For my masters thesis, I tackled the problem of educational games. Why are educational games a problem? Because the mass image of them is simply “quiz+rewards” – what has been referred to as “chocolate coated broccoli”. This analogy is particularly touching to me, because even though I like broccoli normally, the idea of coating it with chocolate repulses me. Similarly, the idea of smothering learning with patronizing encouragement and “rewards” makes the joy of learning less palatable.
In my thesis, I try to put into words some principles for producing games for learning, games that are enjoyable yet impart knowledge that is valued in the real world. Roughly, this ends up with me suggesting that games should be built by simulating a subject area, tightly coupled with structures to support both game driven and free playing experiences. In detail, I provide a list of stuff you can do to up your educational game, with a wide range of examples from mainstream games that you’ve no doubt heard of, and likely have played – summarized in the graphic below.
Whether you’re curious or horrified, I encourage you to read the full thesis! I hope that it sparks topics for discussion, and leads to more awesome games with a serious experience at heart.
I’ve been noticing steam messages seem to seriously reduce the audio of my music player and youtube videos and what not. It was a bit frustrating, so I searched for it and found a typical tech thread here. This didn’t help at all, so I carried on hunting and found the answer burief in steam’s forums, it’s a Windows setting which makes other things quiet when you’re “in a voice call” (which.. well, steam messages don’t really fall into that category). Anyway, file a bug report with steam if this irritates you, and find a workaround/fix here:
Among other things, Bloom’s taxonomy allows us to categorize learning experiences. Bloom’s work was revised somewhat by Anderson a bit later, and it’s that revised edition I’ll describe here.
A taxonomy is a way of arranging things, and the revised Bloom’s taxonomy has two dimensions for categorization, the knowledge dimension and the cognitive dimension. Here they are in tables with examples.
Crude oil can be made into gasoline
Crude oil is a mixture of many different hydrocarbons including gasoline.
Mixtures of chemicals in general can be separated through distillation, including gasoline from crude oil.
Determining if a chemical mixture can be separated with distillation is possible through internet searches or experimentation with different temperatures.
Crude oil can be made into gasoline
Draw diagram showing how gasoline is extracted from gasoline
Set up alcohol distillation in test tubes
Given a set of 20 liquids, determine which are mixtures separable by distillation
Compare your methods to those of your classmates
Try to make brandy by distilling wine (not quite kid friendly.. :D)
I was playing around with statistics from UNESCO to see if there were any trends in education spending over the past few years. Here’s a box plot showing the average international % of GDP spent on education in the last 14 or so years. The 2013 data seemed a bit sparse, so it might be wise to ignore it. Seems like there is a trend of decreasing spending in the past 4 years, but not a huge change over the past 10 years. Enjoy!
I’ve been playing Cafeteria Nipponica on my phone recently, and found myself regularly checking Happy Enna’s Recipe Reference to work out how to do the things I “remember” from last playthrough in the best order. The information there is invaluable but spreadsheets hurt my eyes. So, I created these flow charts!
All dishes come from a “root” dish, you can find out how to get them here.
Colors indicate the max * ranking, keys on each image. I wonder why rice and soba are so lame?
I was recently invited to give a talk on “AI in games” to Jyväskylä’s AMK game programming students. The lecture could have gone better if I had prepared more material for it, but the catch was that I didn’t know what to prepare. These notes act as a guide for “next time”. I won’t go into any depth on the subjects here.
Briefly introduce scientific AI, point out useful libraries [A*, speech recognition, opencv] then waft it away
Focus on architecture of players, representation of game state and move logic
Establish the simplest AI player for tic-tac-toe, then develop it to a perfect player [“smart as possible AI”]
Make the tic tac toe player more fun to play against
Consider expanding it to more complex games (chess, civilization) and optimizations
Human behavior simulation – know the limits of senses, program them in. FPS/Stealth AI is a good example. [“dumb as a human AI”]
Planning and decision making architecture
Techniques for more realistic behavior
Examples of AI in video games: planner in fear, neural networks aren’t used much in industry (notable exception, Supreme Commander 2) and only for decisions, Quake 3 doesn’t have neural net bots