If you work in either game design or training, you’ve probably seen this lovely graph once or twice. It tells us that in order to keep users in a happy state of flow, the difficulty of the task should match their level of mastery. Otherwise, we risk boring the user (too easy), or causing them anxiety (too difficult). So tasks should be just challenging enough to be interesting, but not so hard as to be anxiety inducing.

A graph describing difficulty vs mastery

This can be particularly challenging in both game design and training, since we deal with learners/players whose mastery is everchanging. If the program is doing its job, the “right difficulty” is a moving target since player mastery is evolving.

In training, this seems to be much more frequent than its opposite (ie, when the course is too challenging). Whether the course is gamified or not, the constant seems to be situations where, for fear of leaving one learner behind, the entire experience is nerfed down into the pit of boredom for everyone.

“Nerfing” is a term from gaming that is used when difficulty is reduced to the point of nullifying any challenge (or fun).

When tempted to nerf a project, ask yourself if you can’t use one of the following tactics from gaming:

  • Dynamic difficulty: adjusting the level of difficulty of a challenge for the individual learner, either through their choice or automatically;
  • Optional challenges: extra “sidequests” that can help a lagging learner practice and build up their mastery to pass the difficult challenge;
  • Dynamic challenges: direct different learners to different challenges to address each person’s individual learning gaps. This has the added bonus of making their training time more effective!

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