I’ve written a couple of posts already about motivation (the motivation to learn and motivational momentum) but today I want to explore some of the issues associated with that powerful driver: challenge.
The ability to overcome some conflict is central to the engagement of most narrative experiences. Similarly the level of challenge associated with any game, or stage within a game, is critical in maintaining and encouraging participation in it. The challenge or difficulty presented by any voluntary task needs careful management if it is to keep the user taxed appropriately, that is suitably stretched but not frustrated. Csikszentmihalyi’s theory of Flow describes a ‘channel’ where participants enjoy the optimal experience of play-suspended consciousness while developing their skill.
If the challenge is too much for the user’s skill level, the experience quickly induces anxiety and overwhelming frustration; if the skill level outstrips the challenge, the user is swiftly bored and disengaged.
The key to successful engagement depends on setting the appropriate level of difficulty for the user’s current skills. The difficulty of any game is the product of various elements:
The appropriate level of challenge is dependent on the differing needs and levels of expertise of the target user group and even on the type of task. Games employ different strategies for determining a satisfying level of difficulty. At the simplest level, the game offers options at the start of play such as easy, normal or hard. These levels might manifest themselves in the sheer quantity of conflicts to address as in Sim City with its ability to turn on more features or the ‘intelligence’ of the opposition as in electronic Chess and its ability to ‘think ahead.’ Some games, such as Silent Hill 2 recognise that different types of task might require alternate settings. In this case, the game offers players settings for the puzzle and action aspects of the experience. Ritual offers users control over both the level of challenge (between ‘casual’ and ‘extreme’) and the assistance given to players by other characters (ranging from ‘quickly’ to ‘never’). The Grand Theft Auto series operates a ‘mixed economy’ of challenge with the free-roaming environmental playground offering user-defined activity and specific missions giving greater reward for higher levels of difficulty.
Rather than giving the user control of difficulty, some games, exemplified by the car-racing genre, provide adaptive handicapping of the computer competition. In this approach, the system alters the intelligence of the non-player characters according the player’s current performance to provide opposition that is slightly above and below the user’s current competence.
The most sophisticated forms of difficulty setting offer dynamic and escalating levels of challenge. Elaboration Theory is a learning model that advocates a progression of successively more complex problems. Proponents argue that the clear sense of progression is a powerful motivator. However, these challenges need careful sequencing if they are to keep offering players the optimal experience. Most story-based games like Metal Gear Solid provide increasing levels of challenge where players ‘graduate’ to more difficult levels by achieving the desired goals. Each successive level assumes a degree of competence as demonstrated by the successful completion of the previous one. However if the leap is too great, the challenge is too much for the potential skills development; too small and the player loses his sense of progression.
Players take risks in games because the consequences are rarely significant in the real world but it would be incorrect to believe that there is no comeback from repeated failure. The cost of lack of progress in a game can range from simply lost time to loss of hard-earned privileges and reputation. Particularly in multiplayer games, long terms failure has a genuine social impact, as one veteran player of World of Warcraft commented: “No one wants to be a member of a guild that always wipes out.”
It is far to say, therefore, that the measure of the effectiveness of a game is its ability to develop player skills to tackle ever more challenging scenarios. As players learn, so clever games increase the level of difficulty to maintain the user’s position in the flow channel; getting the level wrong leaves players bored or frustrated. Isn’t that the main cause of disruption in learning?
How many educators need to play a few more games?
Over the last couple of years, I’ve been doing some thinking about the nature of games for the BBC. With gamification the new hot idea and with it the attempt to apply game mechanics to just about every industry both online and real world, it felt like a good time to revisit the core concept of a game.
A game is more than simply an activity with a score
There are countless definitions of ‘game’ by academics and social theorists including:
Dempsey’s “A game is a set of activities involving one or more players. It has goals, constraints and consequences. A game is rule-guided and artificial in some respects. Finally, a game involves some aspect of a contest or a trial of skill or ability, even if that contest is with oneself.“
And Avedon and Sutton-Smith’s suggestion from their book, The Study of Games: “At its most elementary level…we can define a game as an exercise of voluntary control systems in which there is an opposition between forces, confined by a procedure and rules in order to produce a disequilibrial outcome.”
In 2003, researchers Salen and Zimmerman compared 8 academic definitions in their book Rules of Play: Game Design Fundamentals and came up with:
“A game is a system in which players engage in an artificial conflict, defined by rules that result in a quantifiable outcome.”
Frankly, I don’t find any of those academic definitions particularly helpful.
There are grey areas in what constitutes a ‘game’ but we should be cautious about using the term too liberally. Many purists would balk at the suggestion that a multiple choice quiz is a game because the ‘play’ is so simplistic: there is but one rule (to answer questions correctly), one goal (to get all the answers right) but there is negligible ‘conflict’ (that is a sense of competition) or user control (the ability to make anything more than a binary decision).
So I’ve started to take a slightly different approach that focusses on qualities instead. For an activity to be a game, it has to include the majority of the following features:
Of course not all games will exhibit all these characteristics but I think it is a useful starting point when making a case.
What do you think?
In my previous post, I shared some thoughts about the motivation to learn. Today I’m thinking about the momentum that motivation generates.
There are a number of factors that can generate motivation. These can include:
Active participation in a task allows the participant to materially affect the outcome through meaningful choices. This personal responsibility instils a sense of ownership whereby success or failure depends on a positive contribution by the learner. It is not enough to merely observe – the learner must act. Simply by making a decision, learners are investing in the activity’s conclusion.
Seeing the effects of a contribution makes the participation real. This immediate feedback, often taking the form of incrementally altered graphics in computer games, illustrates the effect the learner is having on proceedings. This interim feedback is often an implicit reflection of current conditions before a conclusive summary of performance occurs.
The frequent delivery of feedback encourages learners to overcome challenges that otherwise might be considered too hard but the tasks themselves need to be perceived as achievable if the learner is to remain committed says Stanford’s Carol Dweck in her study, Motivation, In Foundations for a psychology of education ( 1989). For the activity to be satisfying, it should push the boundaries of the learner’s competency and demonstrate clear development. While reinforcing existing skills can build confidence, it is the extension of ability that drives longer-term engagement.
However, to be authentic, the outcomes need to maintain a level of uncertainty, if not unpredictability – a foregone conclusion does not engage participants to the same degree as an event determined by involvement. And, by the same token, if the outcome remains fluid it implies a level of open-endedness.
Although there are concerns about learners being heavily influenced by extrinsic motivational factors like competition and performance goals rather than learning goals, in the short term, the desire to ‘win’ can be very compelling and the triumph over a series of conflicts is a universal motivator.
A highly motivated learner generates a set of conditions that encourages further progress: motivation creates an environment that is conducive to ongoing motivation. Although motivation is central to almost all activity, its characteristics are core to learning per se. Therefore achieving and maintaining motivation should be seen as crucial to the learning experience.
What Miguel is saying is that motivated learners seek out the most successful solution either individually or in a group. Their desire to overcome the challenge presented will often encourage them to work more creatively, look for more effective responses or alternative approaches. When highly motivated teams work together, they instinctively resort to dialogue to refine their thinking: Gorden Pask describes how one person will ‘teach’ another what they have learnt about the situation (Conversation, Cognition, and Learning, 1975).
The dialogue that occurs during collaboration highlights the relative strengths of the cohort with some participants displaying a better grasp of the issue or an illuminating perspective. These ‘expert’ peers support their collaborators in raising their understanding, a process Vygotsky calls ‘scaffolding.’
The increased motivation to succeed prompts more imaginative problem solving as learners look for results. This increased drive encourages higher levels of engagement particularly where there is also some form of competition.
It’s clear that engaging learners and successfully motivating them is key to effective learning but it’s important to remember that engagement alone doesn’t generate improved skills.
The initial challenge for any learning is to determine, encourage and exploit an individual’s motivation so I’ve been thinking a little about what motivates us to learn and what motivation can acheive. Particularly after enforced schooling has finished.
K.Patricia Cross identifies a number of reasons why adults choose to learn voluntarily:
But there’s more to it than that. Motivation has two determinants – drive and incentive. ‘Drive’ is the ‘internal aversion state’ that seeks to reduce a perceived level of deprivation – for example, the discomfort felt by feeling ignorant among peers and ‘incentive’ is the perceived attractiveness of the reward – passing an exam to achieve a pay rise, for example.
A particularly important aspect of motivation is how the user responds to any perceived failure. Those who believe that their failure is the consequence of ‘stable factors’ such as natural ability or intelligence are more likely to give up on a task than those who believe lack of success was due to ‘unstable factors’ that can be corrected through a change of strategy or more effort. Ensuring that learners assume a mindset that attributes progress to factors under their control is essential for long-term engagement and development.
Active engagement in an activity, inspired by motivated learners, can lead to a sense of what Csikszentmihalyi defines as ‘flow.’ Flow describes profound activity that appears effortless. During instances of flow, learners make significant progress towards overcoming some challenge without necessarily being conscious of the process. Daniel Goleman suggests that people enter flow through intentional focus or the taxing of existing skill. Motivation provides focus and minimises the effect of extraneous influences.
Marc Prensky argues that there are a number of signals that indicate that a learner is motivated. These signs are highly desirable in and of themselves with regard to learning. They include:
If learners pursue learning of their own volition, it clearly indicates that there is some driving force encouraging continued attention. Where this learning is beyond the required, it demonstrates highly effective engagement in the materials. Obviously, when this learning becomes extramural, it can be a distraction, but otherwise this unconscious diligence proves useful for progress.
This willing momentum often manifests itself in the learner’s own expansion of the challenge. Self-directed problem posing shows the energy of intellectual curiosity that can transport the learner beyond the expected bounds of educational programmes.
Associated with self-directed problem posing is the persistence required to see problems through to their solution. Without a high level of motivation, learners tend to abandon activity when it becomes too challenging. This frustration not only halts the learning at that time, it can also create barriers to future engagement. Persistent learners demonstrate an attitude that sees challenge as a reason to continue, not a reason to stop. At the same time, the satisfaction derived from completing a task, achieving a solution and beating the problem provides encouragement to explore further still. Learners find themselves with a self-perpetuating momentum that often only stops because of external factors such as running out of time.
Achieving the learning objectives gives learners a sense of progress – a measurable shift in cognitive ability, for example. Extending learning beyond that which was expected gives the learner a genuine sense of triumph. This manifests itself not only in the deliberate creation of new challenges but also in the profound satisfaction of ‘winning.’ This ‘triumph over adversity,’ however small, makes learning enjoyable. Educators should not underestimate this pleasure in learning. And pleasure provides the most sustainable energy to continue activity in all but the most extreme emergencies.
I struggled writing the title for this blog because it’s so obvious isn’t it? Of course education makes us cleverer, for many that’s the whole point. I suspect that many people, like me, have assumed that it’s about ‘filling’ our heads with knowledge but learning offers much more than that – it’s not just about making the most of the cognitive ability we have, the process of developing skills (mental, affective and physical) actually improves the brain itself.
According to the Brainwaves 2 report from the Royal Society this month (summarised earlier), education is “the most broadly and consistently successful cognitive enhancer of all.” It recognises that in popular understanding, cognitive enhancement is more usually associated with drugs, vitamins or sophisticated technologies so it’s nice to be reassured that that fundamental part of our lives, learning, is the most effective neurological exercise we can enjoy.
It’s reinforced by a study published in Bio-med Central by researchers looking at the Framingham Offspring Study. Analysis of nearly 4000 participants indicates that better education leads to lower blood pressure, lower body mass index (BMI), less smoking and less drinking (although educated women drink more than their less educated sisters, apparently).
It’s an important message to send to those who think the purpose of school is merely to find a job and that learning ends at the school gate.