The Interaction Tasks

To evaluate the research hypotheses, a series of user studies was run in which participants performed two scored interaction tasks using the gesture interface: a sorting task, and a maze task. Both of these tasks are game-like, visual in nature, and could be performed using the simple gestures defined and supported by the described gesture system. Additionally, both of these interaction tasks provided opportunities to present users with all of the included affordance and feedback types in a meaningful way. These affordance and feedback types could then be enabled or disabled per study condition to evaluate their effect on interaction performance.

Participants in the user studies performed both interaction tasks, with the order counterbalanced across participants to reduce ordering effects (e.g. due to learning effects and the inherent difficulty of the tasks, relative to one another). The dominant hand of the participants was also controlled for with counterbalancing. To avoid the effects of the users’ hands obstructing their view of the interface, the interaction interface (minus the application area) was mirrored horizontally for left-handed users (see section 3.2.2). All users were incentivized to perform the tasks as quickly as they could, while minimizing errors (which clearly defined for each task). As such, users’ performance in these two tasks was principally affected by the study conditions introduced, and could thus be used to evaluate the research hypotheses.

60 4.3.1. Interaction Task 1: Sorting

Figure 11. The sorting task as it appeared in the gesture interface used by the study participants. Here, the user is about to drop the five of clubs card into the sorting bin labeled spades, so this will count as a task mistake.

The first interaction task (shown in Figure 11) is a sorting one, in which users were presented with playing cards and had to sort them into bins. The types of bins were: suits (4 bins), color (2 bins), and face vs. number cards (2 bins). To maximize the opportunity for affordance and feedback generation, each card appeared at a random location in the interface, the type of bins to be sorted into were change randomly, and order of the bins was be randomized as well. The location of the bins remained consistent, however.

To complete the sorting task, users had to use the supported hand gestures to select and hold the card, move it across the interface to the appropriate bin, and release the card to drop it there. A new card then appeared to be sorted (possibly into different bin types). The cognitive effort of determining which bin to sort a card into may be considered

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minimal, so performance was affected primarily by the clarity of using the interface. Users were be asked to perform the task as quickly and accurately as they could until they’d correctly sorted 5 cards, which constituted one round. They were then given a break of 30 seconds, to reduce arm fatigue, then repeat the task for a total of 3 rounds (so that they sorted a total of 15 cards).

The users were timed for each round of 5 cards, and the interface counts a task error every time the user drops a card in the wrong bin (in which case a new card is drawn) or moves it beyond the interaction space (in that case the same card is reset to its starting position). The number of gestures detected was counted as well: every time the user’s hand crossed the selection plane in either direction (i.e. every time they performed a tap or withdraw gesture, whether intentionally or not) was counted as a gesture attempt.

62 4.3.2. Interaction Task 2: Maze

Figure 12. The maze task as it appeared in the gesture interface used by the study participants. The token to be moved is the small green square at the top-left, and the goal into which it should be dripped is the larger yellow square at the right. Here, the user’s hand is outside the interaction bounds, so the out-of-bounds feedback is presented.

The second interaction task was a set of simple mazes (one is shown in Figure 12). In this task, the user had to move a token through an easy-to-solve maze to a goal. The principal challenge of this task was that allowing the token to touch the walls of the maze will reset it to the beginning. However, the purpose of this task is not to test coordination or puzzle-solving skill, so the paths in the maze were intentionally made very wide, and the mazes were static and manually fashioned to be very easy to solve.

To complete this task, users needed to use the supported gestures to select the token, move it through the maze to its goal (without touching the walls of the maze), and release the token to drop it there. Users were allowed to drop the item along the way and

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pick it up again to continue, without the item being reset to the start. When they completed a maze, they were given a break of 30 seconds (to reduce arm fatigue), and then the task was repeat with a new maze, for a total of 3 mazes. The 3 mazes were be defined statically (i.e. they will not be randomized) in order to ensure they are easily solvable.

Like in the sorting task, users were be timed in their completion of each round of this task (i.e. each of the three mazes). A task error was counted every time the user allowed the token to touch the maze walls (which also resets the icon to the beginning of the maze). Dropping the item within the walls of the maze to pause did not count as a task error, but did affect their completion time. Again, each detected tap and withdraw gesture (whether in the goal or not) was be counted as a gesture attempt.

For both interaction tasks, users were informed that the task is timed, and what constituted a task error, but they were not told that gesture attempts would be counted. The 90-second time limit was applied to each round to ensure that the study could proceed in a timely fashion. Users that could not complete a task round within this time limit were counted as taking the maximum possible time.