we allow them to play. Our system, therefore, does not make sufficient spectators of STEM. Their ability to consume and appreciate STEM is negligible.

We do not play STEM game with competitive proficiency because we do not have sufficient spectators. In their absence, our STEM players are, so to speak, scratching each other back, becoming spectators for themselves. When we want to share our work, we often have to participate in a conference abroad in search of a peer group. Local peer group is essential for developing any expertise.

The need of spectators may sound counter-intuitive, because one may think only STEM experts should appreciate STEM expertise. Though umpire level decisions are the domain of experts, the rules of the game must be shared with the community, which is capable of responding to the performance of the players. However, this will only happen when more people are allowed to play the STEM game.

Even though we have produced an occasional Ramanujan or Raman, we have no spectator class to judge their achievements. If we were an immersive STEM society, then we would more easily identify such talent. We need spectators to identify and nurture talent. At around the time of Sir C.V. Raman the Indian Association of Cultivation of Science had six fellows of Royal Society, among others who are equally proficient in the game.

How are STEM game spectators created?

If the game model is a fit for STEM and STEM education, the need to let students and citizens play the STEM game, at any level of proficiency, defines itself as a necessity. If the STEM game rules are not appreciated, the appreciation of STEM in society at large itself remains a significant gap.

The STEM curriculum should, therefore, substitute the preponderance of ‘reading’ about the STEM game, with actually playing it.

Similarly, the coaches of the STEM game have to be active players themselves. The concept of retired, i.e., no longer participating, players do not exist in this scenario, since coaches themselves either alternate or participate directly with students and other citizens.

Otherwise, a discovery of a Ranjitsinhji, Gavaskar or Sachin of STEM is either not possible or merely a matter of luck. Given the humongous population, while ‘luck,’ or statistical possibility, may exist, it is not as meaningful as participation in an activity or discipline.

Rules of the STEM game

The term ‘game’ is used here more as a metaphor. The defining feature of a game is that it is a rule-following activity. We shall focus on this feature of a STEM game. It is ironic that when we use ‘game’ to refer to an activity, it does not evoke seriousness. But, rule-following does evoke seriousness. So, let us focus on this serious feature and ask the following obvious questions: (1) what rules of the STEM game that we follow (the descriptive question) and (2) what rules of the STEM game that we ought to follow (the normative question)?

Neither of these questions can be comprehensively answered here. We need a book-length treatment for doing justice to these questions. But we can at least focus on some rules that we do follow, which may give us a direction to the STEM and STEM education policy.

One may think that to specify the rules of STEM game is too ambitious since it encompasses at least four apparently different domains, S, T, E, and M. The debate on what methodologies science follows or should follow is a question that is pursued by the philosophy of science, views there continue to be contentious. Similarly, the same questions when posed for technology, engineering and mathematics would make the problem even more difficult and controversial. If even the methods are not well defined, how can one talk about the rules? First of all, are methods and rules different? If they are different what relations do they have among them? Even if one admits that science and mathematics may have some specifiable rules, can we also make a compelling attempt to specify the rules for technology and engineering? Aren’t the latter more close to art, with creativity and innovation being integral to them? Can we specify any rules to be followed for creativity and innovation? What are heuristics, and how are they different from rules and methods?

All such above questions make the problem difficult to approach. So, the only way to turn this into an approachable way is to play the STEM game to define the STEM game itself: to create a microworld that makes all STEM games possible. Here the core concept is that of a microworld, so let us elaborate on this idea.

First of all, a microworld is not a microscopic world. The term “microworld” is introduced by Seymour Papert to make abstract ideas and operations concrete. A world constructed by stipulating constraints (rules) on the possible actions we can perform on a set of available predefined objects or building blocks. Usually, most microworlds are constructed with as minimal constraints as possible. The minimalism allows the players a challenge as well as a creative space to operate in. I am liberating Papert’s microworld, invented initially as a creative space to make students learn by constructing abstract representations, to characterize STEM games.

One primary reason why the model of microworlds is useful is that this idea helps us to see the common aspects of all four domains of STEM. A few examples will make this extension clearer. Let us take Alan Turing’s “microworld” which was constructed by defining a minimal set of operations (a head that can read, write, move left, move right on an infinite tape). This minimal set forms ‘building-blocks’ and also defines the field. Originally proposed as a mathematical theory of computation, Turing’s microworld allowed us to play in a verifiable manner to create the digital world. I need not argue how extensive this digital space (game field) can be, where almost every aspect of human culture is re-represented in a concrete manner so that an entire society could participate. This game has everyone, people, spectators, players, and umpires. In this space of computer science, it is difficult to separate the four domains of the STEM game as different from each other, except as distinct roles played by multiple players.

Within this massive “microworld” several microworlds can be constructed. Alan Turing of educational microworlds is Seymour Papert, who designed Logo, where an agent called turtle can be programmed to move in a 2-D space by simple operations like moving forward, right, and left by specified units followed by pen-up and pen-down. In a typical microworld, the inventor has no clue of what constructions are possible. Though one can retrospectively verify (prove) if the created construction is actually a result of the pre-decided rules.

Papert’s colleagues Mitchell Resnick and Uri Wilensky took the next step of creating a microworld of multi-agent simulations, such as NetLogo. It is a common practice to introduce the new science of complexity through Netlogo. It is one microworld where the creators of the world have no clue of who will, so to speak, inhabit in the world. Models created so far belong to mathematics, music, art, social science, economics, biology, physics and so on. This triumphant story vindicates the game theory of STEM that is being propagated here.

Looking back at the history of STEM, we could ask: aren’t the following also microworlds:

  • Pythagoras’ microworld of natural numbers and their patterns
  • Democritus’ atomic microworld
  • Plato’s and Aristotle’s microworld of relationship between ideas and propositions to explain the world of thoughts and beliefs
  • Panini’s generative grammar for Sanskrit language
  • Euclid’s microworld of geometry
  • Archimedes’ microworld of machines using balance and pulleys
  • Newton’s microworld of interacting point masses

Each of them has applied their rules explicitly enabling inter-subjective judgment possible. Rules help us in STEM to ensure rigor, consistency and community participation making STEM a genuinely social endeavor.

Microworlds are artificially constructed rule-following possible worlds based on minimalist building-blocks. They may produce finite or infinite worlds. Are they same as what we call models? Is modeling same as constructing a microworld? It is an important question, let us pass this question for some other time.

There are other rule-following cultural practices, not usually considered part of STEM game, such as classical music and dance. Playing such seemingly different games also support STEM imagination. For example, Manjul Bhargava’s exposure to Indian classical music during his childhood days helped, according to him, develop mathematical imagination.

This interpretation has the advantage of viewing what we do in STEM, whether with media (symbolic operations) or matter (engineering and technology operations), stand on similar roots. The view of theoretical modeling and mathematics as a microworld construction game on the one hand and engineering and technology to make corresponding physical microworlds, on the other hand, provide a sufficiently comprehensive picture of the roots of STEM. The possibility of creating physical microworlds give STEM participants tremendous confidence in how close they are in understanding the actual physical world.

Whether we play language games in STEM or engineering games, we construct artifacts. Construction and de-construction are common operations of STEM game.

To Conclude

Microworld as a game field for learning as proposed by Seymour Papert is extended here to all of the STEM activities. This is done deliberately to make the point that the context for learning should not be different from the context of execution by experts. Game metaphor clearly guides us to expect the teachers of the game to be the players themselves. And students will learn the game by playing, and there exists no more straightforward way of doing it.

STEM is rooted in cultural practices, such as language, which is rule-based. However, other cultural practices may not always apply as rigorously as STEM does. STEM’s adherence to rigor is manifested in seeking definitions to eliminate multiple interpretations. Multiple interpretations is a game spoiler in STEM. STEM pursuit requires removing ambiguity as much as possible.

There are several other aspects of the STEM game that we could not cover here, which are better described by Thomas Kuhn as disciplinary matrix.

Formation of social groups, as clubs, is part of any cultural activity. Science clubs, whether it is Royal Society or Indian Association for the Cultivation of Science, were created to promote STEM culture. After independence, though, we established more and more Government owned institutions, which restricted broader participation. The existing colleges and universities graduated students based on a syllabus, which did not focus on the rule-following games of STEM. Neither the admission tests, like JEE, nor the graduation exams look for student’s familiarity with practicing STEM games: content knowledge is tested not culture. One-third of human life is spent on a misdirected preparation. Instead, if we focus on rules, we will learn how to create content rather than memorize content.

One intervention game that can transform the existing situation: reform admission tests to check on the skillful use of the rules of the STEM game. This will transform existing schools and colleges, which will metamorphose classrooms into STEM studios. This will also create the need for coaching shops which will become STEM clubs, maker-spaces, tinkering spaces. Commercial agencies adapt to change in the rules (policy) much faster than the conservative school and college system. Can we make this reform? But, should we? Are we convinced? Let us engage and examine these questions critically as the first step.


Hacking, I. (1983). Representing and intervening (Vol. 279). Cambridge: Cambridge University Press. (Role of engineering and technology in realizing the goals of natural science.)

Kuhn, T. S. (1974). Second thoughts on paradigms. The structure of scientific theories, 2, 459-482. (Disciplinary matrix as a proper replacement for paradigm.)

Papert, S. (1993). The children’s machine: Rethinking school in the age of the computer. (Microworlds, constructionism, mathesis and Logo)

Resnick, M. (1997). Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. Mit Press. (Multiagent simulations and complex systems.)

Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with NetLogo. MIT Press. (Microworlds for multi-agent simulations.)

Wittgenstein, L. & Anscombe, G. E. M. (1953). Philosophical investigations. London, Basic Blackwel. (Cultural practices as language games, see sections 65-78.)


Interesting article.

I do love the analogy to Cricket and where and how we play it with the lack of access to the T and E of STEM in Indian education.

I wonder as you detail the Game aspect of STEM, if you could also go on to similarly draw how variations for a Game based on rules, equipment, etc are also similar to variations and even game changers in scientific enquiry. The rules need to be understood, the game played, but it is also important to tinker, to innovate, to redesign. We did not have the helicopter shot in cricket till recently and so on and similarly theories do need to be similarly played with to allow for growth. Bit this can be done only with immersion, by establishing varied interconnections and not just repeated routines. The use of volleyball and running and weightlifting and such in preparing for the game of cricket is akin to say learning a language or music or painting and such to better play the game of STEM.

Thank you for this very interesting article.


This article is interesting in the way it deciphers the STEM game, taking into the analogy of the cricket game and deriving deviations from how it should be played and how it is being played in India. In a vast country like in India, having diversity in every aspect of it, you just name it. Here the competition of proving yourself best so that you will get recognition is at its peak. Nevertheless, this game is played in India with certain different rules. Here there are certain parameters being put forward as a measure of you being a good player. The rule modifiers are certainly not always those who are proficient in the game. One of the major such parameters is the number on the marksheet or on the CV. Just like the number of centuries in cricket or number of wickets in your bag in cricket defines your consistency as a player, here the number is what only matters in most of the cases.
This number doesn’t stop following you till the end of the life, in the current scenario. I have described one such category of number which is very convincing today for scientists in the link below (additional article describing a scenario to understand this article, otherwise this and that link article are independent). The number which actually came into picture through statistics as an expectation to get a curve and that curve will define ones individuality or consistency. The problem happened when we put a selection criteria to a certain domain of the curve. People with their “consistent effort” trying to get into that domain only making that graph uncorrelatable to give any pattern, having a very high standard deviation from normal phenomena.

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