Education is the most critical foundational engine of a discipline.

Not only because it shapes new minds to perform in the field but also because it creates a primordial soup for innovation. Teachers are detached from the industry’s performing necessities and can analyze and explore new routes of understanding. However, here often lies the issue. Education begins a misalignment process with actual work and builds a world that doesn’t correspond to practical use.

The engine no longer provides thrust to the wheels.

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To properly fix the engine, we need to understand what’s wrong.

We’ll start by going back to the basics to understand the very act of “teaching”. This will give us a foundation to understand what’s wrong with what we teach in Game Design. In the end, we’ll look at the consequences of that on the learning environment, which ultimately leads to the nightmare most beginner Game Designers face at the start. Awareness of these issues is not a way to make us sad, but to acknowledge how we can improve how we learn a complex matter like Game Design.

So here’s today’s menu.

• What Does It Mean To Teach Something?
• The Teaching Quality Is Not Only Given By The Teacher’s Skill
• The (In)Sanity Of The Game Design Discipline
• 1 Lack; A Domino Of Issues

Here we have it.

We have a lot to discuss; get comfortable, grab your favorite beverage (I pulled out a delicious hot tea 🍵), and let’s dive into it.

What Does It Mean To Teach Something?

We can’t transfer knowledge between brains.

You may remember Neo learning Kung Fu in seconds with a USB-like device plugged into his brain. That was the Matrix, and this is the real world; it won’t work. The concept of “knowledge transfer” is always used (or it should be, at least) metaphorically when talking about teaching something to someone else.

What happens is more of a “building process”.

When we teach something, we create a sensory environment. Even the most boring monotone lecture creates an environment (surely a bad one, but still). The purpose of this environment is to help students build knowledge in their brains. We’re indirectly reconstructing it, though.

This explains why people understand things differently in the same class.

This is not only because of different brain capacities for elaboration (simplified as intelligence) but also because of different information already present. These 2 processes work together. Learning something involves connecting new information (elaboration) with other concepts you already know (cultural baggage). The brain does that every time we engage in a learning endeavor.

But let’s understand what exactly this knowledge is about.

In other words, what’s the content of our learning?

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What does it mean to have knowledge?

It seems abstract and hard to measure. Yet, this is only true if we look at it with a judging eye instead of a descriptive one. Knowledge of a subject boils down to knowing (well or not, it’s not the point here) 2 generic things: Models and Heuristics.

By Models”, I mean what’s commonly called “Theory”.

It includes many elements like formal definitions, processes, laws, principles, assumptions, data, techniques, etc. The more we, as humanity, know of a subject, the more and more accurate theoretical models individuals have to learn.

This type of knowledge is mostly generic and abstract. Despite being often perceived as a negative thing, it’s actually a positive one because we need it. It allows us to understand how to approach the subject and how to think about it.

By Heuristics, I mean solutions to specific use cases people use to perform.

They’re strategies and mental shortcuts, mostly executed unconsciously when automated. Professionals develop them to solve specific problems and, for this reason, are not adaptable to many situations. They often have very tight limits of usefulness. Heuristics are generally acquired through direct practical experience.

Someone faces a problem and finds a repeatable way to solve it quickly most of the time. Also, through practice, it can become part of the unconscious way of performing in the subject.

So, teaching means creating different scenarios to build these 2 types of knowledge.

Depending on which type of knowledge we need to teach, we could leverage various techniques and change the environment accordingly. Yet, Models and Heuristics both remain the focus of the “what”.

A perfect example of this process gone well is with the so-called “expert”. The word “expert” comes from the Latin “expertus”, meaning “having expertise”. But since Latin is a dead language and etymology is an argument for those who no longer know what to say, we look at today.

An expert is a professional with 2 elements:

• A strong mindset and understanding of the field (Models)
• A massive amount of practical techniques, strategies, and shortcuts (Heuristics).

Packed with both, an expert can make high-quality work fast and efficiently.

So you can’t be a “true expert” without being a kick-ass on both.

Ok, now that we have all the concepts in place, we can get into the weeds of the relationship between Theory and Practice.

The Teaching Quality Is Not Only Given By The Teacher’s Skill

Ok, first things first; let’s wipe out a common confusion.

Theory and Practice is a false dichotomy. Using “and” between them instead of “vs.” is on purpose.

Despite what many people think, they’re not opposites but just two sides of the same coin. They’re the common terms for Models and Heuristics, exactly how we’ve defined them before. They are the content teachers need to teach and students need to learn.

This point is crucial to keep in mind and leave out of the door all those stupid fights between Theory and Practice that spawn during teaching and learning debates.

Good, we can now reason around them more clearly without wasting time.

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If Theory and Practice are not opposites, they must have some sort of relationship.

And they do indeed! The state of Theory and Practice is a good indicator of the" sanity" of a discipline.

Now, the concept of "discipline sanity" is not an actual term. I made it up at this very moment to explain this concept. But bear with me; it will be useful for our reasoning.

Let's start by what "discipline sanity" is not.

It's not how much has been discovered in a given field of study. That's not quantifiable because you would need to know the total amount of knowledge in that field, and that's impossible. And it's not the average quality of professionals operating in the field either. So, with "Sanity", I mean how much that discipline can improve over time.

It's not really measurable; it's more a result of a debate about the state of the discipline. The point is that the "sanity" of a discipline is based on the Theory-Practice ratio.

A discipline with "good sanity" will constantly improve.

It will do it because there's a constant flow between Theory and Practice. Professionals' practice is formalized to crystallize new theoretical models. New theoretical models are tested in practice and continuously improved by analyzing the results.

A discipline with "bad sanity" instead will stagnate.

Theory and Practice won't communicate. Professionals will ignore the theoretical models because they're useless and don't represent real-world applications correctly.

Researchers and Teachers, while constantly diminishing in numbers, will lock themselves in a never-ending useless discussion disconnected from practice. There can't be an improvement (or at least it can at a very slow rate) because practice is never formalized into frameworks. But there's an even more interesting part to all of this.

We can analyze this relationship between Theory and Practice on 2 levels.

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We can make a quantitative or qualitative evaluation.

A good quantitative relationship means we have enough formalized models to represent, guide, and discuss professionals' practical actions in the field. Basically, we have the words to describe what we do. A good qualitative relationship, instead, means formal models correctly represent practice. In other words, professionals can be trained with them and use them to perform in the field.

The evaluation on both sides gives us a good understanding of the "sanity" of the discipline. And the best (or worst) part of it is that "sanity" dramatically influences the quality of the teaching.

So, what about the Game Design field from this "sanity" perspective?

You'll probably already have some thoughts while reading, but let's analyze the situation in detail.

The (In)Sanity Of The Game Design Discipline

Let's start with the painful side: Theory.

It's honestly tough to imagine a worse situation than Game Design's at the moment. There are no major theories or models and, as a consequence, no standards. Wait… to be fair, there's one thing we pretty much all agree about its importance. The Game Design Iteration Cycle.

Don't celebrate too much, though. The agreement stops at the name since there are many different opinions about how this Iteration Cycle actually works.

If we dig a bit more, we can find some other frameworks.

They try to represent a game's anatomy from different perspectives, like geometric patterns, resource flow, etc. They're even impressive attempts, and some of them are very well put.

However, they're all partial approaches that can't encompass every situation. Also, most of them, are very clunky to use since there's no precise method underneath them. Another major issue is that they try to include all 6 Game Design branches in a single framework, which is a crazy huge task.

To make this worse, there's "Game Design Research".

The little you can find is a murky pool of stagnant water. And it's pretty much non-existent when it comes to building models of understanding and practical methodologies.

The vast majority of research endeavors are split between 2 main areas:

• Applying psychology to player's behavior.
• The long-tail debate about gameplay and narrative.

The first is interesting yet tangential to real Game Design practice; the second is plain pointless.

The lack of both theoretical models and research creates a "negative combo effect" to the worrying point that none even agree on the basic terminology of games. I don't mean high-level stuff, but basic concepts like "What's a game?", "What's a game mechanic?", "What's gameplay?", etc.

We're an industry that can't even define what it's doing.

Ok, fair, but what about Practice, then?

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Of course, we have a bit of relief watching the practice side of Game Design.

Great professionals are honing their craft and designing amazing game experiences. But don’t go too far with that (sorry for ruining the party here again).

We want to focus on 2 main problematic points:

• Competence reduced to Heuristics
• Game Design “Best Practices”

They seem like distant points, but, as we’ll see in a moment, they are strongly related.

The first essentially means that the vast majority of Game Designers’ skills are made of heuristics.

As we’ve said at the beginning, they have many pros and cons. They’re very fast and helpful in many cases, but they’re not reliable and adaptable because they always refer to a specific context.

Relying too much on heuristics is not “real competence” since you don’t know what you’re doing. This has obvious dangerous consequences for the individual Game Designer, but that’s not it. It creates an environment where veterans sharing their competencies (on web posts, books, videos, etc.) can only share heuristics because that’s all they have.

And this is where the second main point comes in.

From a beginner’s standpoint, the Game Design world is full of “Best Practices”. Unfortunately, the more you collect best practices, analyze them and use them, the more you realize the truth.

They’re not “best” practices but just practices (when they don’t contradict each other, which happens frequently). They’re presented (and often wrongly perceived) as needed and working independently from the context. Yet, it’s the exact opposite (because they’re heuristics). They create in the beginner’s eye a false perception of strict rules, design objectivity, and one-way road approaches.

And that’s not a good learning environment where honing the craft.

1 Lack; A Domino Of Issues

So the #1 issue is the lack of practically working Game Design theoretical models.

As we’ve seen in the previous episode, it’s a major problem, particularly for the beginner’s learning process. However, because of the Theory-Practice relationship, concerns must be on both sides. A discipline with issues on the theoretical side will also have issues on the practical side. On the other side, having good frameworks leads to improving and refining the practice side.

We can find a famous example in Physics with Einstein’s General Theory of Relativity.

More than a century ago, how we see and interpret the world flipped on its head. It also led to practical applications that were never imaginable before. Einstein didn’t “discover gravity” or “make gravity work in a certain way”. Gravity has been there and working the same way since the dawn of time.

What good Albert did (and what theoretical research does in general) was develop a descriptive model to represent how gravity works. That formal model changed our understanding and allowed many people after him to create new things by leveraging that new knowledge.

You may have a legitimate objection to this.

“Ok, great, but Game Design is not Physics; it’s an artistic medium, so it’s inherently more focused on practice”. I half-agree with this.

Yes, Game Design is not Physics, and it’s not Science in general either. Yet, this doesn’t logically translate to “there can’t be formal models to design a game”. The repulsive nature (often from veterans) of formal models in artistic mediums is generally based on a wrong perspective of the concept of models. There can’t be a “magic formula” for Game Design. Formal models in artistic mediums are always thinking tools empowering artistic decision-making.

Here lies the difference between a prescriptive approach and a descriptive one. But this is another topic for another time.

Let’s focus on how this lack negatively influences the Game Design field.

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The lack of proper theoretical frameworks starts a domino effect.

It’s not by far inevitable, but it’s the general trend. As we saw in the previous episode, it all starts when a beginner approaches Game Design for the first time. What happens is a chain of effects that is hard to stop.

You can’t develop the proper Game Design mindset.

A correct mental model of how a discipline works is crucial for understanding and navigating it. If you approach literature with a scientific mindset, you won’t go too far as much as if you consider scientific theories like a “narrative point of view”. However, even without working Game Design methodologies to rely on, you need actually to do something.

So, you can’t help but apply a trial-and-error approach.

Unfortunately, this is not just a beginner's problem. It also hinders veterans since they do things without knowing what they’re doing. Of course, it’s not their job to understand it as a teacher would, but being conscious of our own process is a crucial step towards continuous improvement.

Once a beginner becomes a veteran, he gets absorbed by the game industry. He’s a great professional for sure, but Game Design as a discipline has not benefited from it.

The “sanity” of Game Design hasn’t changed.

And that’s where the long-term effects come in, the ones we’re starting to witness.

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Theory and Practice issues make Game Design stagnate by hindering innovation.

We could open an entire episode about this, but the kind of innovation I'm pointing my finger at is not like "creating a new genre". That's good, but I'm focusing on the methodological side. Game Design has gotten complicated year after year, but technological advancements mainly drive it. The innovation I'm focusing on here is about understanding what games are and how we craft them.

How we design games has not changed much since the dawn of the industry.

We only make bigger productions with absurd costs, which I see as a bad signal. Of course, I don't want a Game Design revolution each year, but we're close to the opposite: stagnation. That's why teaching Game Design is so hard, and based on the same approach we discussed before.

Trial and error.

The more we leave behind a random approach based on "intuition", the more we can improve the "sanity" of the field.