For all roles observed, the tasks initiated after an interruption were most often professional communication tasks.
(See "Software That Learns from Users"). The Task Tracer research employed machine-learning techniques to build desktop applications that were able to learn and observe the task that a user was working on at any given moment.
On the upper right side of the figure, it is possible to observe the task structure framed according to the timing properties of the task (P,D,T), and on the bottom right side, it is possible to observe the task's serialized representation (i.e., task execution without parallelism).
In this figure, it is possible to observe the task structure of a fork-join task (left side), its timing properties (upper right side), and its serialized representation (lower right side).
Initially the task was done individually without other educators observing; the task was then used in a group setting to create an opportunity for discussion of the concept of equipoise and the potential impact of beliefs on delivering the intervention.
To illustrate, we observed the following task effects – in the 'eye' region, gender was only decoded during the expression task and not during the gender task; and vice versa in the 'mouth' region.
And in the spirit of the Philipse family, Ms. Johnson observed that the task of reproducing the paintings for the exhibition was given to a local concern.
Conversely, laterality effects were neither observed when the task involved "Perceptually Identical" or "Different" letter pairs.
However, deterioration in performance was observed in the task to stretch a rubber band around 16 nails.
In this analysis, we observed that the task of finding relevant content for documenting specific API elements is not trivial: sometimes it can be subjective.
