Regarding Google’s advice to learning app designers

There is a growing public perception that “most educational apps stink” in today’s App Store, in part because they are ineffective.  That’s partly why I’m so happy to see Google promoting quality apps in their new App Store for Educators:

“Apps submitted to Google Play for Education will be evaluated by a third-party educator network, which will review them based on alignment with Common Core Standards and other factors.”  In the demo video, it is revealed that CUE is the 3rd party doing the reviewing.

I’m also very happy to see Google offering design advice to educational app designer/developers.  In this article I suggest ways Google could improve that advice.

In this first section, I argue that Google should require app developers to prove their app is effective.  I then review Google’s advice more broadly.

If I could make only one change…

If I could make only one change to this list, I would add this:

  • Prove your app is effective.

For example developers should be required to say, “Students who played the game [Motion Math] for 20 minutes for five days improved on a fractions test by an average of 15%.”  (link).  Pearson offers a free, generic framework (link) and many other similar resources exist.

I’m not talking about screening low quality apps.  I’m talking about screening apps that don’t measure anything at all.

Google told learning app designers (here, my bold):

Apps with highest educational value will have these characteristics:

  • Designed for use in K-12 classrooms.
  • Aligned with a common core standard or support common-core learning.
  • Simple, easy to use, and intuitive for the grade levels the app is targeting. App is relatively easy to navigate without teacher guidance. Not distracting or overwhelming to students.
  • Enjoyable and interactive. App is engaging to students and lets them control their experience.
  • Versatile. App has features make the it useful for more than one classroom function or lesson throughout the school year.
  • Supports the “4Cs”:
  1. Creativity — Allows students to create in order to express understanding of the learning objectives, and try new approaches, innovation and invention to get things done.
  2. Critical thinking — Allows students to look at problems in a new way, linking learning across subjects and disciplines.
  3. Collaboration — Allows students and (if appropriate) educators to work together to reach a goal.
  4. Communication — Allows students to comprehend, critique and share thoughts, questions, ideas and solutions.

Edutainment, initially hailed as a educational revolution, failed to disrupt classroom practice. One of the many reasons, argued MIT researchers, was the products’ frequent lack of efficacy (link). Google could help the latest generation of developers avoid repeating this clear and well-understood mistake in the field.

Bad learning apps can actually hurt learning. Some popular learning products are widely believed to be ineffective (such as toddler DVDs), but it is less commonly known that bad learning apps can do harm, not just fail to do good.   “Zimmerman, Christakis, and Meltzoff (2007) empirically demonstrated that for each hour children, ages 8 to 16 months, were exposed to commercially available audiovisual programs (e.g., Baby Einstein and Brainy Baby), the children developed 6 to 8 fewer receptive vocabulary words (i.e., words they understand) than their counterparts who were not exposed to such stimuli.” (Christakis 2009).  Google should prevent ineffective products from being confused with unknown or proven good educational products.  Requiring any sort of efficacy evidence would be a simple way to screen many of these products.

Obviously not all 1-person app developers can afford to do a “proper” randomized controlled trial, but I believe anyone can do a simple pre-post efficacy test. Some learning goals are less obviously testable. How does one evaluate efficacy of “systems thinking”?  It can be done, if only by using very qualitative, unstructured interviews.

I wish Google should require all apps in the education store to

  1. make a clear, specific claim of efficacy,
  2. provide evidence of that claim, and
  3. have that evidence validated or reviewed by a 3rd party

Google’s CUE approval system is a good first step toward the 3rd point, but I hope for more: I want a scale rating,  not just approved/not approved, so proven apps are first on the list, and the reasons are clear.

A Broader Critique

Next, I want to talk more broadly about Google’s design advice: Is this list good advice? 

Advice is cheap to make, but VERY EXPENSIVE to follow. Every point on Google’s list adds huge cost and risk to the app developer.

Specifically, I ask:

  • How should developers decide which, if any, of these to follow?
  • Should other stakeholders, say publishers, criticize an app, using this advice?
  • How?

There is difference between a wishlist and useful design advice. For example, consider this design advice: A quality car should include as many of these features as possible:

  • seats 12
  • 100 mpg
  • 0-100-0 in 4 seconds
  • Less than $10,000
  • Made from environmentally friendly materials
  • Looks awesomer than a Lambourghini
  • Parks in half a parking space

I hope we can agree that this list is near-impossible for commercial, practicing car designers to adhere to, and that it unlikely to be useful to audience.  Compare that silly list to Google’s list, and note what the two lists have in common, as you read the following questions.

  • Where did this advice come from? Who wrote this? What are their qualifications?
  • Is the source ‘data’ trustworthy?  Is this a wishlist of a naive enthusiast?  Is it based on lessons learned from a single case study? Is it a broad summary of the academic literature, written in an ivory tower?
  • Does this advice apply equally across the entire diverse landscape of the field?  Should learning game apps that practice, be more collaborative than instructional apps?
  • Does this advice fit with other expert design advice?  See below for examples. Are there conflicts or commonalities between this advice and existing, prevailing views of experienced designer/researchers?  What reasons are given for this variance?
  • Is this advice realistic? Is it even possible to build an app that fits all, or even most, of this advice?
  • What are some examples of apps that follow this advice?  Discuss merits and weaknesses of exemplary designs.
  • Could and should this advice be used by stakeholders, other than developers, to assess or critique?
  • Is there any evidence or reason to believe this advice will yield improved learning apps?  Are there cautions on any dangerous combinations?

I hope the reader can, by comparing to the silly list of car design, see why and how Google’s advice might be improved upon.

How useful is broad advice, to 1-person app developers?

What use is design advice for a “car”?  Minivans, supercars, and econoboxes all have very different use cases.  There is precious little design advice that applies to all.

A naive advisor might argue that these traits are all desirable. What’s the problem with advising designers to aim for such traits?  THe problem comes in assuming all learning apps are essentially similar.

Consider how a supercar designer who is told: cars should be affordable. Should they try to make a $10,000 supercar?  Of course not. It would not be possible to meet the key requirements of a supercar (performance, style, etc) in a $10,000 cost ceiling   Why not try to make minivans take half a parking space?  Again, the value of the minivan is its hauling capacity.  A tiny minivan is not a minivan anymore. It’s a different type of car.

Good learning apps are not essentially similar.  Teaching the concepts of algebra has little in common with reviewing cultural norms in 17th century Africa.    Proponents of gamification, applied to cars, suggest we can reuse mechanics for a variety of purposes.  That’s like saying we can all adapted a Ford Taurus to our needs: Farmers can add a roof rack, instead of buying a pickup truck, for hauling brush.  Racers can put chrome rims on and bingo, teen revheads have a cool car.

How many e-learning apps are basicly flash cards?  show material, multiple choice. Such elearning designs can be effective but designers should work hard to improve on that weak interaction. Such designs are not the best we can do with the power of Android apps.  I believe Google offered this advice intending designers to aim higher, as Devlin explains well here.

So, how what should the advice be?  Following the car metaphor, supercar designers should be discussing specifics: the merits of carbon fiber in interior detail, for example.

However, there is need for basic advice aimed at one-person learning app designers who didn’t necessarily study e-learning design principles in school. Such designers are perhaps akin to kit-car builders:

  • They need a few basic ideas (more rubber on the road means more traction, but higher friction). I think this was Google’s intent with this list, and I give some of my favorite examples of such advice at the end of this post.
  • They need many specific tips (e.g. slant your kingpins to make the car steer straight). this is tough to deliver on paper – it needs to be “just in time” and very simple, and pushed to designers as they work.
  • They don’t need broad goals (make your car use less gas). I think Google accidentally delivered much of this type of advice.

There are some general points, such as those made by

Much design advice should be specific to the intended learning goal, age, and nature of outcome (practice, etc).  Learning designers ask:

Should we repeat material?  Is it worth building a proper simulation, or just semi-faking it with a simple 1-variable interactive element?   Where does learning really occur in apps?  How can we collaborate yet avoid the blind leading the blind of the cliff?  There are some clues and a few outright answers in the literature (it’s not very accessable and easy to find, but that’s a separate rant).  That’s the design advice we need.

The end.

PS Further Reading

Finding good advice ain’t easy.  I’ll give three personal favorites, for classroom learning game design.

  1. MIT’s “Moving Learning Games Forward” paper here,
  2. Gee’s numerous excellent principles here (summarized by Draper here).
  3. For math learning games specifically, Devlin’s blog here.

These three examples are specific to learning games, part of the vast literature on e-learning (a random example of which is here).

<whap> Thank you sir. May I have another?

I am considering writing a review where I compare, point by point, Google’s advice to prevailing views from Gee, Osterweil, specifically for learning game designers. (if that’s something you’d be interested to see, let me know).

New Job Title: Researcher/Designer, Northwest Media

I’m happy to report that I’m at Northwest Media designing interventions for social good based on learning games, We’ve got a number of projects on the go:

  • VSG, a Sims-RPG hybrid game designed to help at-risk kids, especially foster teens, realize the need to develop life skills before jumping into the real world.  It’s a NIH-funded SBIR Phase II, and we’ve got most of a year left to finish.
  • InTouch, a serious game that aims to help foster and birth parents develop a form of mentalization called “Parental Reflective Functioning”.

It’s exciting stuff that combines innovation, simple execution of what is known, and all for social good.  Nice!


Doctoral Dissertation – shipped!

I am so happy to report that I have submitted my doctoral dissertation, back in December.

Here’s the abstract.

This research aims to improve the practice of designing educational video games (“learning games”). This thesis aims to both validate and extend Shelton’s theory of activity-goal alignment, which focuses on the relationship between a player’s activity and the designer’s intended learning goal in any learning game. The thesis develops and evaluates two novel tools. First, an autoethnographic account of a recent learning game project confirms Shelton’s prior findings that activity-goal alignment theory meets an important need in learning game design practice and that Shelton’s theory might be made more accessible to practising designers. The AGA Scoring Tool is developed, and both it and Shelton’s theory are evaluated through analytic discussions of designs of several existing learning games: activity-goal alignment theory is found useful, and scoring activity-goal alignment is argued to be clearer than Shelton’s narrative-based approach. Secondly, this thesis argues that there is need for improved tools for assessment of learning games. A critical review of existing assessment tools yields a list of criteria for any learning game assessment tool.  A basis for a new learning game assessment tool is developed from three theories: Higher Order Learning theory, Gee’s principles of Deep Learning, and Shelton’s activity-goal alignment. These three theories are argued to comprise an important, prevailing position within the learning game design literature. A new tool, the AGA-Based Assessment Tool, is proposed and exercised in critical discussions of several learning games. Important gaps between learning game design practice and theory are revealed using the tool.  The thesis concludes that scoring activity-goal alignment is useful to the learning game designer because it makes an important theoretical position from the learning game design literature clear and simpler to apply in practice.

So good to have this sent!  It’s being examined now, and I’ve been trying not to think about it for that last seven months.  I’ve already had one paper adapted from the autoethnographic chapter, accepted at the Games for Health Europe conference #GFHEU in October, so that’s a good feeling!

LegitMe Pitch

Do YOU want to disrupt the world of e-retail? Are you unafraid of Amazon, Apple, Hollywood, and every other powerful IP holder in the world?  OK!  here’s the plan:

NEED 1: CONVENIENCE. I, the LegitMe customer, used to be a pirate but as I get older and richer, I use torrents not to save money but time, and to get a better product. Software is quicker and easier to install via torrent, and DRM-free media is handy and quick, compared to regionlocks and other silliness of legit media. What I want is a way to legalize everything I’ve illegally downloaded on my pc, quick and simple.

SOLUTION:  LegitMe is a client and ASP, endorsed by an organization I totally trust, and that I install voluntarily.  When I run the client, it crawls all storage on all my personal devices, identifies illegally downloaded media (torrents, mainly). Once a year or so, it would invite me to buy all my downloads: “This computer, and WifePc, and Kidspc, together have 258 songs, 32 movies, and 6 apps that aren’t legal. To buy these all for $379, click here. To buy and/or delete certain ones, click here.”  I pay $379 to LegitMe’s paypal account, and I’m done (actually, not quite done – more on this later).

Once I’ve OKed it, the client send parts of that list to thousands of other clients using P2P.  After the data is sufficiently anonymized, the clients upload the list (no personally identifying information) to LegitMe’s servers.   The servers tally how many copies of each media are there, and contacts the rightful owner.   e.g. “Dear MGM: 6271 torrent owners have illegally downloaded “Full Metal Jacket” and have asked us to buy it for them under these terms [link]. Based sales history of similar titles (viewable here), and with an amnesty discount, we believe a fair price is $32,800 ($5.23 per copy).  To agree, click here to receive imeediate, cash payment.  If you do not accept this price or terms, feel free to counteroffer by contacting”


LegitMe doesn’t know and doesn’t promise the user is obeying the terms of the IP deal.  There is no “ownership receipt”.  Angry IP owners can subpoena LegitMe’s servers, but there’s nothing on them that would help identify users. It would be more useful to get torrent download sites, which at least have IP addresses associated with the torrent download.

LegitMe allows the users to set the terms, and forces IP Owners to negotiate on stupid ideas like Region Lock. It’s based on trust.  LegitMe allows honest users to “come clean,” out of the goodness of their hearts.  In their hearts, most people do want to be good.  They want to see indie artists rewarded.  Most even want James Cameron to get $10M to make Avatar 2.  LegitMe allows them to be good without being punished.  Two examples:
1) I’ll pay something for Windows XP, but not $100, and I’m not driving to Best Buy to get it!
2) Collectively negotiating terms could open exciting new business opportunities to indies (“Dear AngryTanks developer: 253 users are collectively offering you $32,393 to open source your entire game”) but would be more often used to counteroffer untenable terms in major IP Owners’ licensing agreements (“Dear MGM: Owners have authorized LegitMe to pay $0.37 more for each of your DVDs if they are not region-locked.”).

RISKS:  I can think of only three teensy little risks….

RISK 1. IP owners like Sony Music are known to be vicious,greedy sharks. Would they really negotiate with known pirates?

A.  They will have no choice.  A key hire for LegitMe would be a really excellent IP licensing negotiator.  At first LegitMe would only be able reach agreement with progressive, openminded IP owners (e.g. O’  It would not even try to negotiate with larger entities; it would simply hold the money (with users’ permission) in escrow for a future date, while it continued to bring on more and more IP owners.  The money would be stacking up, over the years. If/when the escrow reached millions, LegitMe would fund a campaign to pressure the big boys, working on them via stockholders (they are legally obliged to make a profit), competitive pressure (progressive publishers would have a “pure profit” revenue stream), and political (good old campaign finance, seeking a “obligation to offer fair alternative” law).

If LegitMe works, eventually I (the user) might trust LegitMe enough to not go anonymous.  At that point, I can track my IP ownership across multiple devices, download higher quality versions of the content from IP owners, build a genuine relationship of trust with the IP owner directly.

In the eyes of the IP owners, LegitMe would work like a bricks-and-mortar retailer: buying IP in bulk, competing with Apple and Amazon.

2. Would enough users really trust this product not to rat them out?
This is the biggest risk, at this point. Certainly a few people will do it, but also certainly some people would never do it.  A realistic estimation of the market size would require some research.  Partnership or endorsement by a completely trustworthy entity would help.  The EFF springs to mind. Suggestions?

3 Is it possible for code to determine which media you had purchased, as opposed to legally downloaded or ripped content?
LegitMe would allow users to tag IP they bought legally (e.g. DVDs they ripped themselves), versus downloading.  LegitMe would see a very large (90% say) discount for media I bought and ripped, provided I share them only among devices I own.


Obviously it won’t be easy.   And also obviously, there’s a LOT of money in it, if it works. To me that’s a risk, not a goal.  Anything worth $100m gets greedy sharks circling.  We are not sharks.  We are wizards, changing the world with the power of pure ideas.  We must protect this from sharks – hence “social enterprise.”  This idea can rebalance the scales of IP ownership by letting normal people get rewarded for being honest.

To the investor, LegitMe is a disruptive new business model for e-retail that will beat Apple and Amazon three ways:

1) cost of doing business is massively lower – no ads, retail website, etc.
2) licensing terms are set by purchasers, not owners.
3) negotion leverage: IP owners can cut off Apple and Amazon if they wish.  They can’t do that with LegitMe.

Critiques? Suggestions?  I honestly don’t see how this can’t work.  Fire away!

interesting thesis on Facebook and privacy

Game designer Kate Raynes-Goldie just wrote an interesting doctoral thesis that examines Facebook and privacy. Her abstract says:


Most academic and journalistic discussions of privacy on Facebook have centred on users, rather than the company behind the site. The result is an overwhelming focus on the perceived shortcomings of users with respect to irresponsible privacy behaviours, rather than an examination of the potential role that Facebook Inc. may have in encouraging such behaviours. Aiming to counterbalance this common technologically deterministic perspective, this thesis deploys a multi-layered ethnographic approach in service of a deep and nuanced analysis of privacy on Facebook. This approach not only looks at both the users and creators of Facebook, it examines Facebook Inc. in the context of historical, cultural and discursive perspectives. Specifically, this thesis details how the company’s privacy policy and design decisions are guided not simply by profit, but by a belief system which which encourages “radical transparency” (Kirkpatrick, 2010) and is at odds with conventional understandings of privacy. In turn, drawing on Fiske’s model of popular culture, users “make do” with the limited privacy choices afforded them by the site, while at the same time attempting to maximise its social utility. As this dynamic demonstrates, Facebook Inc. plays a critical, yet often overlooked role in shaping privacy norms and behaviours through site policies and architecture. Taken together, the layers of this thesis provide greater insight into user behaviour with respect to privacy, and, more broadly, demonstrate the importance of including critical analyses of social media companies in examinations of privacy culture.

Stuff which might be useful for Facebook, social media & privacy researchers

  • In Chapters 3 and 8, I expand on my definition and application of social privacy as distinct from institutional privacy (which I first wrote about in in 2010) — that is, the management of information and disclosure about oneself in the context of one’s friends, acquaintances, co-workers — as an important concept in understanding privacy behaviours and attitudes on Facebook.
  • In Chapters 5, 6 and 7, I provide the origins, manifestations and consequences of the philosophy of Facebook — or what I call “radically transparent sociality,” which essentially explain why Facebook doesn’t want to protect the privacy of its users.
  • Chapter 4 provides a comprehensive chronological overview of Facebook’s history and evolution from 2004 until 2011.
  • Throughout the thesis, particularly in Chapter 8, I show how the idea that youth are privacy unconcerned (sometimes described as the “privacy paradox“) is an oversimplification, and is largely inaccurate.


The full text is here.

The three ways technology reaches end users

In this discussion, I suggest that all modern technological breakthroughs that affect normal people might be understood as belonging to one of three models:

First, I acknowledge the ‘normal’ model: publicly funded research yields technological breakthroughs, which are developed into mass-market tools. The selling of the tool generates profit.  The user applies the tools to generate value for himself, not the entity.

Typewriters –> IBM, Selectric
Mobile phones –> Motorola, Sprint
Smartphones –> Apple, Google, Samsung
eBooks –> Amazon
Video games –> EA, Sony, Valve

Second, the ‘fishhook’ model does not generate most of its value from selling the tool.  These entities develop a technology into a ‘fishhook:’ the tool is free, because the entity extracts value from users’ activity: the use of the tool, not the tool, generates the value.  Any free or advertising-supported tool is using the ‘fishhook’ model.

TV –> NBC, Foxtel, Comcast
Ad-supported Kindle –> Amazon
Video –> Youtube
Collaborative Planning –> Google Calendar, etc
Social science –> Facebook, LinkedIn, etc.

The third way are what I call ‘happy accidents’. For example, the personal computer, email, WWW, and torrents were all unharnessed breakthroughs. I argue these were accidents, not the plan, of the large entities that funded their research.  Apple largely failed to exploit the PC revolution with the Apple II. It did not make that mistake the second time with the iPhone.  Many entities today aim to intentionally induce these “accidents”. Free IP, indie media, maker movement, and open-source culture are examples.

I developed this idea during a discussion of consumer media literacy.  If I publish that, I’ll edit this line with a link to it.

I’m looking forward to your reasoned response.

an letter to kids who want to mod minecraft

A smart gamer kid recently emailed me:

> i forgot to say in my last email that it would be epic if you could show me how to make a mod for minecraft!!!

Here’s a public reply, for that kid and all the world of kids like him.


Are you a kid who wants to learn how to mod minecraft?

First: IF YOU CAN MOD GAMES, YOU ARE SERIOUSLY AMAZING!   Modding teaches you really important skills: how to program, create art, and work with the biggest, baddest kind of program ever: video games are hardcore.   So, it’s fun to make them, but it could be more than just fun. It could be a big deal if you take it seriously and stick with it.

The bad news is: it’s not easy!  Minecraft wasn’t designed for modding, so the code is confusing and complicated.  I love Minecraft too, but I would NOT suggest learning to mod on it.  Mod some other games first!  I know some way easier games to mod. Here’s 3:

  • If you can build lego, you can mod games with By playing this game, you’ll learn to mod, and build your own, simple games – WITHOUT having to learn anything hard at all!  You just drag and drop little guys and blocks and click “play”.  SUPER easy.  What you learn here will help you mod harder games.
  • Once you’ve beaten GameStar Mechanic, you will probably want more controls than just a gravity slider and whatever.  You need a “game engine”.  Here’s two: Construct ( and GameMaker ( No coding needed, and you can build some seriously fun games, or just mod the ones it comes with.  (but to build more complex games in GameMaker, you can also write code.
  • If you want 3D games, one really powerful game engine with lots of good tutorials is Unity ( You can build most kinds of games with Unity.

…but I bet some of you will ignore that list because YOU just want to mod MINECRAFT.  I would have said that when I was 12.  OK, OK!

The tutorial below assumes you know how to program (I call programming “coding”).   So, to learn to code enough to mod Minecraft, do this tutorial:   It’s free, fun and easy – no installs or downloads – just watch the videos and code right in the browser.   There’s another site called which is also great.

OK, so you know how to code a bit.  Here’s how to mod minecraft.

1. install something called MCP (instructions here).

2. do this tutorial. It’s step 4 of a longer tutorial. I skip steps 1-3 because they mainly teach some advanced coding ideas, which are confusing for beginners. In step 4, you make a new kind of dirt block, and see how Minecraft really works.

3. Keep going. There’s lots more tutorials here.  Or, you can continue with the “lightdirt” tutorial:

Don’t give up.  Search around for other mod tutorials if you don’t like this one.  Try youtube “mod minecraft tutorial”

Take your time.  If you can do this tutorial, even if you don’t understand it all, you are seriously amazing.  This is like a full university!

You can do this, as long as you don’t give up.  I learned how to program on my own when I was 12 because i was SO KEEN to mod my favorite game, I NEVER gave up. Even when it was frustrating, I just WANTED to mod SO BADLY – I just kept struggling till one day, it worked! I was awesome.

If you get frustrated with modding Minecraft, don’t feel bad!  Modding can be quick, simple, and really fun (not modding Minecraft! it’s hard, complex, and really fun 🙂 ).  Try GameStar Mechanic.  Try Construct.  WAY easier.

When I was 12, I started with WAY easier games than Minecraft.  I probably would have been too frustrated with Minecraft to finish.  My first games were more like Pac-man.  I did really dumb mods of games (and I didn’t try hard games like Minecraft! I started with easy ones first).  Then I did cooler games.  From there, no one could stop me – and now I get paid to design games – awesome!

Also.  There’s two kinds of mods:  art mods, and real mods.  Art mods (skins, levels) is fun, because you can just click around or paint in Photoshop, but for a game like Minecraft, art mods can’t change how the game WORKS.  If you want to really control the game, you’ll need to code.

I would be so impressed if you learned to program properly.  Programming is the real thing.  If you can write a game, you can write code that controls everything – robots, cars, airplanes, figher jets. You can earn good money.  If you want to really control the world, learn to program.  And, it’s really fun!


paper+sound prototyping

The next time I have a ‘from-scratch’ game project, maybe I’ll try paper prototyping with sound effects to indicate emotionally meaningful gameplay events (inspired by Schell’s ‘ding’ effect during his Gamepocolypse talk).  I picture doing it live, in person: talking through a gameplay session by flipping and pointing at mockup sketches on paper and touching a soundboard on an iPad.

tiny rewards: operant conditioning in video game culture

This post is about conditioned response, triggered by an unrelated video game design discussion (about using sound effects as triggers for data collection for analytics because “[…] all the semantically important moments in a video game have unique sound effects (or patterns of sound effects)” – Marc LeBlanc Facebook post July 16 2012).  One responder I won’t identify replied “I think it says gamers salivate when a bell is rung.”

When games, and their designers, are accused of manipulating players, akin to deceit, Pavlov’s famous salivating dogs are often cited.  I think this isn’t a fair summary of operant conditioning in games. This made me want to explore my own understanding of conditioned response, and how game designers use it.  Hence this post.

A more powerful example is in Jesse Schell’s Gamepocolypse talk, he gives many horrific examples of blatant manipulation of gamer behavior using a “bling!” sound effect for each. A s I watched, I said “no!” but felt “cool!” The sound effect told me I should feel satisfaction of getting points. That “bling!” sound was spending my conditioning capital, earned through game play.  At the end of the lecture, even after some reflection, I felt confused at an intuitive level. Is the Gamepocolypse good or bad? It’s bad, but it’s fun!    It’s good to reward toothbrushing!  It’s horrible if game designers place products in my dreams!  This confused, complex feeling is correct: operant conditioning is not simple. the drooling dogs of Pavlov are not the whole story.

I want to start at the research.  In achieving the conditioned response, Pavlov first identified an inherently rewarding activity (dogs eating).  He then connected the ringing bell to that event.  The final salivating-for-bell behaviour was “borrowing” from the inherently rewarding activity of eating. If he had fed the dogs dirt, would they learn to salivate with the bell alone?  I think not, because there was no inherently rewarding activity.

BF Skinner’s Law of Effect says “behavior which is reinforced tends to be repeated (i.e. strengthened); behavior which is not reinforced tends to die out-or be extinguished (i.e. weakened)” (source).

To measure this I use the metaphor of ‘conditioning capital’:  designers earn ‘conditioning capital’ by providing inherently rewarding activity.  This ‘conditioning capital’ can be spent for various purposes.

For example, when a designer places a “ka-ching” sound effect, they are either predicting the player feels game mastery at that moment (which earns conditioning capital), or rewarding player for doing what the designer wants (spending capital).

In my play experience, games often build conditioning capital with rewards. For example, when I earn a powerup, the game plays a “bling” sound. This is a tiny reward.  It feels like the game is recognizing, externalizing, and acknowledging my tiny mastery of navigation.

Collecting a powerup is inherently rewarding: it improves my options for gameplay.  The “bling” sound is extra. It’s not just audio feedback. “Bling!” is a happy sound in my culture. I enjoy hearing it on its own. It’s a tiny reward. It is also being reinforced. I get something good, I hear “bling”, thus “bling” means good.  The game is building a conditioned response.

If you doubt that effect sounds are more than pure feedback, do this thought experiment: Play a generic 2D platformer in your mind, replacing the powerup sound swith a culturally meaningless ‘tick’ sound.  Would it be just as satisfying as Super Mario’s sounds?  Is it clear how important positive sounds are for effects, and how much conditioned capital is on tap through these sounds?

Of course, designers can use operant conditioning to manipulate the player.  Jon Blow criticizes this (Blow 2011) and asks designers: ““Are you trying to take advantage of your players and exploit them? Or are you trying to give them something?”As a designer, I give these tiny rewards for many reasons.

* guide the player towards designer-desired gameplay (e.g. collect coins)

* to amplify and validate the internal reward (yes, player, that was good!).

Perhaps one could define “bad” game design as spending more behaviorial ‘capital’ than it generates.  For example, if a math-memorization game uses “Boss Killer” achievements and players’ pleasure is primarily a conditioned response accumulated from past experience of killing bosses, then that capital will run out.  It may take a while – a lifetime of gaming has built a lot of capital around certain reward signals – and but it could be a clear basis for judgement of game design.

This ‘conditioned capital’ is so large for certain video game sounds that popular media mocks our helpless responses, even while using it effectively. In the animation “Scott Pilgrim vs” (youtube), at 2:52 Scott hits the boss, earning a “KO” victory sound effect. At 3:13 Scott kisses a girl and gets a “Powerup” sound effect.  It’s not just sound effects. There are many visual effects with cultural capital. In the Scott Pilgrim comic book series, Scott gets a “level up” graphic when he achieves anything major.

I view the conditioning capital around these iconic sounds as a shared resource: a Commons, in the Tragedy of the Commons sense.  Low quality gamification can be seen as a pure “capital spend” of video game reward conditioning. For an extreme example, consider low-quality ‘gamification’ of a classroom: convert grades to “points” and assignments to “quests”, with no other changes.  It is a ‘pure spend’ – it is borrowing the ‘cool’ that kids associate with games – and obviously manipulative.  BK Skinner’s theory suggests it will quickly become less effective, unless there are some genuinely new experiences behind it.

Of course, operant condition isn’t the whole story of player motivation – far from it. Player motivation is complex and multivariant, and behaviorism is only one small part of the picture. For example, in-game achievements are sought for social status signaling reasons (Medler 2011, “Validating Motives” section). These powerful motivations could well trump any motivation from intrinsic reward or conditioned response.  But operant conditioning is a important topic in any reflective game designer’s mind.

To summarize, I believe games designers should build ‘conditioning capital’ by providing players with inherently rewarding experiences, and be aware when they are spending it.


the game should be the task, not the reward.

I’ve been trying to put my finger on what’s so wrong with poor old Math Blaster’s oft-maligned core mechanic (solve an arithmetic problem to progress the game).

Learning game researchers often critique this type of design, using arguments common from anti-gamification (my favorite is “chocolate covered broccoli”). But like gamification advocates, defenders ask: What’s wrong with that? It works, adding motivation to rote learning. While some question the value of extrinsic motivation, let alone rote learning (see wolfram’s TED talk), it does work.  No, there is something else. Something more frustrating.

Nintendo’s Help Cat (see Danc’s insanely detailed critique) runs away from the cursor, making it harder, not easier, to get hints . Since users assume winning yields valuable information, Help Cat winners are predisposed to value the factual knowledge delivered (hints about using the hardware).

After noting how Help Cat exposed hidden assumptions in UX and instructional design, Help Cat implies a question of learning games:

Is game play activity the reward, or the task?

Math Blaster’s design implies that game activity is simple, easy entertainment — a reward for real work of calculation. The “fun” in games is “simple, easy entertainment.”  But games are a form of play, and it may seem strange to say, but video game play is rarely simple or easy. In fact, it has a lot more in common with the frustrations and satisfactions of learning than “simple, easy entertainment”, as James Paul Gee convincinly explains in some detail.

Maybe playful design can help learning game designers disrupt the fallacious tension between fun and learning.  This line of thinking is leading back to one of my favorite design principles: “Find the Fun in the Learning.”  (“Moving Learning Games Forward”, MIT education arcade).