Authors : Mahdi Mirhoseini Pierre-Majorique Léger Sylvain Sénécal Abstract. Using Electroencephalography (EEG), this study aims at extracting three features from instantaneous mental workload measure and link them to different aspect of the workload construct. An experiment was designed to investigate the effect of two workload inductors (Task difficulty and uncertainty) on extracted features along with a subjective measure of men- tal workload. Results suggest that both subjective and objective measures of workload are able to capture the effect of task difficulty; however only accumulated load was found to be sensitive to task uncertainty. We discuss that the three EEG measures derived from instantaneous work- load can be used as criteria for designing more efficient information systems.

1. The Influence of Task
Characteristics on Multiple
Objective and Subjective
Cognitive Load Measures
Mahdi Mirhoseini
Pierre-Majorique Léger
Sylvain Sénécal
Gmunden Retreat on NeuroIS
Gmunden, Austria
Jun 6-8, 2016

2. How can we use
neurophysiological measures
to uncover more aspects of
cognitive load construct?

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Workload and its consequence
Working memory is the set of mental resources that people use to
encode, activate, store, and manipulate information while they
perform cognitive tasks (Baddeley 2003)
Workload reflects the interaction of mental demands imposed on
operators by task (Cain 2007)
Workload has consequences: frustration, negative affects, mental
fatigue, and user satisfaction (Mizuno et al., 2011, Gwizdka, 2010)

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Measuring workload
Subjective workload measures prevent us from understanding the multiple
variations of workload during a task and are subject to a retrospective bias
Measuring the mental workload construct has been a challenge to researchers to
researchers in different fields
Researchers have compared subjective and objective mental workload and
suggested that objective measures can provide a more comprehensive and richer
understanding of the workload construct
However, thus far, research has only used one of many possible measures
of objective workload when comparing it to subjective workload

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Workload : Different perspective
There are three types of cognitive load
measures: subjective, performance,
and physiological
Xie and Salvendy (2000) defined four
types of workload:
Peak load
Average load
Accumulated load, and
Overall load

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Hypotheses
H1: Task difficulty is positively associated with all
workload types (Overall, Average, Accumulated,
Peak).
H2: Task uncertainty is positively associated with
all workload types (Overall, Average,
Accumulated, Peak).

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Methodology
A 2 (low or high task difficulty) X 2 (low or high task uncertainty) within-subject
experiment was designed
Factors Low Uncertainty High Uncertainty
Simple
5 non-perishable product
The same quantity as suggested in
the recipe (4 people)
5 perishable product
The same quantity as suggested in
the recipe (4 people)
Complex
5 non-perishable product
Adjust quantities for 20 people
5 perishable product
Adjust quantities for 20 people

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Methodology
N=10 (50% were male)
Tasks were randomly ordered
Timeline:

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Methodology
Measurement
Overall Load Cameron (2007)
Instantaneous load: A linear EEG algorithm, which includes calculating the
((delta+theta)/alpha) power ratio over a moving 2 second window and compare it
with the average of previous 20 seconds Coyne et al., (2009)
Accumulated load: The area under the instantaneous workload curve
Peak load: The number of times that the amplitude of instantaneous load
exceeded 2.5 standard deviations of the instantaneous load

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Results
Thus, H1 is supported.
H1 Regression results
Overall b= 0.88, p<0.01
Average b=0.02, p<0.05
Accumulated b=44.45, p<0.01
Number of Peaks b=4.87, p<0.05

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Results
Thus, H2 is partially supported.
H2 Regression results
Overall b=0.51, p=0.18
Average b=0.01, p=0.15
Accumulated b=35.24, p<0.05
Number of Peaks b=3.12, p=0.15

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Discussion
Our results suggest that all the extracted features of instantaneous load and the
subjective measure of workload (i.e., Overall load) are sensitive to task difficulty;
however only Accumulated load was able to capture the mental workload
induced by task uncertainty
Posthoc Analysis:
Four regression models with the same independent variables (Task difficulty and
uncertainty) but with four different measures of workload as dependent variable
(Overall, Accumulated, Average, and number of Peaks).

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Discussion
Results
Dependent Variable R2
Accumulated 21%
Number of Peaks 16%
Overall 14%
Average 5%

16. 1) introducing a mental
workload feature
extraction method in
order to benefit from the
richness of EEG data
2) deriving three new
metrics for measuring
mental workload
Average load and overall
load yield similar results
while Accumulated load is a
stronger indicator of the
total workload experienced
by users.
Number of Peaks is also an
appropriate metric to
assess users’ mental
Summary Contributions
Copyright Nom de l’étudiant
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Next Steps
1- Using Accumulated load as criteria for design:
Testing multi search feature on an existing online shopping website
2- Testing primary versus recency effect
3- EFRP:
Manipulating workload factors on a shopping
Using users’ eye fixation as an event