Open AccessReducing Friction for Knowledge Workers with Task Context
Author(s) -
Kersten Mik,
Murphy Gail C.
Publication year - 2015
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v36i2.2581
Subject(s) - knowledge worker , task (project management) , computer science , human–computer interaction , context (archaeology) , knowledge management , interface (matter) , productivity , focus (optics) , work (physics) , engineering , mechanical engineering , paleontology , physics , macroeconomics , systems engineering , bubble , optics , maximum bubble pressure method , parallel computing , economics , biology
Knowledge workers perform work on many tasks per day and often switch between tasks. When performing work on a task, a knowledge worker must typically search, navigate, and dig through file systems, documents, and emails, all of which introduce friction into the flow of work. This friction can be reduced, and productivity improved, by capturing and modeling the context of a knowledge worker's task based on how the knowledge worker interacts with an information space. Captured task contexts can be used to facilitate switching between tasks, to focus a user interface on just the information needed by a task, and to recommend potentially other useful information. We report on the use of task contexts and the effect of context on productivity for a particular kind of knowledge worker, software developers. We also report on qualitative findings of the use of task contexts by a more general population of knowledge workers.