Uploaded by Mariel García Hernández

An eye-tracking study on the effect of infographic structures on viewer’s comprehension and cognitive load

An eye-tracking study on the effect of
infographic structures on viewer’s
comprehension and cognitive load
Information Visualization
2018, Vol. 17(3) 257–266
Ó The Author(s) 2017
Reprints and permissions:
DOI: 10.1177/1473871617701971
Azam Majooni1, Mona Masood1 and Amir Akhavan2
The basic premise of this research is investigating the effect of layout on the comprehension and cognitive
load of the viewers in the information graphics. The term ‘Layout’ refers to the arrangement and organization
of the visual and textual elements in a graphical design. The experiment conducted in this study is designed
based on two stories and each one of these stories is presented with two different layouts. During the experiment, eye-tracking devices are applied to collect the gaze data including the eye movement data and pupil
diameter fluctuation. In the research on the modification of the layouts, contents of each story are narrated
using identical visual and textual elements. The analysis of eye-tracking data provides quantitative evidence
concerning the change of layout in each story and its effect on the comprehension of participants and variation of their cognitive load. In conclusion, it can be claimed that the comprehension from the zigzag form of
the layout was higher with a less imposed cognitive load.
Visualization, visual storytelling, infographic, layout, eye tracking
In this study, the main objective is to investigate the
effect of the layout of the Infographics in the formation
of the mental model and cognitive load. The most
important elements of information graphics are the
use of visuals (images, graphs, font size and colour).1
Infographics can be easier to read if effective visuals
are applied in their structure. The parameters such as
balance in the placement of text and graphics are
essential in making an infographic aesthetically pleasing to look at.2 The visual elements of an Infographic
should be able to narrate the visualized story with a
minimal requirement for additional text explanations.3
Several studies support that images and graphs are
salient compared to the texts and can capture the
immediate attention of the viewers.4 The proper
arrangement of visuals and graphs can provide coherence for an infographic design. A coherent layout is
very important in guiding the viewers from one section
of the infographic to the other related section based on
the flow of the story. Besides the visual elements, cultural and language background can be very important
in the formation of the layout. English-speaking readers naturally read textual contents from left to right
and top to bottom. The results of this study show that
the subjects of this study tend to move from left to
right and from up to bottom, therefore arrangement of
layout plays an important role in the design of the
Infographics.5 In order to determine the influence of
the layout on the cognitive load, the gaze data of the
participants are recorded using the eye-tracking
Centre for Instructional Technology & Multimedia, Universiti
Sains Malaysia, George Town, Malaysia
School of Computer Sciences, Universiti Sains Malaysia, George
Town, Malaysia
Corresponding author:
Azam Majooni, Centre for Instructional Technology & Multimedia,
Universiti Sains Malaysia, George Town, 11800 Penang, Malaysia.
Email: [email protected]
devices. The recorded gaze data for two different
Infographic stimuli are analysed and the results are
discussed. Without loss of generality, in this experiment, a suggested layout with zigzag form demonstrated better results. Therefore, it could be assumed
that this form of layout if applied in the real-world
Infographics should be more comprehensible. The
predictable orientation of the chunks in this model
helps the viewers follow the story of the Infographic
more steadily with less distraction.
The term ‘Infographic’ is the abbreviation for the
information graphics. The name has become popular
in the past few years. From the novelty perspective,
some believe Infographics have been used from a long
time ago and even consider the prehistoric paintings in
the caves as the early Infographics which tell a story
using graphical elements and illustrations.6,7 However,
the demand and application of Infographics have been
growing rapidly in the past few years. The popularity
of the terms searched on Google search engine can be
estimated by the aid of Google trends;8 these statistics
provide that the term ‘Infographics’ is searched almost
seven times more frequent during the year 2014 compared to the same period in 2011. The main purpose
of Infographics is to represent information and convey
meaning by the aid of graphical elements; this task is
sometimes accompanied by small textual contents.9
An Infographic usually contains a story embedded
in it; therefore, it can be assumed as a visual storytelling method.10 The modern automated illustration
tools have extensively simplified the design process of
Infographics, but in the crowded and information
overloaded world, attracting and keeping the attention
of the audience is an extremely difficult task. Almost
40 years ago, Herbert Simon11 was one of the first
researchers to directly point out that attention is a
scarce resource in an information-rich world, he also
mentioned that: ‘What information consumes is rather
obvious: it consumes the attention of its recipients’.
Similar to any other storytelling medium, such as
novels, scripts and motion pictures, visual storytelling
requires a skilled director and an attractive plot to capture the attention of the audience.
There exist only a few elaborated guidelines to
design a good Infographic and also there is no clear definition for estimating the efficiency of the design.
However, some general conceptual requirements
based on the standards stated by the Roman architect
Vitruvius are presented by Moere and Purchase.2 The
Vitruvius triangle states the basic requirements for
an architectural design: soundness, utility and
Information Visualization 17(3)
attractiveness.2 These requirements have been
addressed and labelled as Appeal for attractiveness
and Comprehension and Retention for utility by Lankow
et al.3
There has been an ongoing debate about the appeal
or beauty (usually referred as aesthetics) of visualizations between the psychologists, artists, architects,
computer scientists and philosophers.12 According to
Fechner,13 the most central principle of aesthetics is
‘the right combination of diversity in unity’. Moreover,
basic adjustable features of aesthetics such as colour,
contrast and clarity;14 simplicity and complexity;15 and
balance and scale16 along with novelty17 and surprise18
have been analysed intensively by the researchers to
find the effectiveness (aesthetic impression) of each of
the features in the design of visual artefacts.19
The appeal of an Infographic presentation is necessary for attracting the attention of the viewer; nonetheless, the main goal of any visualization is to deliver
abstract information to the viewer. Therefore, comprehension and the retention of the visualization are the
key factors in the design of any Infographic.20
In order to successfully maintain these factors,
storytelling based on instructional design strategies
can be applied. Storytelling is a very successful way for
transferring knowledge,7,21 although an Infographic
aims to take advantage of this technique, but it is the
receiver that perceives the presented visualization.
Eventually, the viewer starts developing a mental
model after seeing the external visual and textual elements inside the Infographic.22 In the process of developing the mental model, the viewer automatically
creates connections between the mental model and the
external visualization.22
According to the scaffolding theory, a temporal
framework can improve the understanding of the
viewer; additionally, according to the chunking principle, the cognitive load can be reduced by presenting
the visualizations in small chunks.23,24 In this study,
both the scaffolding theory and chunking principle are
applied to design the experiment. The main goal of
cognitive load theory is to introduce methods to
enhance the intellectual performance of the learners;25
therefore, monitoring cognitive load can show the
effectiveness of visualizations.26
The goal of designing Infographic is to transfer knowledge (mostly conceptual knowledge) to the viewers in
a very short time, premised on the assumption that
there are three main elements in the scenario of
Infographics design: message (story), the sender (story
teller) and receiver (viewer). The designer should go
Majooni et al.
Figure 1. Schematic form of the layouts for stories A and B.
through a sequence of steps, which includes ‘gathering, processing, pictorial rendering, analysing and
interpreting data’.27 Because of the nature of the
Infographics, the designer attempts to map the story to
be attractive and clear so that the viewer can develop
the intended mental model of the story with the least
effort.7 Card et al.28 have presented a visual mapping
model that includes four sequential steps. At the first
and second stages, the designer possesses original data
and prepares data tables. In the third stage, the data
tables are transformed/mapped into visualizations.
Finally, in the last stage, the designed visual structure
is transformed to view. The process of mapping the
data tables into visualization can be carried out by several visualization techniques.29 In this study, the main
concern is to overview the layout issue of the infographic. Several studies have discussed issues about
the layout, and automated design of layouts,30 but to
the best of our knowledge, there has not been any
study investigating the layout of visualization using
eye-tracking techniques and analysing the cognitive
load yet. There are two main research questions in this
study: (1) What is the effect of layout in the formation
of the mental model? (2) Which type of suggested layouts is effective in decreasing the cognitive load?
The answer to these statements is investigated using
the comprehension questions and analysing the gaze
data including the fixations, saccades, the number of
the blinks and the pupil dilation of the subjects.
The experiment includes two stories (A and B) which
compare two types of layouts (1 and 2) for each story.
The designs are based on chunking principle, scaffolding theory and Cards method28 manipulating two different layouts. The schematic shape of the layouts for
A-1, A-2, B-1 and B-2 are presented in Figure 1.
As it can be seen from Figure 1, in the story A, the
layouts 1 and 2 compare the Stairs (Steps) with the
Zigzag organization, also in the story B the layouts 1
and 2 compare Vertical columns with Horizontal rows
organization of the chunks.
In order to reduce the possible bias caused by external variable, the effort has been to identify effective
variables and remove the sources of bias. The variables
related to the subjects such as age, gender, educational
and cultural background are addressed by inviting participants from almost the same age, cultural and educational background and an equal number of male and
female participants from the same ethnics. The participants are put into two groups with different tasks each
one containing both types of stimuli. Similarly, in the
design of the tasks, the duration of the task, the applied
colours and symbols, font size and other graphical elements are kept constant.
Information Visualization 17(3)
divided into a sequence of small chunks of data. In the
second step, the chunks are translated into graphical
elements accompanied with small textual data (story
elements). In the last step, each chunk is organized by
composing the layout nodes. The steps used for the
design of the stimuli are similar to those suggested by
Card et al.28
In this experiment, 23 local undergraduate (second
year) students from the same field of study (School of
Housing, Building and Planning, Universiti Sains
Malaysia) and nationality participated. Three of the
participants had poor eye-tracking calibration in the
final results; therefore, their results were eliminated
from the final experiment results and gaze data of the
remaining 20 participants (10 females, 10 males) were
used for the analysis. The age range of the participants
was between 22 and 23 years with standard deviation
of less than 1 year. All the participants were randomly
put into two groups of experiment with similar content
but different designs (each group containing n = 10
In order to record the gaze data, in this experiment,
remote eye-tracking device (SMI, ‘iView X RED’,
50 Hz) is used. In order to achieve the best results,
the device was calibrated and the calibration is validated before each task and the level of the eye-tracking
cameras were adjusted based on the height of the subjects. At the final stage, the results of the subjects with
lower calibration score were ignored. The recorded
gaze data are then transferred for the further analysis.
Two stories are visualized to design the Infographics
and are used as stimuli in this experiment. Each story
is presented with two different layouts (2 stories 3 2
layouts = 4 stimulus). The graphical elements and colours used for each story are identical and only their
layout differ. The Infographics contain general information from two different general areas. In the first
set, layout A-1 is based on a single Stairs (Steps) path
from left to right and top to bottom, whereas layout
A-2 is based on a single Zigzag path from top to bottom with the same story. In the second set, layout B-1
has divided the page into three major vertical columns,
whereas layout B-2 has divided the page into three horizontal rows. The schematic form of the layouts is presented in Figure 1.
In order to apply the layout, initially, the arbitrarily
selected pieces of textual information are outlined and
Subjects were randomly assigned to one of the two
groups I and II. These groups each contained two separate tasks (A and B) recorded by eye-tracking device.
There was a 1-min break between the first and the second task. The instruction and the steps of the experiment were briefly described to the subject to achieve
better calibration on the eye-tracking device. After
each task in the experiment, each participant was
asked to answer questions related to the comprehension of the Infographic. The participants are assured
that the results of the questions are anonymous and
will not be distributed. The process of the experiment
was straightforward and no other interaction was made
with the subject. The assigned exposure duration for
each stimulus was 1 min, the amount was equal for all
the participants. According to the initial pilot study,
1 min was sufficient for the tasks.
In order to explore the comprehension of the subjects,
scores of the answers to the questions are calculated.
The comprehension scores for each group are presented in Table 1.
The analysis of the gaze data and score of the questions for each task can be used to study the effect of
layouts on the comprehension and cognitive load of
the subjects. To analyse gaze data and compare the
variations of the cognitive load, a threshold method is
applied to study the sequence of saccades. In the second analysis, the overall increase in the cognitive load
for each stimulus is calculated using the CLS
(Cognitive Load Score) calculation methods.31
In order to calculate the comprehension score for the
tasks, immediately after each task, the subjects are
asked to answer a set of conceptual questions about
the viewed Infographics. Because of the short period
of the tasks and existence of no time span between the
tasks and the questions, the long-term memory is not
involved and only the comprehension is estimated.
The final results presented in Table 1 demonstrate the
scores of the subjects in respect to every stimulus.
Majooni et al.
Table 1. Average gaze data for each stimuli.
(per minute)
dilation (%)
Average overall
fixation (ms)
Score (%)
Figure 2. Sample of a saccade symbolic representation.
Saccade patterns
When the visual attention is directed to another location, the eyes move fast to position the fovea to the
point of attention to achieve higher resolution image
from the attention point. This fast movement of the
eye (relocation of gaze) is called as saccade.32
Monitoring saccades can be very helpful in providing
the scan path of the stimuli. As mentioned in the earlier sections, the information used to design the infographic were initially outlined and each item has been
translated into one graphical element and accompanied abstract textual contents (chunks). The chunks
are placed such that subject sees one chunk at a time.
Accordingly, the fast eye movements (saccades)
between each fixation show the path in which the subject goes through the chunks in the infographic.
However, the subject starts this path from the most
salient position of the infographic. In addition, the subjects tend to explore the whole infographic in the first
2–5 s to create an overall understanding of the whole
story. In this analysis, we categorize the saccades for
each stimulus into three groups (short, medium and
long saccades) according to their length. This grouping
is related to the distance between the chunks inside
every infographic layout. The medium size saccades
are the ones which are in the range of the distance
between two neighbour chunks in the stimuli. The saccades longer than and shorter than the medium-sized
saccades for each stimulus are set as long and short
saccades, respectively. The symbols (S, M and L) are
assigned to ‘short, medium and long’ saccades, respectively. This method is similar to threshold filtering in
the symbolic dynamics. Figure 2 demonstrates a sample of a saccade symbolic representation.
Information Visualization 17(3)
Figure 3. Density map of the gaze data for story A and story B layouts.
As it can be seen from Figure 2, there exist more
than five repetition of type ‘S’ saccade between every
couple of type ‘M’ saccade. By investigating the area of
interest (AOIs), it can be presumed that the subjects
relocate their gaze from one chunk to another chunk
with type ‘M’ saccade whereas they tend to explore the
whole infographic in the beginning and at the end of
the experiment using type ‘L’ saccades.
Density map
A density map (also called as heatmap) diagram provides information about the number and duration of
eye fixations of a subject on stimuli acquired from an
eye-tracking device. In the density map diagram, the
longer fixations are represented by red and yellow colours, whereas green and blue colours represent less
attention and shorter fixation time.33 Figure 3 demonstrates density map diagram for story A and story B
layouts of all subjects. As it can be seen from this figure, the fixations are overlapped on the layout of the
Infographics. According to the density map diagrams,
it can be concluded that majority of the fixations are
in the upper half of the page, which confirms the claim
that the upper portion of the Infographics is more
Cognitive load analysis
There exist two other features besides the fixations
and saccades that can be recorded easily using the eyetracking devices. The number of the blinks and pupils
dilation during the experiment are two measures that
can help estimation of variation of the cognitive
Pupil dilation. Klingner et al.36 have investigated the
effect of an increase in cognitive workload on the
pupillary dilation. They have concluded that subtle
changes in the pupil diameter can be used to measure
the cognitive workload. In this study, in order to compare the overall cognitive load between two different
types of layouts for each story, the numerical integral
dilation of the pupil diameter for each eye is calculated. Figure 4 shows a sample of papillary dilation on
infographic type A-1.
Majooni et al.
Figure 4. Sample of papillary dilation on infographic type A-1.
Blinks. Blinks rate can also be a good measure of the
cognitive load and fatigue.36,38–40 Based on the study
conducted by Recarte et al.,41 the number of blinks
can even be more effective in estimating the increase
in the cognitive load caused by the visual searching in
comparison to the pupil dilation. They claim that the
cognitive load estimation based on pupil dilation
method cannot differentiate between the mentally and
visually challenging tasks. However, in this study, similar to the method suggested by Majooni et al.,31 the
blinks rates and the pupil dilations are recorded and
stored in a database (along with the saccades, fixations
and the gaze location) for all the subjects.
Efficiency. The efficiency measure is calculated using
the classification of the number correct answers to the
questionnaire, the blinks rate, the saccades length, the
number of fixation and the average of fixation duration. The normalized value of the Efficiency is a measure between zero and one, when it is closer to one it
means the design has been more efficient from both
cognitive load and comprehension point of view. In
the CLS method, five distinct and independent parameters (saccades length, fixations length, blinks rate,
pupil dilation and the score of the questions) are effective in classification of the value of the efficiency score.
Each one of these parameters separately affects the
efficiency score. The maximum and minimum for
each parameter is first identified and then the classification is applied to avoid the presence of any bias. The
method can easily be applied to any type of infographic or visualization. The value is equally
dependent on the score of the questions, pupil dilation, blinks rate and number of long saccades and fixations. The classification is operated using the Weka
software, which is a collection of neural network algorithms for data mining tasks.42 In this study, the
Zigzag layout A-2 had the lowest amount of blinks rate
and pupillary dilation and highest amount of correct
answers and accordingly achieves highest efficiency
rate. In contrast, the Horizontal rows layout B-2 with
the lowest comprehension and highest pupillary dilation has the lowest efficiency score.
Analysis of AOIs. The designed Infographics are based
on chunks order and their relations in a sequential format; therefore, in this experiment, the sequences of
the fixations on AOIs are investigated. In order to
complete this task, an indexed AOI is assigned to each
one of the chunks with the order intended by the
designer. The average visit sequence of the AOIs for
each stimulus is then calculated based on the number
and latency of the visit. For each AOI, the average visit
order and average visit latency are assigned and then
again a second sequence is generated based on these
latencies and visit order. In the last step, the similarity
of the sequence of visited AOIs versus the intended
order of chunk’s sequence is estimated using classification of similar clusters method. Table 2 provides the
average similarity of the AOIs index order versus
chunks order. According to the similarity results, the
AOI sequence of the layouts A-2 is slightly more similar to the intended chunk order compared to the AOI
sequence of layout A-1. In the case of sequence
Information Visualization 17(3)
Table 2. Average similarity of the AOI’s sequences versus
chunks order.
Story A (%)
Story B (%)
Layout 1
Layout 2
besides using the fixation data for identification of
attention, we classified the saccade data into three
categories and compared the eye movement behaviours of the subjects using the saccades classification
(Figure 2) and the pupil dilation (Figure 4).
Layout and cognitive load
similarity, story B-1 has better similarity score compared to B-2. The analysis of order of AOIs is based
on the calculation of Bayesian similarity of clusters
method and does not necessarily prove the efficiency
of any of the layouts and it can only be addressed as
an insight.
The answer to the first research question of this study
can be investigated by comprehension score of the
subjects, meaning that the layouts can be significantly
effective in conveying information. With the study of
the scan path of each of the subjects, we noticed that
the subjects tend to move from one chunk to the other
chunk usually following the path provided by the layout. The observation demonstrates that, during the
experiment, the subjects tend to go back a few (two or
three) chunks and start over (revisit the chunks). This
revisit of AOIs can either be interpreted as the difficulty of understanding43 or steps of making the connection between the previous and current chunk
(inductive reasoning). The analytic study of pupil dilation shows that this eye movement behaviour was
almost the same for all the subjects. Therefore, it can
be claimed that it is related to the visual memory and
the process of mental model formation rather than the
difficulty of the information.
According to Treisman and Gormican,44 human eye
can process simple visual objects in a time period as
short as 40–50 ms. In this study, the number of revisits and dwell time for each AOI has been calculated.
The average dwell time for each AOI has been in the
range of 80–250 ms. However, the dwell time was not
proportional to the number of words and elements in
each chunk. In some cases, two similar chunks with
almost exactly the same amount of content had an
extremely different average dwell time. In this case, it
can be claimed that the subject was no more looking
at the AOI and actually was busy processing the information and building the mental model. In this study,
In order to study the variation in the cognitive load
and also calculate the average workload for each stimulus, the average number of the blinks and the sum
of dilation of the pupils for each stimulus is calculated for all the subjects. In order to calculate the
workload, the results are linearly normalized between
zero and one and workload score is calculated based
on the number of blinks and integral of pupil dilation
for each subject and stimuli. In addition, results provide that the average saccade length for the subjects
viewing stimuli A-2 in the first 30 s has been slightly
longer than Stimuli A-1. This difference could be
caused by the distances difference between chunks in
each stimulus.
The analysis of the recorded parameters for each
participant on each stimuli can be used to calculate
overall efficiency index for each subject. The average
of overall efficiency index of each layout for all subjects
is calculated and presented in Table 1. According to
the results, it can be concluded that the layout A-2
which is based on a Zigzag path has significantly higher
efficiency index compared to layout A-1. In addition,
the layout B-2 (three vertical columns) has been more
efficient compared to top-down layout B-1 (three horizontal rows).
Instructional design strategies, such as scaffolding theory, if applied in the design of Infographics can be
effective in decreasing the cognitive load and reducing
the initial confusion. In this study, two contexts are
presented in the form of Infographics. The two contexts are initially split into small chunks (following the
chunking principle) and then the chunks are presented
on four different layouts (two for each context). All of
the layouts are organized according to the scaffolding
theory. The main goal of this study is to investigate the
effect of the layout on the comprehension and cognitive load of the subjects. In order to investigate the
effect of each layout on comprehension of the participants, a set of brief conceptual questions are asked
about the Infographics from the subjects. In addition,
to identify the effect of each layout on the cognitive
load of subjects, their gaze data (fixations, saccades,
blink rate and pupil dilation) were recorded. The gaze
data for the participants were analysed using simple
Majooni et al.
linear classification method. Finally, the results suggest
which layouts perform better in decreasing workload
and increasing comprehension. In addition, from the
results of the experiments, in can be concluded that
using natural left-right (up-down) eye movement of
the viewers could be useful in the layout design and
improvement of the comprehension of the viewers
from the Infographics and visualizations.
This research was supported by University Sains
Malaysia, Centre of Instructional Technology and
Multimedia (Grant No. 1001/PMEDIA/817072).
1. Harris RL. Information graphics: a comprehensive illustrated reference. Atlanta, GA: Management Graphics,
2. Moere AV and Purchase H. On the role of design in
information visualization. Inform Visual 2011; 10(4):
3. Lankow J, Ritchie J and Crooks R. Infographics: the power
of visual storytelling. Hoboken, NJ: John Wiley & Sons,
4. Larkin JH and Simon HA. Why a diagram is (sometimes) worth ten thousand words. Cognitive Sci 1987;
11(1): 65–100.
5. Faraday P. Visually critiquing web pages. In: Proceedings
of the 6th conference on human factors the web, Austin, TX,
19 June 2000.
6. Mol L. The potential role for infographics in science communication. PhD Thesis, Athena Institute, Vrije Universiteit
Amsterdam, Amsterdam, 2011.
7. Bertschi S, Bresciani S, Crawford T, et al. What is
knowledge visualization? Eight reflections on an evolving
discipline. In: Marchese FT and Bannisi E (eds) Knowledge visualization currents. London: Springer, 2013, pp.
8. Pulizzi J. The rise of storytelling as the new marketing.
Publish Res Q 2012; 28(2): 116–123.
9. Huang W, Parsons P and Sedig K. Handbook of human
centric visualization. New York: Springer, 2014.
10. Gershon N and Page W. What storytelling can do for
information visualization. Commun ACM 2001; 44(8):
11. Simon HA. Designing organizations for an informationrich world. In: Greenberger M (ed.) Computers, communication, and the public interest, vol. 37. Baltimore, MD:
The Johns Hopkins University Press, 1971, pp. 40–41.
12. Lau A and Vande Moere A. Towards a model of information aesthetics in information visualization. In: Proceedings of the 11th international conference on information
visualization, IV’07, Zurich, 4–6 July 2007, pp. 87–92.
New York: IEEE.
13. Fechner GT. Vorschule der aesthetik, vol. 1. Wiesbaden:
Breitkopf & Härtel, 1876.
14. Pachalska M. The psychology of art and the evolution of
the conscious brain. J Nerv Ment Dis 2006; 194(8): 632–
15. Birkhoff GD. Aesthetic measure. Cambridge, MA and
London: Harvard University Press, 1933.
16. Cawthon N and Moere AV. The effect of aesthetic on the
usability of data visualization. In: Proceedings of the 11th
international conference on information visualization, IV’07,
Zurich, 4–6 July 2007, pp. 637–645. New York: IEEE.
17. Hekkert P, Snelders D and van Wieringen PCW. ‘Most
advanced, yet acceptable’: typicality and novelty as joint
predictors of aesthetic preference in industrial design.
Brit J Psychol 2003; 94(1): 111–124.
18. Ludden GD, Schifferstein HN and Hekkert P. Surprise
as a design strategy. Des Issues 2008; 24(2): 28–38.
19. Moshagen M and Thielsch MT. Facets of visual aesthetics. Int J Hum-Comput St 2010; 68(10): 689–709.
20. Graves A. Creation of visualizations based on linked
data. In: Proceedings of the 3rd international conference on
web intelligence, mining and semantics – WIMS’13,
Madrid, 12–14 June 2013.
21. Wojtkowski W and Wojtkowski WG. Storytelling: its role
in information visualization. In: European systems science
congress, Crete, Greece, 16–19 October 2002, pp. 1–2.
Emerald Group Publishing Limited. Available at: http://
22. Schnotz W and Kürschner C. External and internal
representations in the acquisition and use of knowledge:
visualization effects on mental model construction. Instr
Sci 2007; 36(3): 175–190.
23. Baker RM. Examples of scaffolding and chunking in
online and blended learning environments. Soc Sci Res
Netw. Epub ahead of print 2010. DOI: 10.2139/
24. Young JQ, Van Merrienboer J, Durning S, et al. Cognitive load theory: implications for medical education:
AMEE guide no. 86. Med Teach 2014; 36(5): 371–384.
25. Sweller J, Van Merrienboer JJ and Paas FG. Cognitive
architecture and instructional design. Educ Psychol Rev
1998; 10(3): 251–296.
26. Huang W, Eades P and Hong SH. Measuring effectiveness of graph visualizations: a cognitive load perspective.
Inform Visual 2009; 8(3): 139–152.
27. Gotel OC, Marchese FT and Morris SJ. On requirements visualization. In: Proceedings of the second international workshop on requirements engineering visualization,
2007 (REV 2007), Washington, DC, 15–19 October
2007, p. 11. Washington, DC: IEEE Computer Society.
28. Card SK, Mackinlay JD and Shneiderman B. Readings in
information visualization: using vision to think. San Francisco, CA: Morgan Kaufmann Publishers, 1999.
29. Qin C, Zhou C and Pei T. Taxonomy of visualization
techniques and systems: concerns between users and
developers are different. In: Proceedings of the Asia GIS
conference, Wuhan, China, 16–18 October 2003, pp.
30. Nesbitt K and Friedrich C. Applying Gestalt principles
to animated visualizations of network data. In:
Information Visualization 17(3)
Proceedings of the sixth international conference on information visualization, London, 10–12 July 2002.
Majooni A, Masood M and Akhavan A. Scientific visualizations based on integrated model of text and picture
comprehension via eye-tracking. Procedia: Soc Behav Sci
2015; 176: 52–59.
Duchowski A. Eye tracking methodology: theory and practice. London: Springer, 2007.
Drusch G, Bastien J and Dinet J. From gaze plots to eye
fixation patterns using a clustering method based on
Hausdorff distances. In: Proceedings of the 23rd French
speaking conference on human-computer interaction, Sophia
Antipolis, 24–27 October 2011, p. 1. New York: ACM.
Kahneman D and Beatty J. Pupil diameter and load on
memory. Science 1966; 154(756): 1583–1585.
Ahern S and Beatty J. Pupillary responses during information processing vary with Scholastic Aptitude Test
scores. Science 1979; 205(4412): 1289–1292.
Klingner J, Kumar R and Hanrahan P. Measuring the
task-evoked pupillary response with a remote eye tracker.
In: Proceedings of the 2008 symposium on eye tracking
research & applications, Savannah, GA, 26–28 March
2008. New York: ACM.
Di Stasi LL, Antolı́ A and Cañas JJ. Evaluating mental
workload while interacting with computer-generated
artificial environments. Entertain Comput 2013; 4(1):
Stern JA, Boyer D and Schroeder D. Blink rate: a possible measure of fatigue. Hum Factor 1994; 36(2): 285–
Fukuda K, Stern JA, Brown TB, et al. Cognition, blinks,
eye movements, and pupillary movements during performance of a running memory task. Aviat Space Envir Md
2005; 76(7): 75–85.
Benedetto S, Pedrotti M, Minin L, et al. Driver workload and eye blink duration. Transport Res F: Traf 2011;
14(3): 199–208.
Recarte MA, Pérez E, Conchillo A, et al. Mental workload and visual impairment: differences between pupil,
blink, and subjective rating. Spanish J Psychol 2008;
11(2): 374–385.
Hall M, Frank E, Holmes G, et al. The WEKA data
mining software: an update. ACM SIGKDD 2009;
11(1): 10–18.
Goldberg JH and Kotval XP. Computer interface evaluation using eye movements: methods and constructs. Int J
Ind Ergonom 1999; 24(6): 631–645.
Treisman A and Gormican S. Feature analysis in early
vision: evidence from search asymmetries. Psychol Rev
1988; 95(1): 15–48.