Table of Contents Author Guidelines Submit a Manuscript
Advances in Human-Computer Interaction
Volume 2009, Article ID 121494, 9 pages
Research Article

Cognitive Load in eCommerce Applications—Measurement and Effects on User Satisfaction

1Department of Psychology, University of Basel, Missionsstrasse 62a, 4055 Basel, Switzerland
2IV-Stelle Basel-Stadt, Lange Gasse 7, 4052 Basel, Switzerland

Received 15 October 2008; Accepted 24 February 2009

Academic Editor: Richard Kline

Copyright © 2009 Peter Schmutz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Guidelines for designing usable interfaces recommend reducing short term memory load. Cognitive load, that is, working memory demands during problem solving, reasoning, or thinking, may affect users' general satisfaction and performance when completing complex tasks. Whereas in design guidelines numerous ways of reducing cognitive load in interactive systems are described, not many attempts have been made to measure cognitive load in Web applications, and few techniques exist. In this study participants' cognitive load was measured while they were engaged in searching for several products in four different online book stores. NASA-TLX and dual-task methodology were used to measure subjective and objective mental workload. The dual-task methodology involved searching for books as the primary task and a visual monitoring task as the secondary task. NASA-TLX scores differed significantly among the shops. Secondary task reaction times showed no significant differences between the four shops. Strong correlations between NASA-TLX, primary task completion time, and general satisfaction suggest that NASA-TLX can be used as a valuable additional measure of efficiency. Furthermore, strong correlations were found between browse/search preference and NASA-TLX as well as between search/browse preference and user satisfaction. Thus we suggest browse/search preference as a promising heuristic assessment method of cognitive load.