Information systems and task demand: An exploratory pupillometry study of computerized decision making

作者:

Highlights:

• Human-computer collaboration could be improved by observing human pupil data as a proxy of cognitive load

• Pupil dilation, pupil dilation trends, and pupil variation vary with task demand in computerized decision making

• Information about the distribution of cognitive effort during various stages of decision making can be provided by pupil dilation trends

• Pupillometry has the potential to serve as a reliable, objective, continuous, and unobtrusive measure of task demand to improve adaptive decision support systems

• Adaptive decision making theory may serve as a suitable theoretical lens for such pupillometry studies

摘要

Information systems (IS) play an important role in successful execution of organizational decisions, and the ensuing tasks that rely on those decisions. Because decision making models show that cognitive load has a significant impact on how people use information systems, objective measurement of cognitive load becomes both relevant and important in IS research. In this paper, we manipulate task demand during a decision making task in four different ways. We then investigate how increasing task demand affects a user's pupil data during interaction with a computerized decision aid. Our results suggest that pupillometry has the potential to serve as a reliable, objective, continuous and unobtrusive measure of task demand and that the adaptive decision making theory may serve as a suitable framework for studying user pupillary responses in the IS domain.

论文关键词:Pupillometry,Task demand,Adaptive decision making,Eye tracking,Cognitive load

论文评审过程:Received 10 January 2016, Revised 22 January 2017, Accepted 15 February 2017, Available online 20 February 2017, Version of Record 22 April 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2017.02.007