Design and Evaluation of Computing Technologies to Promote Learning of Feature-Rich Software

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Feature-rich software applications, such as photo-editing software, word-processing applications, and spreadsheet applications, are used by over one billion people each year to accomplish diverse productivity-related and recreational tasks. These applications are very powerful, in part owing to the hundreds (or even thousands) of commands and options that they make available. At the same time, the sheer volume of commands can make feature-rich software difficult for individuals to learn and use. Consequently, techniques for promoting efficient access to needed commands and for increasing the ease with which users learn feature-rich software have received considerable attention by the HCI and applied AI communities over the past 30 years. While this prior research has contributed several important techniques and design guidelines, the landscape of feature-rich software continues to shift substantially, raising a host of new challenges and opportunities including: a decentralization of the help resources upon which users rely, the increasing availability of web-based knowledge on command-to-task mappings, the increasing popularity of user-contributed content, and the growing diversity of computer users which now also includes young children.