http://hdl.handle.net/10388/11931

Sotoodeh Mollashahi, E. (2019). Improving Revisitation in Long Documents with Two-Level Artificial-Landmark Scrollbars http://hdl.handle.net/10388/11931

Revisitation – returning to previously-visited locations in a document – is commonly done in the digital world. While linear navigation controls provide a spatial representation of the document and allow effective navigation in short documents, they are not effective in long documents, particularly for revisitation. Bookmarks, search and history dialogs, and “read wear” (visual marks left as the user interacts with the document) can all assist revisitation; however, for long documents all of these tools are limited in terms of effort, clutter, and interpretability. Inspired by visual cues such as coloured edges and “thumb indents” in hardcopy books, recent work has proposed artificial landmarks to help users build up natural spatial memory for the locations in a document; in long documents, however, this technique is also limited because of the number of pages each landmark represents. To address this problem, this thesis proposes a Double-Scrollbar design that uses two columns of artificial landmarks that can provide greater specificity for spatial memory and revisitation in long documents. We developed three versions of landmark-augmented Double-Scrollbar, using icons, letters, and digits as landmarks. To assess the performance and usability of the Double-Scrollbar design, two studies were conducted with 21 participants, each visiting and revisiting pages of a long document using each of the new designs, as well as a single-column design and a standard scrollbar. Results showed that two levels of icon landmarks were significantly better for assisting revisitation, and were preferred by participants. The two-level artificial-landmark scrollbar is a new way of improving revisitation in long documents by assisting the formation of more precise spatial memories about document locations.

Masters, University of Saskatchewan, Integrated Modelling Program for Canada

http://hdl.handle.net/10388/11931