@inproceedings{412dc07cf407432e8501695e09024571,
title = "Automatic versus manual forwarding in web surveys - A cognitive load perspective on satisficing responding.",
abstract = "We examine the satisficing respondent behavior and cognitive load of the participants in particular web survey interfaces applying automatic forwarding (AF) or manual forwarding (MF) in order to forward respondents to the next item. We create a theoretical framework based on the Cognitive Load theory (CLT), Cognitive Theory of Multimedia Learning (CTML) and Survey Satisficing Theory taken also into account the latest findings of cognitive neuroscience. We develop a new method in order to measure satisficing responding in web surveys. We argue that the cognitive response process in web surveys should be interpreted starting at the level of sensory memory instead of at the level of working memory. This approach allows researchers to analyze an accumulation of cognitive load across the questionnaire based on observed or hypothesized eye-movements taken into account the interface design of the web survey. We find MF reducing both average item level response times as well as the standard deviation of item-level response times. This suggests support for our hypothesis that the MF interface as a more complex design including previous and next buttons increases satisficing responding generating also the higher total cognitive load of respondents. The findings reinforce the view in HCI that reducing the complexity of interfaces and the presence of extraneous elements reduces cognitive load and facilitates the concentration of cognitive resources on the task at hand. It should be noted that the evidence is based on a relatively short survey among university students. Replication in other settings is recommended.",
keywords = "Web surveys, Interactivity, Human-computer interaction, Interface design, Cognitive load theory, Cognitive Theory of Multimedia Learning, Survey satisficing theory, Sensory memory, Working memory, Long-term memory, Satisficing responding, Automatic forwarding, Manual forwarding, Item-level response times, Standard deviation, Cognitive burden, Nondifferentiation, Straightlining, Intrinsic cognitive load, Extraneous cognitive load, Eye-tracking, Eye-movements, Proactive attention, Contiquity principle, Spatial orienting, Attentional capture, Group-mean centering, Log-linear regression model, Attentional capture, Automatic forwarding, Cognitive burden, Cognitive load theory, Cognitive Theory of Multimedia Learning, Contiquity principle, Extraneous cognitive load, Eye-movements, Eye-tracking, Group-mean centering, Human-computer interaction, Interactivity, Interface design, Intrinsic cognitive load, Item-level response times, Log-linear model, Long-term memory, Manual forwarding, Nondifferentiation, Proactive attention, Satisficing responding, Sensory memory, Spatial orienting, Standard deviation, Straightlining, Survey satisficing theory, Web surveys, Working memory",
author = "Arto Selk{\"a}l{\"a} and Mario Callegaro and Couper, {Mick, P.}",
year = "2020",
month = jul,
doi = "10.1007/978-3-030-49570-1_10",
language = "English",
isbn = "978-3-030-49569-5",
volume = "LNCS",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "130–155",
editor = "Gabriele Meiselwitz",
booktitle = "Social Computing and Social Media",
address = "Germany",
edition = "12194",
note = "null ; Conference date: 19-07-2020 Through 24-07-2020",
}