Difficulty Curveball

On successfully winning our epic battle with the concept of Magnitude itself, the next thing was to work out how to make the gameplay of Millie Moreorless equally engaging for players of different abilities.

When we were starting out, one of the key things that parents of children with Down's Syndrome told us was that their kids love the same games as anyone else (Angry Birds, Temple Run, Clash of Clans, etc) - the trouble was that they became too difficult too quickly. This is a cornerstone of inclusivity: we are all human beings, we all like similar things.

In an iPad game like Millie Moreorless, accessibility means firstly making sure that every player is welcomed in and supported to understand the rules of the game. It then becomes a question of articulating the difficulty curve so that each player faces just the right level of challenge to keep them engaged with the game and rewarded for giving it their attention, and thus gradually develops their ability through play rather than it feeling like work.

It is especially important for us to get this right as although Millie Moreorless plays and feels like a mainstream game, it is secretly an educational product. Our aim is to help children with Down's Syndrome develop better number skills.

Our target audience is children with Down's Syndrome aged 3-12. This is an extremely wide range in terms of cognitive development time, and of course even children the same age can have vastly differing abilities. We are determined that anyone can play Millie, whatever their ability, but at the same time we don't want to lose players who have a slightly higher ability because they are not sufficiently challenged.

Thus the difficulty curve has to be carefully articulated to measure the player's base-line ability and respond appropriately by giving them array choices that challenge but don't exclude them. It also needs to evolve as they play the game if we are to help people to develop number skills. In game design speak, our dynamic difficulty adjustment mechanism has to be very sophisticated.

This requires a lot of testing!