We often do not get voluntary participants. People are forced to come to programs and consequently, it undermines the implementation of other game mechanics. How do we overcome the challenge of voluntary participation?

My response:

• First, there’s an assumption that participants DON’T want to go to training — I think they do. I think their work gets in the way. If they had their druthers, they would volunteer to come, but the system they are a part of (aka, their work environment), prevents/hinders/discourages them from doing so. If it’s choice between learning and utilization, utilization wins (particular to professional services.) Examine the SYSTEM they are a part of.
• Motivation comes from goals. Perhaps if were to get clear on the learner’s goals, we could more clearly map to motivation. If they don’t know their goals, their motivations will be fuzzy, IMHO. If their goal is to figure out their goals, then even that helps.
• The tension in most learning, as was noted in Joe’s post, is that is about the “message” that the organization wants their employees to learn/regurgitate/live. So absolutely, there are training situations where there is a need for compliance and people are forced to go. We look for ways to make those trainings more palatable (like gamification) rather than stating quite clearly, in this GAME of WORK, here are the rules. This is what you must know to survive and thrive. If your goal is to keep your job, guess what, you gotta play by these rules.
• The medium in which this message is given (yes I’m channeling McLuhan, he is Canadian after all) usually kills the motivation (yes, I’m thinking death by powerpoint)
• The challenge is the capture the energy in a forced training situation. Where is the energy? In onboarding (new hires or acquisitions), the energy has to do with anxiety of joining a new organization. The motivation is to understand the lay of the land – expectations, tools, etc. How does one channel the energy into something positive — either connections with each other, with their new organization, or voicing/airing concerns in a safe way. This is not new.

I think with gamification and voluntary participation we are perhaps asking the wrong question. It’s not just about the individual but the system they are a part of. Use gamification, but use it in a way that makes the experience more authentic — bring in randomess and the gaming aesthetic it creates rather than a point system. Allow rules that channel and focus the energy in the room — rules that open up the experience rather than shut it down by someone “telling” you what to do. Create teams that support collaboration rather than competition.

Gamification can be useful with the right framing.

Two things happened that piqued my interest: a friend shared a TEDx talk by Seth Priebatsch: the game layer on top of the world; and I talked to another friend about the difficulty of selling anything called a “game” into corporations. As many others have concluded, you have to change the name of the game. Call it anything but a game. Which begs the question — what do we call games?

What are games?

What are games? What are some of their characteristics? Learners are actively engaged in a simulation/fantasy or solving a problem, where they will fail multiple times in order to succeed. The game is filled with feedback mechanisms. It’s about getting the points, not so much having the points (for most people anyways). It’s about status in the game, and often about playing amongst a community of gamers, whether that be in a multi-player game or in a single player game where you compete with your friends.

Sounds kind of like….

Discovery learning

What is discovery learning? Here’s a quick introduction.

• Basedon theories of  Dewey, Piaget, and Vygotsky.
  • Dewey – primary premise was learning by doing, learning is experiential and social; experiential was often defined as “using your hands” — building a house, taking apart a radio, with a group of peers.
  • Piaget – showed that a child is not an empty vessel, but is an active participant in learning about the world; assimilation and accommodation are means of adjusting the understanding of the world. Created the idea that children learn differently from adults and go through “stages of development” — not all of his theories have stood the test of research.
  • Vygotsky – best known for Zone of Proximal Development (ZPD) and the bringing out the social and cultural influences on cognitive development. ZPD is the zone between what an individual can learn on their own versus what they can learn with guidance or social interaction. In a sense, it is the optimal learning zone. Related ideas include scaffolding and situated learning.
• Architectures for discovery learning
  • case-based learning
  • incidental learning – results incidentally from an interaction, such as a crossword puzzle.
  • learning by exploring/conversing – asking questions to solve a mystery, discover an object
  • learning by reflection – a teacher never gives a direct answer, but instead answers questions with questions, forcing the students to reflect.
  • simulation-based learning
• How discovery learning is different
  • active rather than passive
  • process-orientated rather than content-oriented
  • failure is important
  • opportunity for feedback in learning process

Sound familiar?

Games as discovery learning

So let’s call games what they are — guided discovery learning. Games are guided by the rules of the game, where you get feedback on how you perform, instantaneously.

Change the name of the game to “guided discovery learning.”

Hmmmm…. I think I can sell that.

But what about…

The fear with guided discovery learning (aka games) is that you will not cover the course content and it will take to long or will be too expensive to create. I’ve been struggling with these questions — how do I design a game so people learn the ‘right content’? Well, it’s about the process, not the content, so that’s the wrong question. I’m not selling a learning PRODUCT, I’m selling a learning SERVICE. Games are a type of learning service. That means coming up with a business model that works in the service economy. OK, some more thinking to do here.

We don’t need to learn how to play games — games are already a part of our world. (Seriously go listen to Seth’s TEDx talk.) The problem is that they are just not fun yet. The bigger problem is that we just haven’t figured out a business model for adult learning games that works yet. How do we create and sell guided discovery learning that’s relevant and cost-effective?

Castronova, J. (2002). “Discovery Learning for the 21st Century: What is it and How Does it Compare to Traditional Learning in Effectiveness in the 21st Century?” Action Research Exchange 1 (1)

Bicknell-Holmes and Hoffman (2000) Engage, Elicit, Experience, Explore: Applying Discovery learning to Library Instruction – LOEX. Presentation.

Social Development Theory: Vygotsky. TIPS website – http://tip.psychology.org/vygotsky.html

Predication and plans for 2010

In response to the ASTD big question this month – I offer the following

Predictions:

• Design thinking will be the buzz word for 2010. To be honest, I’m still figuring out what it means for learning. I think this all started with Tom Kelly’s IDEO: Art of Innovation book back in 2005 (see my review of this book) and continues with Tim Brown’s Change by Design. On IDEO’s blog, design thinking is described by 3 ideas: Inspiration, Iteration and Change
• Analytics will rule. I think the learning profession, especially online learning folks, will have to collect more specific data on how people are using the learning, finding patterns in the data to describe different “types” of learners. Again, still figuring this one out. (See post on analytics book review.)

Challenges:

• Finding new metaphors for learning. The metaphors of the book, and of the the classroom/course still dominate learning. What are the new metaphors? How do we move beyond these old metaphors? I think the big tool sets out there (Captivate, Articulate) push us towards these metaphors. Will there be new tools that move us in a different direction?
• Aging workforce. We’ve heard much about Gen Y. However, I think we are also dealing with an aging workforce. I need to research more stats.

Plans:

• Get work, get paid. Let there be work! Looking forward to being more fully employed in 2010, whether that be employment or more contracts: 2009 was not the best year to graduate :-}
• Design more games. Been focussed so much on the employment thing, forgot to do the thing I really wanted to explore.
• Learn more about:
  • Design thinking
  • Analytics
    
  • Metaphors for learning
  • Workforce statistics
  • Tools that break the mold(s)

Hmmm… I see many blog posts coming out of this. Happy 2010 everyone – may it be filled with blue skies and new possibilities!

I’ve recently decided to deepen my understanding of analytics, in part to think about my website and how to better promote it, and secondarily to better understand this new way of thinking about business decisions. So I thought I’d start with this book and a broad introduction to this field.

The Deciding Factor is just that — a broad introduction written for executives by two guys from the Fair Issac corporation (the group that invented the credit score.) The essential gist of this book is that we can use analysis of the tons of data collected about customers/consumers to better understand how to not just make, but to automate decisions. If you’ve ever read the book The Numerati by Stephen Baker, it is the more detailed dive into the new world of data mining and decision making that is governing many business and political decisions.

Quoting Lowell Bryan, managing partner at McKinsey & Gary Hamel author of The Future of Management, the authors bring to our attention that “increasingly the work of managers won’t be done by managers. Instead it will be pushed out to the periphery. It will be embedded in systems.”

The greatest benefit will be seen in retail operations (credit cards, banks, retail stores) — where there is a lot of data on consumer behavior, and where the primary business decisions are being made on the front-lines by retail employees or call-center folks. One of the most interesting examples the authors give is about Best Buy and how they used analytics to better understand the types of customers coming into the store, created personas for each of these behavior types: Barry, the affluent techy enthusiast; “Jill”, the busy suburban mom; “Ray” the price-conscious family man; “”Buzz”, the young gadget fiend. Best Buy then rearranged the layout of the some of its stores to better serve these types. In addition, they trained their front-line employees to ask life-style questions to uncover the needs of each of these types (“how are you going to use this product?”, “Is it for you or someone else?”.)

The three essential components of using analytics is:

1. Developing a Rules-Based System – automating high-volume operations decisions to make the decisions more consistent and increase control (such creating and understanding personas, and creating a set of questions to ask the types.)
2. Using Predictive Analytics Models – creating decision models and frameworks to mathematically evaluate the trade-offs among conflicting objectives then execute decisions; using adaptive control (the process of making the best possible decision to control a complex system based on current knowledge and learn more about how the system behaves.)
3. Connecting Decisions Across Multiple Dimensions - also known in part as cross-selling.

The use of both descriptive analytics – the process of finding relationships/patterns among data (i.e. figuring out the personas as described in the Best Buy example); and of predticive analytics – using what you do know to make informed decisions aobut what you don’t know to predict what might happen in the future – it expresses the future in terms of odds and probabilities.

The descriptions of how to make business decisions using analytics sounds similar to the way one imagines business decisions are currently made. However, there is a difference of degree and of control. In expert-driven decision making, one uses the experts and their experience. In data-informed decision-making, the experts interpret the information into a report and it informs the decisions. In data-guided, a predictive model replaces the unproven assumptions with objective information, and the model provides advisory decisions (methinks this is what happened in the investment banks). Finally in data-driven decision making, the running of analytic models and execution of decision are completely automated. The control is in the rules created to describe the system, whether that be a bank, a electronic store, or credit card business. The problems come in when the system is described incompletely and something unexpected happens.

The gist of this book is that decisions based on analytics are the way of the future. Decisions on how much credit-card increase to give people, whether to approve them for a loan, or what kind of other products can be sold to them are all automated. The rules are set by the business and math people, who interpret the data and create rules based on this interpretation. This feels very much like game-design.

To effectively use analytics you need organizations that have tons of data, and that collect the right kind of data. From this you can derive patterns and understand how to better make decisions, make suggestions based on these analytics. But you have to have good data, and thoughtful people making the rules, otherwise you may end up creating a system that controls you, rather than informs you. It’s a new way of thinking of understanding the world.

This book is a basic introduction to this world — at this point, I feel I need more in-depth thoughtful exploration of how it works best in the web world. Onto the next read.

• Steve Meretzky — VP of Game Design at Playdom
  funny, very experienced and knowledgeable game designer, now designing Social Games
• Dave Castelnuovo — of Pocket God (Game), cofounder at Bolt Interactive
  one of the first entrepeneurs to successfully lead the charge into iPhone Games, very funny

Notes from the meeting:

Dave Castelnuovo:

• Created an app game called Pocket God where you help pygmaies get off the island, but can also do ultimate evil to them.
• Talked about and how he got started in games — long hours working on other projects, as an employee, then as independent contractor. Really wanted to get on the iPhone bandwagon.
• Used the idea of sprint projects, setting himself goals to create a usuable game/app within 10hrs and just get it out the door. Create a prototype. Get things done in a set amount of time. A way to focus yourself when life keeps distracting you.
• Created app game with co-worker. Many updates, done weekly, quick turnaround, to add features to the game.
• Early on noticed that his game was mentioned on TouchArcade – a community/reivew site. Starting interacting with the community reviewing his project. Built trust. Recommends toucharcade.com as a place to get feedback.
• The key is to build grassroots, build slow and steady, then go for eyeballs and ramp up.
• His first game had 150 downloads per day, 2nd game 2 or 3, Pocket God – ramped up to millions. The key is to interact with your community.
• Chose your category on the app store carefully. Simulation is a category where its easier to stay at the top. What categories you choose is key.
• Apple used to take 3 days to approve and app. Now approval time is up to 3 weeks. if you posted updates frequently, it would push your app to the top. No more.

Castelnuovo was a wonderful, self-deprecating storyteller. He left me feeling that I too, could design games, given enough chutzpah and willingness to give up sleep.

Steve Meretzky:

• Presentation on the ABCs of social games.
• Great intro of Steve Meretzky, sounds like a great guy.. and fun.
• Who knew Stanford had a game industry archive? Steve donated to it when he moved from MA to a much smaller house

Presentation Notes:

• Social games are different from traditional games in that:
  • can be cooperative or competitive
  • have content that changes over time
  • have potential for negative behavior
  • they are easy to get into –> start simple and reveal depth over time.
• Design and business of social games is intermixed — cannot have one without the other.
  • Virality and monetization.
  • Goals of virality
    • Once you start the game/install game, the designer must get you to come back to game.
    • What you want to do and what terms of service (TOS) of the platform allows (Facebook, MySpace, iPhone App Store platforms)
    • The overlap of TOS and what you want is the what you end up doing. Developers however, are constantly pushing the boundaries of the TOS, and the rules of what is allowed is constantly changing..
  • Viral tools
    • Invites
      • Negatives – they require action on part of the user, TOS have limited number of invites that can go out
      • Positives – they are persistent in the user’s inbox.
    • Wallposts
      • are bragworthy
      • high profile
      • can disappear in a user’s stream rather quickly
    • Notification channels
      • Negatives – require action on part of user (click to activate the Notification window).
      • Positives — once they are there, they are paying attention
• New changes afoot in Facebook
  • Notifications changing (easier to see access), number of invites allowed changing, new scores/points/post? from game will be allowed.
• New viral strategies
  • join my mob
  • beat my score
  • let’s exchange gifts
  • Wish list
  • Be my employee (playfish started this with restaurant)

• The key to Monetization starts with engagement
• Games have a longer form (arch), they allow you to build a presence over time.
  • Bejeweled, which has 4 mil players, is unable to monetize because it’s game arch is limited, does not allow building of engagement over time. They don’t know how to make $$ with their fan base.
• Key monetization comes from
  • Re-engagement strategies
    • …. harvesting fields..
    • collect $ (mobster),
    • daily login rewards.
    • Taking care of employees (who are your social network friends)
    • taking care of pets.
    • Someone beat high score.
  • Monetization strategies – selling:
    • virtual goods (major $$ strategy)
    • premium virtual goods for rare items and that also have in game use
    • accessories for avatar customization,
    • buying stuff for your pet
    • content — charge for premium content
    • mini-games within a game (i.e. within sorority game)
• Themes within social games.
  • What’s not working is what works in non-social gaming before (FPS, Fantasy, Sci-Fi)
  • Real world settings work (Mobster, Sorority, Farmville, Restaurant, etc.)
  • This is now the mass market games… based on RL
• The future….
  • more social synchronous game time
  • personal profiles play into game more
  • your social graphs – who you interact with, how, etc.
  • cyber-expression of selves in the social world

Meretzky had a good perspective on what works in social games. He was also very clear that the rules keep changing. Excellent presentation.