Document Type
Article
Publication Date
2018
Department
Industrial Engineering
Abstract
Potential benefits of multiscreen and multiple device environments were assessed using three different computing environments. A single factor, within-subject study was conducted with 18 engineering students in a laboratory experiment. Three levels for the computing environment factor included one with a desktop computer with a single monitor (control, condition A); one with a desktop with dual monitors, as well as a single tablet computer (condition B); and one with a desktop with a single monitor, as well as two tablet computers (condition C). There was no statistically significant difference in efficiency or workload when completing scenarios for the three computing environments. However, a dual monitor desktop with a single tablet computer (B) was the ideal computing environment for the information-rich engineering problem given to participants, supported by significantly fewer errors compared to condition C and significantly higher usability ratings compared to conditions A and C. A single desktop monitor with two tablet computers (C) did not provide any advantage compared to a single desktop monitor (A).
Original Publication Information
Saleem JJ, Weiler DT. 2018. Performance, workload, and usability in a multiscreen, multi-device, information-rich environment. PeerJ Computer Science 4:e162 https://doi.org/10.7717/peerj-cs.162
ThinkIR Citation
Saleem, Jason J. and Weiler, Dustin T., "Performance, workload, and usability in a multiscreen, multi-device, information-rich environment" (2018). Faculty and Staff Scholarship. 412.
https://ir.library.louisville.edu/faculty/412
DOI
10.7717/peerj-cs.162
ORCID
0000-0002-7397-5170
Comments
© 2018 Saleem and Weiler
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.