  Scrolling is an essential interaction technique enabling users to display
previously off-screen content. Existing evaluation models for scrolling are
often entangled with the selection of content, e.g., when scrolling on the
phone for reading. Furthermore, some evaluation models overlook whether the
user knows the target position. We have developed ScrollTest, a general-purpose
evaluation tool for scrolling speed and accuracy that avoids the need for
selection. We tested it across four dimensions: 11 different scrolling
techniques/devices, 5 frame heights, 13 scrolling distances, and 2 scrolling
conditions (i.e., with or without knowing the target position). The results
show that flicking and two-finger scrolling are the fastest; flicking is also
relatively precise for scrolling to targets already onscreen, but pressing
arrow buttons on the scrollbar is the most accurate for scrolling to nearby
targets. Mathematical models of scrolling are highly linear when the target
position is unknown but like Fitts' law when known.
