Learning Mechanics in Tyto Online

Learning Mechanics in Tyto Online

Hello there! I wanted to take some time to outline how we view learning within Tyto Online. The experience we currently have in the game does not have all of this in it, so I’ll be clear on what is currently in-game, what is in progress, or a feature we’re considering for the future.

This is a bit of a long post, but it’ll be a starting point for those people who want to dig in on the learning design with us!

This is the model I’ve designed to explain our learning theory:dKqxks1

First, the Base Game World presents a lot of really compelling elements to go from and each one is important to learning as players begin the game.

Then the user does Quests where they’re taught content more directly. As they complete Quests, they’ll be unlocking more in the Sandbox experience. Many players want to jump into the Sandbox and unlock more of it in the Quests as they play both alongside each other (although some just do all the Quests first). After the Quests are done, they’ll be able to continue playing in the Sandbox, including with Weekly Challenges to accomplish. The more activities the user completes, the more their knowledge — and their autonomy — grows, since the Sandbox is more open and exploratory.

Our first module, Ecology, has a set of ~40 Quests and a create-your-own ecosystem Sandbox for players.

As you continue to read, you may see this as an idealized version of what an edu-MMO can be, and I would agree. I don’t think we’ve successfully pulled it off yet, and our current designs and quests certainly have room for improvement. Limited resources mean we don’t get to make everything we want quite yet! But we want people to see where we’re heading with this and to give us feedback during Early Access to help us reach the potential of what this can really be.

Base Game World

Many game designers already discuss that game design and gameplay are basically a form of learning — learning the rules and systems of the game in order to progress. As I studied learning theory while working on a PhD in education, we talked about ideal learning environments and everything kept linking back to my gaming experiences, especially in social online games.

  • Context — the story of the game and its world provide context to help players understand what’s being learned and make mental connections more fluid. We don’t want people to ask, “Why are we learning this?” because it’s already part of the context — Non-playable characters (called NPCs, which are characters we design into the game) and you, the player, are using the information for a reason during the process of gameplay.
  • Identity — taking on the identity of a scientist and learner is important so children can see themselves as capable learners and part of the gameplay (shown to be very important in successfully learning science).
  • Motivation — reward structures in the game increase motivation to complete more learning activities (such as getting more currency to buy more clothing, leveling up, etc.).
  • Immersion — increases involvement between the player and the content.
  • Affective Involvement — deepens interaction between the player and the content and helps with retention of knowledge, as we remember things better when they’re tied to emotion.
  • Social Learning — communities share knowledge and increase their learning pool together; also presents opportunities for developing important social skills.
  • Goal Setting — goals within the game lend themselves to self-regulated goal setting, an important skill for learners.
  • Collaboration — playing online with others, completing tasks together, is great skill development for what people refer to as “21st Century Skills.”

Unfortunately, when most people think of educational games, they really only thing of motivation, and maybe immersion, but as you can see, there is so much more to it.


Quest to Learn

So the first part of students actually learning the content is based on Quests. We see the Quests as aligned with an “inquiry-based learning” approach, which has been shown to be very effective for learning science. As you can imagine, this basically means that you solve problems in order to be guided through the learning process — gathering needed background information, collecting information about the current situation, and learning as you solve in the context of a problem.

Right now we have a decent number of Quest mechanics that we use to do this, and will continue to build these out as we progress.

Basic Quest Mechanics

We have a lot of the basic Quest mechanics you’d expect: collecting items, talking to NPCs, going to certain locations, etc.

You’ll find a lot of our current Quests are about collecting poop, because that happens a LOT in ecology. Some of these lead you to other Quests, and others are just for helping players understand new contexts for why poop would be needed.

  • An example we like in the game right now: collect poop to start you off on a Food Web Quest.
  • An example we don’t like in the game right now: using poop to get DNA samples, but that’s where the quest ends. The idea for this quest was actually to collect DNA samples for a DNA bank, as that’s something scientists do in real life right now to make sure we have diverse sets of endangered species’ DNA , which is super cool. But we had some limitations with the Quest mechanic toolset, so right now it’s just picking up poop for that purpose. This will be improved in the future.

Categorization Quests

Also pretty simple, but if you think about it, categorization happens a LOT in learning. Is this abiotic or biotic? What type of symbiosis is exhibited? Recycling or Compost?

Here’s an example of it in action:

Screenshot 2017-06-21 13.55.31

Detective Quests

A lot of science standards revolve around using empirical evidence to make arguments and draw conclusions. So we designed a Detective-style Quest where the user finds evidence in the game world. Basically, the student uses their Observation skills to find evidence, or analyze graphs, or use what they learned from previous quests all in their  Evidence Log.


After you’ve collected the evidence, you make an argument: and try to convince the Quest-giving NPC of whatever conclusion you’ve come to.

 AB_After3-900x505 (1)

 AB_After2-900x506 (1)


Analyzer > Food Web Quests

In these quests, you first collect animal poop, then figure out what bone, fur, etc. fragments were in the poop of carnivores using the “Tranquil-icer” on animals and taking a DNA sample. After you’ve figured out what animals were eaten, you’re able to make a food web to represent this.


We’re going to be updating this UI soon as we know it’s not our most polished, by far!

This was designed to be more open, so we’ll be able to re-use the Analyzer and Flow Chart Mechanics when we do more types of Quests — anything a model needs to be designed for!

“Item Action” and Spawning/Unique Tasks

This was just implemented recently, so we’re going to start using it in more quests! Basically, this mechanic lets people use items for quests that do various things.

For example, when you release flittermice for a quest where you’re testing to see if they pollinate plants, you now see them spawn and fly off!  We even have a quest where we used an item to let you turn into a jackrabbit for a detective quest (you get to keep the item afterwards, of course).


Specific Heredity Quest Mechanics

Now that we’re building Heredity, there are a few new mechanics we’ve been adding, like doing a Punnet Square puzzle!  There will be more information available about these soon as they go live.  

Learning Sandbox

Each of our Modules also has a learning Sandbox.  As we mentioned, as students level up through their Questing, they will unlock more in their Sandbox. It’s an important element of the game, for learning and especially re-playability.

For Ecology, this is a create-your-own ecosystem we call the H.E.L.O., or Holographic Environmental Life Observatory.  The purpose of this is to learn more about the ecosystems so that Tyto Academy may be able to better help these species. Students receive Research Points as they progress, which they use to unlock new species across the five ecosystems they can build right now.

This follows a more experimental learning model where students are learning through trial and error, and also provides opportunity for depth and self-directed problem solving.  One of the powerful elements of games is that we can recreate systems and let students explore those, manipulate variables, and see the outcomes. They can do this for a nearly infinite amount of time depending on how interesting they find it. It’s creative, learning, and a reward in many ways as the act of creation is rewarding.

We first released this as a stand-alone game called Tyto Ecology, and here’s some video responses of YouTube streamers playing it:

For Heredity, the Sandbox we are building is a Drakon Breeding!  Drakons are dragon-like creatures that the players are helping to repopulate and increase their genetic diversity… but of course, they also get to create a lot of awesome looking dragon-type pets in the process!  This is also a full set of complex systems, including dominant/recessive genes, but also codominance, incomplete dominance, mutations, environmentally unlocked aspects, and more!

Heredity Module (1)

Read more about that on the Tyto Online blog, at this link.


We have a LOT of work to do, and this is just the beginning. What you’re playing now is the Ecology and first Heredity Quests, with the Ecology Sandbox as well, but we have a lot of improvements to make. (We’ve also added a feature to clear quest progress so you can replay them with the updates as we go).

The first attempts for everything were slower, because instead of directly coding them in, we’ve been building back-end tools that are more scalable for us to add and build from. So expect things to continue to speed up in the next few months as we make improvements on our base mechanics and toolsets and get new content in even faster!


Lindsey Tropf

Lindsey Tropf

Founder & CEO of @immersedgames // School psychology doctoral candidate interested in #edtech, game-based learning, and using data.

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