Gamify your classroom – Part 1

Online games do have an entertainment value, which if properly harnessed, could be a powerful learning mechanism to optimise the learning capacity within a short time. Learning outcomes has to be a prominent point here. It is not helpful to play Space Invaders for a whole lesson if there is nothing to be learnt at the end of the day.

Admittedly, up to a few years ago, I was still a skeptic when it came to mixing games with learning.

‘But education isn’t about entertainment! It is a deliberate (and at times painful) process that allows benefits to be reaped at the end of the journey, as long as the student perseveres.

Picking up life skills like mental strength and discipline is part of the learning process, and they will be eternally grateful for this opportunity.”

old me

However, my thinking has changed somewhat through the years. Especially after picking up new hobbies and skills, and started re-examining my own learning curve to realise that, yes, there has to be a fun element to ensure a positive mindset to internalise learning.

Gradually, I started looking at infusing more games into classroom time to monitor how students learn under various conditions. With some experimentations, I isolated various variables of what makes certain games exciting and which features make them such valuable tools for developing a certain skill.

For example, do time-based games and point-based games offer the same learning outcomes? If so, what makes me want to choose one over the other?

Are team-based games more appropriate than individual game modes for certain learning purposes? If so, when is a good time to tap on the team mode, and when should the individual game mode be activated instead?

So, here is a list of lighthearted online games which students are able to play on their own devices, either independently or as a group.

To further help discern the educational nature of the games, I have included a short writeup of how such games could be facilitated in class, and the learning goals that could be set.


Semantris is a set of word association games powered by machine-learned, natural language understanding technology. Each time you enter a clue, the AI looks at all the words in play and chooses the ones it thinks are most related. Because the AI was trained on billions of examples of conversational text that span a large variety of topics, it’s able to make many types of associations.
Check out Google Semantic Experiences to learn more about how this technology works.
Built by Ben Pietrzak, RJ Mical, Steve Pucci, Maria Voitovich, Mo Adeleye, Diana Huang, Catherine McCurry, Tomomi Sohn, and Connor Moore.

How to play

word association can be fun too

Look at the list of cascading words and focus on the top of the list.

Type in an associated word related to the highlighted word, and watch the word list re-rank based on relevance.

The suitability of your answer determines how many similar words on the list can be struck off, hence determining your score.

Keep at it until the list hits the top of the screen.


Definitely one for the language classroom. I played this several times before writing this post, and already could feel the mind trawling through a more extensive vocabulary while typing. I’m guessing this would have the same effect before a creative writing assignment, to quickly assess the language competency of the room.


Land Lines – Chrome Experiments

Land Lines is an experiment that lets you explore Google Earth satellite images through gesture. Using a combination of machine learning, data optimization, and graphics card power, the experiment is able to run efficiently on your phone’s web browser without a need for backend servers. This is a look into our development process and the various approaches we tried leading us to the final result.

I must admit that this is a pretty cool thing to see.

Travel has always been something I’m fascinated with, so seeing various parts of the worlds pop up on screen based on simple doodles does provide inspiration to shortlist places worth visiting.

But how does such a neat feature translate into classroom teaching?

How to play

How do simple lines resemble parts on Earth?

Draw different types of lines on screen.

Watch how the AI calls up various geographical features around the world with the similar line type.




Bringing awareness of various geographical formations into the classroom is a helpful way to kickstart a discussion on environmental awareness.

My first impression of the various land lines is that there are an awful lot of highways. And the necessity of such concrete infrastructure for sustaining megacities does lead us to take a good look at the world we are developing around the human race.

Another way to go about this would be a how-much-you-know about the different spots around the world. How many (adults included) could confidently locate where Belarus is? Or Ternate?

One more cool feature is Land Line’s ability to list out different places based on one shape drawn repeatedly.

[Fun challenge: draw 10 circles in a row on Land Line and see how many different spots around the world pop up on screen!]


AutoDraw is a new kind of drawing tool that pairs the magic of machine learning with drawings from talented artists to help everyone create anything visual, fast.

How to play

Hard to be bad at drawing anymore

Make an absymal attempt to draw something on screen.

Gape in astonishment at how AI deciphers the feeble attempt, and offers a list of items that most closely resemble your try.

Choose the most likely item (which you will not likely master anytime soon).

Use various editing tools to soup up your sketch.


This is a helpful tool to give students some hope at leaving a good impression on a blank canvas.

I can see a lot of potential for students to develop their own portfolio in the domains of iconography or design. Simple line art which they can be proud on, and represented on various mediums like class art, display profiles or even t-shirts.

[Hot tip: Predictive feature here is pretty good, so the more you sketch, the closer and more intricate the guesses become]

Quick, Draw!

Draw your best under 20 seconds!

Can a neural network learn to recognize doodling? Help teach it by adding your drawings to the world’s largest doodling data set, shared publicly to help with machine learning research.

How to play

Within 20 seconds, attempt to draw whatever prompted. The robotic guesses will throw you off initially, especially if you choose to respond in indignation “What broom? I’m trying to draw a car here”, but it is all good fun as your sketch becomes more increasingly recognisable as the time runs out.


Quick, Draw! is a great ice-breaker to start a quiet lesson. Have a student try this in front of the class. Challenge them to see how many correct guesses they can nail in under a minute!

Discover how daunting it can be to work under pressure. With a ticking timer and many eyes on you, how many of them can block out the distraction and perform as they do under normal calm conditions?

Do you have any teaching ideas based on the games above? Or are there other games which your students are having a ball with, and are worth sharing here?

Drop a comment below!

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