Year: 2007
Type: report
Abstract: This work reports results from two studies investigating intelligent notification scheduling. The first study tested the performance of composite statistical models for detecting and differentiating three granularities (types) of breakpoints within novel task sequences. Results showed that the models detect breakpoints reasonably well, but do not perform as expected for differentiating their type. Our second study investigated how scheduling notifications at different types of breakpoints affects users and their tasks. Results showed that scheduling notifications to occur at breakpoints reduces frustration and reaction time relative to delivering them immediately. We also found that the content of a notification determines the type of breakpoint at which it should be scheduled. The overall concept of scheduling notifications at breakpoints matched well with how users preferred notifications to be managed. This indicates that users would be willing to adopt the use of notification scheduling systems in practice.
Authors: Shamsi T. Iqbal, Brian P. Bailey
Institution: University of Illinois Urbana-Champaign
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W1158960174