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Good fonts for dyslexia

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Abstract and Figures

Around 10% of the people have dyslexia, a neurological disability that impairs a person's ability to read and write. There is evidence that the presentation of the text has a significant effect on a text's accessibility for people with dyslexia. However, to the best of our knowledge, there are no experiments that objectively measure the impact of the font type on reading performance. In this paper, we present the first experiment that uses eye-tracking to measure the effect of font type on reading speed. Using a within-subject design, 48 subjects with dyslexia read 12 texts with 12 different fonts. Sans serif, monospaced and roman font styles significantly improved the reading performance over serif, proportional and italic fonts. On the basis of our results, we present a set of more accessible fonts for people with dyslexia.
Number of Fixations box plots by Font Type for group N (ordered by average Reading Time for group D). -OpenDys had the second smallest mean for number of fixations. Participants had significantly fewer fixations reading with OpenDys than with Verdana (p = 0.004). -Arial had the third smallest mean for number of fixations. Participants had significantly fewer fixations reading with Arial than with Courier (p = 0.023). -Summary: CMU, OpenDys and Arial led to significantly less fixations than three other fonts. In this case only 3 out of the 66 pairwise comparisons were significant. -Group N: There was a significant effect of Font Type on Number of Fixations (χ 2 (11) = 68.84, p < 0.001) (Table IV, Figure 9). The results of the post-hoc tests show that: -Arial had the smallest mean for number of fixations. Participants had significantly fewer fixations reading with Arial than with Arial It. (p < 0.001), Courier (p = 0.003), Times (p < 0.001), Times It. (p = 0.003), and Verdana (p < 0.001). -Verdana had the highest mean for number of fixations. Participants had significantly more fixations reading with Verdana than with Arial (p < 0.001), CMU (p = 0.001), Garamond (p < 0.001), and Helvetica (p = 0.014). -Participants had significantly fewer fixations reading with Times than with CMU (p = 0.022). -Participants had significantly more fixations reading with Arial It. than with CMU (p = 0.018), and Garamond (p = 0.006). -Summary: Arial and Times led to significantly less fixations than six other fonts, and Verdana and Arial It. led to significantly more fixations than five other fonts. That is, as one comparison appears twice, 10 out of the 66 pairwise comparisons were significant.
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Good Fonts for Dyslexia
Luz Rello
NLP & Web Research Groups
Universitat Pompeu Fabra
Barcelona, Spain
luzrello@acm.org
Ricardo Baeza-Yates
Yahoo! Labs &
Web Research Group, UPF
Barcelona, Spain
rbaeza@acm.org
ABSTRACT
Around 10% of the people have dyslexia, a neurological dis-
ability that impairs a person’s ability to read and write.
There is evidence that the presentation of the text has a
significant effect on a text’s accessibility for people with
dyslexia. However, to the best of our knowledge, there are
no experiments that objectively measure the impact of the
font type on reading performance. In this paper, we present
the first experiment that uses eye-tracking to measure the
effect of font type on reading speed. Using a within-subject
design, 48 subjects with dyslexia read 12 texts with 12 dif-
ferent fonts. Sans serif,monospaced and roman font styles
significantly improved the reading performance over serif,
proportional and italic fonts. On the basis of our results,
we present a set of more accessible fonts for people with
dyslexia.
Keywords
Dyslexia, font types, typography, readability, legibility, text
layout, text presentation, eye-tracking.
1. INTRODUCTION
Worldwide, around 15-20% of the population has a language
based learning disability [17]. Likely, 70-80% of them have
dyslexia [17], a neurological disability which impairs a per-
son’s ability to read and write. Previous research has shown
that text presentation can be an important factor regarding
the reading performance of people with dyslexia [11, 25].
On the other hand, any digital text has to be written using
one or several certain font types. Although the selection
of font types is crucial in the text design process, empirical
analyses of reading performance of people with dyslexia has
focused more on font size [23, 26] rather than on font type.
In this paper we present the first study that measures the
impact of the font type on the reading performance of 48
people with dyslexia using eye-tracking, as well as asking
them their personal preferences.
ASSETS 2013 Bellevue, Washington, USA
The main contributions of this study are:
Font types have a significant impact on readability of
people with dyslexia.
Good fonts for people with dyslexia are Helvetica,
Courier,Arial,Verdana and Computer Modern Uni-
code, taking into consideration reading performance
and subjective preferences. On the contrary, Arial It.
should be avoided since it decreases readability.
Sans serif,roman and monospaced font types increased
the reading performance of our participants, while
italic fonts did the opposite.
Next section focuses on dyslexia, while Section 3 reviews re-
lated work. Section 4 explains the experimental methodol-
ogy and Section 5 presents the results, which are discussed
in Section 6. In Section 7 we derive recommendations for
dyslexic-friendly font types and we mention future lines of
research.
2. DYSLEXIA
Dyslexia is a hidden disability. A person with dyslexia can-
not perceive if they are reading or writing correctly. Dyslexia
is characterized by difficulties with accurate word recogni-
tion and by poor spelling and decoding abilities [16]. This
implies that people with dyslexia have more difficulty access-
ing written information and, as side effect, this impedes the
growth of vocabulary and background knowledge [16]. Pop-
ularly, dyslexia is identified with its superficial consequences,
such as writing problems like letter reversals; but dyslexia is
a reading disability with a neurological origin. Brain struc-
ture, brain function, and genetics studies confirm the bio-
logical foundations of dyslexia [31].1Although dyslexia is
also popularly identified with brilliant famous people, such
as Steve Jobs or Steven Spielberg, the most frequent way to
detect a child with dyslexia is by low-performance in school
[4]. Moreover, dyslexia is frequent. From 10 to 17.5% of
the population in the U.S.A. [15] and from 8.6 to 11% of the
Spanish speaking population [18] have this cognitive disabil-
ity. The frequency and the universal neuro-cognitive basis
of dyslexia are the main motivations of this study.
1Despite its universal neuro-cognitive basis, dyslexia mani-
festations are variable and culture-specific [31].
3. RELATED WORK
The relationship between fonts and dyslexia has drawn the
attention of many fields, such as psychology, arts, and acces-
sibility. We divide related work in: (1) fonts recommended
for people with dyslexia, (2) fonts designed for this target
group, and (3) related user studies.
3.1 Recommendations
Most of the recommendations come from associations for
people with dyslexia and they agree in using sans-serif
fonts. The British Dyslexia Association recommends to use
Arial,Comic Sans or, as alternatives to these, Verdana,
Tahoma,Century Gothic, and Trebuchet [2]. However, the
website does not disclose on the basis of which evidence these
recommendations are made. In [10] recommendations for
readers with low vision as well as readers with dyslexia are
put in comparison, giving as a result the recommendation of
using also Arial and Comic Sans. In [22] is recommended to
avoid italics and fancy fonts, which are particularly difficult
for a reader with dyslexia, and also point to Arial as pre-
ferred font. Another font recommended in 2010 was Sassoon
Primary but not anymore [9].
The only recommendation for serif fonts has been done
by the International Dyslexia Centre [13] and that was for
Times New Roman. According to [1], Courier is easier to
read by people with dyslexia because it is monospaced.
In the Web Content Accessibility Guidelines (WCAG) [3],
dyslexia is treated as part of a diverse group of cognitive
disabilities and they do not propose any specific guidelines
about font types for people with dyslexia.
Surprisingly, none of the typefaces recommended by the
dyslexia organizations mentioned above were ever designed
specifically for readers with dyslexia.
3.2 Fonts Designed for People with Dyslexia
We found four fonts designed for people with dyslexia: Sylex-
iad [12], Dyslexie [21], Read Regular,2and OpenDyslexic.3
The four fonts have in common that the letters are more
differentiated compared to regular fonts. For example, the
shape of the letter ‘b’ is not a mirror image of ‘d’. From
these fonts, we choose to study Open Dyslexic (both roman
and italic styles), because it is the only open sourced and
hence free. This font has been already integrated in various
tools.
3.3 User Studies
There are several uses studies on text presentation and peo-
ple with dyslexia regarding font and background colors [25],
font [23, 26] or letter spacing [33].
The closest work to ours is a study with people with dyslexia
[21] that compared Arial and Dyslexie. They conducted
a word-reading test with 21 students with dyslexia (Dutch
One Minute Test). Dyslexie did not lead to faster reading,
but could help with some dyslexic-related errors in Dutch.
In [29], text design for people with dyslexia is explored with
a qualitative study with just eleven students. In some tasks,
2http://www.readregular.com/
3http://opendyslexic.org/
the participants needed to choose the font they prefer, but
no analyses of the chosen fonts is presented.
3.4 What is Missing?
What is missing is an objective investigation into the effect of
the most frequent fonts on reading performance. Our exper-
iment advances previous work by providing this evidence via
quantitative data from eye-tracking measurements. In ad-
dition, with testing 12 different fonts with 48 participants,
we compare a greater number of font types with a larger
number of participants than previous studies. We selected
the fonts on the basis of their popularity and frequency of
use in the Web.
4. METHODOLOGY
To study the effect of font type on readability and com-
prehensibility of texts on the screen, we conducted an ex-
periment where 48 participants with dyslexia had to read
12 comparable texts with varying font types. Readability
and comprehensibility were analyzed via eye-tracking and
comprehension tests, respectively, using the latter as a con-
trol variable. The participants’ preference was gathered via
questionnaires.
4.1 Design
In our experimental design, Font Type served as an inde-
pendent variable with 12 levels: Arial,Arial Italic,Com-
puter Modern Unicode (CMU),Courier,Garamond,Hel-
vetica,Myriad,OpenDyslexic,OpenDyslexic Italic,Times,
Times Italic, and Verdana (See Figure 1). We use for brevity
OpenDys for the corresponding fonts in the rest of the paper.
This is Arial
This is Arial It.
This is Computer Modern
This is Courier
This is Garamond
This is Helvetica
This is Myriad
This is OpenDyslexic
This is OpenDyslexic It.
This is Times
This is Times It.
This is Verdana
Figure 1: Fonts used in the experiment.
We chose to study Arial and Times because they are the
most common fonts used on screen and printed texts, re-
spectively [5]. OpenDyslexic was selected because is a free
font type designed specifically for people with dyslexia and
Verdana because is the recommended font for this target
group [2]. We choose Courier because is the most common
example of monospaced font [5]. Helvetica and Myriad were
chosen for being broadly used in graphic design and for being
the typeface of choice of Microsoft and Apple, respectively.
We chose Garamond because is claimed to have strong legi-
bility for printed materials [5] and we selected CMU because
is widely used in scientific publishing, as is the default of the
typesetting program TeX, as well as a free font supporting
many languages [20].
We also made sure that the fonts cover variations of essential
font characteristics:
Italics served as independent variable with two values:
italic denotes the condition where the text was pre-
sented using an italic type, that is a cursive typeface,
and roman denotes the condition when the text was
presented in a roman type. We study the italic types
of Arial,OpenDyslexic, and Times.
Serif served as independent variable with two values:
serif denotes the condition where the text was pre-
sented with typefaces with serifs, small lines trailing
from the edges of letters and symbols, and sans serif
denotes the condition when the text used typefaces
without serifs. In our set of fonts there are three serif
fonts –CMU,Garamond, and Times– and four sans
serif fonts –Arial,Helvetica,Myriad, and Verdana–.
Monospace served as independent variable with two
values: monospaced denotes the condition where the
text was presented using a monospaced type, that is, a
font whose letters and characters each occupy the same
amount of horizontal space, and proportional, where
the text was presented using proportional fonts. We
chose the most commonly used monospaced font, the
roman serif font Courier, and we compare it with the
rest of the roman and serif fonts that are proportional:
CMU,Garamond and Times.
For quantifying readability, we used two dependent mea-
sures:Reading Time and Fixation duration, both extracted
from the eye-tracking data. To control text comprehension
of the texts we use one comprehension question as a con-
trol variable. To collect the participant preferences, we used
subjective Preference Ratings through questionnaires.
Reading Time: Shorter reading durations are preferred to
longer ones since faster reading is related to more readable
texts [32]. Therefore, we use Reading Time, i.e. the time it
takes a participant to completely read one text, as a measure
of readability, in addition to Fixation Duration.
Fixation Duration: We used fixation duration as an ob-
jective approximation of readability. When reading a text,
the eye does not move contiguously over the text, but alter-
nates saccades and visual fixations, that is, jumps in short
steps and rests on parts of the text. Fixation duration de-
notes how long the eye rests still on a single place of the text
and we use the mean of the fixation durations obtained by
the eye-tracker. Fixation duration has been shown to be a
valid indicator of readability. According to [24, 14], shorter
fixations are associated with better readability, while longer
fixations can indicate that processing loads are greater. On
the other hand, it is not directly proportional to reading
time as some people may fixate more often in or near the
same piece of text (re-reading).
To check that the text was not only read, but also under-
stood, we used literal questions, that is, questions that can
be answered straight from the text. We used multiple-choice
questions with three possible choices: one correct choice, and
two wrong choices. We use this comprehension question as
acontrol variable to guarantee that the recordings analyzed
in this study were valid. If the reader did not chose the cor-
rect answer, the corresponding text was discarded from the
analysis.
Preference Ratings: In addition, we asked the partici-
pants to provide their personal preferences. For each of the
twelve text-font pairs, the participants rated on a five-point
Likert scale, how much did they like the font type used in
the text presentation.
We used a within-subject design, that is, each participant
read 12 different texts with 12 different fonts, hence, con-
tributing to each condition. We counter-balanced texts and
fonts to avoid sequence effects. Therefore, the data with
respect to text-font combinations was evenly distributed.
4.2 Participants
We had 48 people (22 female, 26 male) with a confirmed
diagnosis of dyslexia taking part in the study. Their ages
ranged from 11 to 50 (¯x= 20.96, s= 9.98) and they all
had normal vision. All of them presented official clinical
results to prove that dyslexia was diagnosed in an autho-
rized center or hospital.4Except from 3 participants, all
of the participants were attending school or high school (26
participants), or they were studying or had already finished
university degrees (19 participants). We discarded the eye-
tracking recordings that had less then the 75% of the sample
recorded, hence, 46 out of the 48 recordings were valid.
4.3 Materials
To isolate the effects of the text presentation, the texts them-
selves need to be comparable in complexity. In this section,
we describe how we designed the texts that were used as
study material.
4.3.1 Texts
All the texts used in the experiment meet the comparability
requirements because they all share the parameters com-
monly used to compute readability [8]. All the texts were
extracted from the same book, Impostores (Impostors), by
Lucas S´anchez [28]. We chose this book because its struc-
ture (32 chapters) gave us the possibility of extracting simi-
lar texts. Each chapter of the book is an independent story
and it starts always by an introductory paragraph. Thus, we
went through the book and selected the introduction para-
graphs sharing the following characteristics:
(a) Same genre and same style.
(b) Same number of words (60 words). If the paragraph
did not had that number of words we slightly modified
it to match the number of words.
(c) Similar word length, with an average length ranging
from 4.92 to 5.87 letters.
(d) Absence of numerical expressions, acronyms, and for-
eign words, because people with dyslexia specially en-
counter problems with such words [27, 7].
4In the Catalonian protocol of dyslexia diagnosis [6], the
different kinds of dyslexia, extensively found in literature,
are not considered.
El texto habla de: ‘The text is about:’
Un sue˜no. ‘A dream.’
Un parque de atracciones. ‘An amusement park.’
Un helado de chocolate. ‘A chocolate ice cream.’
Figure 2: Comprehension control question example.
4.3.2 Text Presentation
Since the presentation of the text has an effect on the read-
ing speed of people with dyslexia [11], we used the same
layout for all the texts. They were left-justified, using a 14
points font size, and the column width did not exceeded 70
characters/column, as recommended by the British Associa-
tion of Dyslexia [2]. The color used was the most frequently
used in the Web for text: black text on white background.
4.3.3 Comprehension Control Questions
After each text there was one literal comprehension control
question. The order of the correct answer was counterbal-
anced. An example of one of these questions is given in
Figure 2. The difficulty of the questions chosen was similar.
4.4 Equipment
The eye-tracker we used was the Tobii 1750 [30], which has a
17-inch TFT monitor with a resolution of 1024×768 pixels.
The time measurements of the eye-tracker have a precision
of 0.02 seconds. Hence, all time values are given with an ac-
curacy of two decimals. The eye-tracker was calibrated indi-
vidually for each participant and the light focus was always
in the same position. The distance between the participant
and the eye-tracker was constant (approximately 60 cm. or
24 in.) and controlled by using a fixed chair.
4.5 Procedure
The sessions were conducted at the Universitat Pompeu
Fabra and lasted around 20 minutes. Each session took
place in a quiet room, where only the interviewer (first au-
thor) was present, so that the participants could concen-
trate. Each participant performed the following three steps.
First, we began with a questionnaire that was designed to
collect demographic information. Second, the participants
were given specific instructions. They were asked to read the
12 texts in silence and complete the comprehension control
questions after each text. In answering the question they
could not look back on the text. The reading was recorded
by the eye-tracker. Finally, each participant was asked to
provide his/her preference ratings.
5. RESULTS
In this section, we present the reading performance results
and the preference ratings.
5.1 Reading Performance
A Shapiro-Wilk test showed that nine and eight out of the
twelve data sets were not normally distributed for the Read-
ing Time and Fixation Duration, respectively. Also, a Lev-
ene test showed that none of the data sets had an homoge-
neous variance for both measures. Hence, to study signifi-
cant effects of Font Type in readability we used the Fried-
man’s non-parametric test for repeated measures plus a com-
plete pairwise Wilcoxon rank sum post-hoc comparison test
with a Bonferroni correction that includes the adjustment
of the significance level. To study the effect of the second
level independent variables, Italics,Serif, and Monospace,
we use a Wilcoxon test. For these reasons we later include
the median and box plots for all our measures in addition
to the average and the standard deviation. All this analysis
was done using the R statistical software.
5.1.1 Font Type
Table 1 shows the main statistical measures5for the Reading
Time and Fixation Duration for each of the Font Type con-
ditions. Reading Time and Fixation Duration had a Pearson
correlation of 0.67 and p < 0.001. This is as expected, re-
calling that reading time is the most relevant measure.
Reading Time: There was a significant effect of Font Type
on Reading Time (χ2(11) = 31.55, p < 0.001) (Figure 3).
The results of the post-hoc tests show that:
Arial It. had the longest reading time mean. Par-
ticipants had significantly longer reading times using
Arial It. than Arial (p= 0.011), CMU (p= 0.011),
and Helvetica (p= 0.034).
Fixation Duration: There was a significant effect of Font
Type on Fixation Duration (χ2(11) = 93.63, p < 0.001) (Fig-
ure 4). The results of the post-hoc tests show that:
Courier has the lowest fixation duration mean. Par-
ticipants had significantly shorter fixation durations
reading with Courier than with Arial It. (p < 0.001),
CMU (p < 0.001), Garamond (p < 0.001), Times It.
(p < 0.001), OpenDys It. (p= 0.001), and Arial
(p= 0.046).
Helvetica has the third lowest fixation duration mean.
Participants had significantly shorter fixation dura-
tions reading with Helvetica than with Arial It. (p <
0.001) CMU (p= 0.001), and Garamond (p= 0.006).
– Participants had significantly shorter fixation dura-
tions reading with Arial than with CMU (p= 0.020).
Arial It. had the highest fixation duration mean.
Participants had significantly longer fixation durations
reading with Arial It. than with Courier (p < 0.001),
Helvetica (p < 0.001), Arial (p < 0.001), Times It.
(p < 0.001), Times (p= 0.003), Myriad (p= 0.004),
Garamond (p= 0.011), and Verdana (p= 0.049).
Summarizing, Courier lead to significant shorter fixations
durations than six other fonts and Arial It. lead to signif-
icant longer fixations durations than eight other fonts. In
fact, 16 out of the 66 pairwise comparisons were significant.
5.1.2 Italics
Reading Time: We did not find a significant effect of Ital-
ics on Reading Time (W= 4556, p = 0.09). The visit du-
ration means were ¯x= 32.35 seconds (˜x= 28.77, s = 14.62)
5We use ¯xfor the mean, ˜xfor the median, and sfor the
standard deviation.
a_Arial b_OpenDys c_CMU d_Courier f_Helvetica g_Verdana h_Times i_Times It. j_Myriad k_Garamond l_Arial It.
20 40 60 80
Font Name
Visit Duration Mean (ms)
Arial OpenDys CMU Courier OpenDys It. Helvetica Verdana Times Times It. Myriad Garamond Arial It.
Font Type
Reading Time (seconds)
20 40 60 80
Figure 3: Reading Time box plots by Font Type ordered by average Reading Time.(Lower reading times indicate
better readability.)
Arial OpenDys CMU Courier OpenDys It. Helvetica Verdana Times Times It. Myriad Garamond Arial It.
Font Type
Fixation Duration (seconds)
0.1 0.2 0.3 0.4 0.5
Figure 4: Fixation Duration box plots by Font Type ordered by average Reading Time.(Lower fixation durations
indicate better readability.)
Font Type Reading Time Font Type Fixation Duration Font Type Preferences Rating
˜x¯x±s% ˜x¯x±s˜x¯x±s
Arial 24.22 28.35 ±12.39 100 Courier 0.22 0.22 ±0.05 Verdana 4 3.79 ±0.98
OpenDys 23.81 29.17 ±15.79 103 Verdana 0.22 0.23 ±0.07 Helvetica 4 3.62 ±1.08
CMU 26.06 29.58 ±12.05 104 Helvetica 0.24 0.24 ±0.06 Arial 4 3.60 ±1.13
Courier 29.73 29.61 ±10.87 104 Arial 0.23 0.24 ±0.07 Times 4 3.45 ±1.15
OpenDys It. 25.44 29.68 ±14.44 105 Times 0.24 0.25 ±0.07 Myriad 3.5 3.40 ±0.99
Helvetica 27.18 31.05 ±15.04 109 Myriad 0.25 0.25 ±0.07 CMU 3 3.31 ±0.98
Verdana 28.97 31.16 ±13.03 110 Times It. 0.25 0.26 ±0.06 Courier 3 3.14 ±1.39
Times 29.30 31.68 ±11.81 112 OpenDys 0.24 0.26 ±0.07 Arial It. 3 2.90 ±1.10
Times It. 28.55 32.38 ±12.34 114 OpenDys It. 0.26 0.26 ±0.07 Times It. 3 2.86 ±1.20
Myriad 26.95 32.66 ±14.80 115 Garamond 0.25 0.27 ±0.07 Garamond 2 2.57 ±1.15
Garamond 30.53 33.30 ±15.45 117 CMU 0.25 0.27 ±0.08 OpenDys 3 2.57 ±1.15
Arial It. 29.68 34.99 ±16.60 123 Arial It. 0.28 0.28 ±0.08 OpenDys It. 2 2.43 ±1.27
Table 1: Median, mean and standard deviation of Reading Time and Fixation Duration in seconds as well as the
median, mean, and standard deviation of the Preference Ratings. We include the relative percentage for Reading
Time, our main readability measure, with respect to the smallest average value, Arial.
and ¯x= 29.74 seconds (˜x= 27.04, s = 13.40) for the fonts
in italic and in roman, respectively.
Fixation Duration: There was a significant effect of Ital-
ics on Fixation Duration (W= 8297.5, p = 0.040). In
fact, the fixation duration mean of the fonts in italics (Ar-
ial It.,OpenDys. It., and Times It.), ¯x= 0.27 seconds
x= 0.26, s = 0.08), was significantly larger than the fix-
ation duration mean of the fonts in roman (Arial,OpenDys
and Times), ¯x= 0.25 seconds (˜x= 0.24, s = 0.07).
5.1.3 Serif
Reading Time: We did not find a significant effect of Serif
on Reading Time (W= 11852, p = 0.2021). The visit
duration means were ¯x= 31.53 seconds (˜x= 29.06, s =
13.21) and ¯x= 30.80 seconds (˜x= 27.08, s = 13.83) for the
serif fonts and sans serif font types, respectively.
Fixation Duration: There was a significant effect of Serif
on Fixation Duration (W= 10547.5, p = 0.008). Indeed,
the fixation duration mean of the fonts with serif, ¯x= 0.26
seconds (˜x= 0.25, s = 0.07), was significantly larger than
the fixation duration mean of the fonts sans serif, ¯x= 0.24
seconds (˜x= 0.24, s = 0.07).
5.1.4 Monospace
Reading Time: We did not find a significant effect of
Monospace on Reading Time (W= 3589.5, p = 0.159). The
visit duration means were ¯x= 29.61 seconds (˜x= 29.73, s =
10.87) and ¯x= 31.53 seconds (˜x= 29.06, s = 13.20) for the
monospaced fonts and the proportional fonts, respectively.
Fixation Duration: There was a significant difference of
Monospace on Fixation Duration (W= 4251.5, p < 0.001).
We found that the fixation duration mean of the monospaced
font, ¯x= 0.22 seconds (˜x= 0.22, s = 0.05), was significantly
shorter than the fixation duration mean of the proportional
fonts, ¯x= 0.26 seconds (˜x= 0.25, s = 0.07).
5.2 Preferences Ratings
A Shapiro-Wilk test showed that the twelve data sets were
not normally distributed for the Preference Ratings. Also, a
Levene test showed that none of the data sets had an homo-
geneous variance. Hence, to study the effect of Font Type
in the preferences we use the same analysis of the previous
section.
5.2.1 Font Type
Figure 5 shows the means of the Preference Ratings for each
of the Font Types and in Table 1 we show the main statistical
measures for the participants preferences.
Preference Ratings and Reading Time had a Pearson corre-
lation of -0.13, negative as expected (Table 1). However is
close to 0, which implies that there is almost no correlation
between the reading time and the participants preferences.
There was a significant effect of Font Type on subjective
preference ratings (χ2(11) = 79.6119, p < 0.001). Pairwise
post-hoc comparisons showed significant differences between
the following conditions:
Verdana is significantly preferred over Arial It (p <
0.001), OpenDys (p= 0.002), OpenDys It. (p= 0.004),
Garamond (p= 0.008), and Times It. (p= 0.041).
Helvetica is significantly preferred over OpenDys It.
(p= 0.010), OpenDys (p= 0.020), and Arial It.
(p= 0.031).
Arial was significantly more preferred than Arial It.
(p= 0.028) and OpenDys It. (p= 0.050).
Garamond was significantly less preferred than Ver-
dana (p= 0.008), Times (p= 0.023), Arial (p=
0.023), and CMU (p= 0.030).
Hence, participants significantly preferred Verdana and Hel-
vetica to other fonts and significantly disliked Garamond in
comparison with others.
5.2.2 Fonts Subsets
We did not find a significant difference of Italics on the par-
ticipants preferences (W= 2747.5, p = 1). The preference
ratings mean of the fonts in italics was ¯x= 3.73 seconds
x= 3, s = 1.20) and for the fonts in roman was ¯x= 3.21
seconds (˜x= 3, s = 1.22).
We did not find a significant effect of Serif on the partici-
pants preferences (W= 13030.5, p = 0.999). The preference
ratings mean of the fonts with serif was ¯x= 3.05 seconds
x= 3, s = 1.17) and for the fonts with sans serif was
¯x= 3.46 seconds (˜x= 4, s = 1.17).
We did not find a significant effect of Monospace on the
participants preferences (W= 2574.5, p = 0.789). The
preference ratings means were ¯x= 3.13 seconds (˜x= 3, s =
1.19) and ¯x= 33.14 seconds (˜x= 3, s = 1.39) for the
monospaced and the proportional fonts, respectively.
6. DISCUSSION
First, our results on reading performance provide evidence
that font types have an impact on readability. Second, these
results are consistent with most of the current text design
recommendations for people with dyslexia. Fonts sans serif
and in roman style, lead to shorter fixation durations in our
participants, as recommended in [22]. However, these styles
did not lead to significant shorter reading durations.
Overall, the reading time of the italic fonts was always worse
than its roman counterpart, confirming the commonly estab-
lished fact that cursive letters are harder to read for people
with dyslexia. Although sans serif,monospaced and roman
fonts lead to significant shorter fixation durations, we did
not find a significant difference in reading time. Hence, our
conclusions towards these characteristics are weaker.
Although Arial is highly recommended in literature [2, 10,
22] and had the shortest reading time, we cannot conclude
● ●● ●
a_Arial b_OpenDys c_CMU d_Courier f_Helvetica g_Verdana h_Times i_Times It. j_Myriad k_Garamond l_Arial It.
12345
Font Name
Preferences
Arial OpenDys CMU Courier OpenDys It. Helvetica Verdana Times Times It. Myriad Garamond Arial It.
Font Type
Preferences
2 3 4 5 1
Figure 5: Subjective Preference Ratings box plots depending on the Font Type (by average Reading Time order).
Arial
Arial It.
CMU
Courier
Garamond
Helvetica Verdana
Times
Open Dys l exic
OpenDyslexic It Times It.
Myriad Arial
Arial It.
CMU
Garamond
Helvetica Verdana Times
Open Dys l exic
OpenDyslexic It Times It.
Arial
Arial It.
CMU
Helvetica
a) b)
c)
Figure 6: Partial order obtained from the means order of Reading Time and Preference Ratings (a), and the
partial order for the significant differences in Reading Time (b) and Preference Ratings (c).
that this font type leads to better readability because we
only found significant differences with respect to OpenDys
It. and Arial It. However, Arial It. did lead to significant
longer reading times than Helvetica,Arial, and CMU and
significant longer fixation durations than most of the fonts.
Hence, we recommend to avoid using Arial It. Moreover,
participants significantly preferred Arial to Arial It.
The two fonts that lead to shorter fixation durations than
other fonts were Courier and Helvetica. Hence the use of
these fonts might help people with dyslexia to read faster.
This is consistent with the recommendation of [1] to use
Courier and with [22] to use sans serif fonts in the case of
Helvetica. Also, Helvetica was the second most significantly
preferred font by our participants after Verdana.
The fonts designed specifically for dyslexia, OpenDys and
OpenDys It., did not lead to a better or worse readability. As
in [21], OpenDys did not lead to a faster reading. However,
we did not performed a reading out loud test with words,
which is what might improve with the use of specially de-
signed fonts [21]. In addition, our participants significantly
preferred Verdana or Helvetica for reading than OpenDys
and OpenDys It.
One way to understand these results is to build the partial
order obtained by considering all the order relations that are
valid for the average values in Reading Time and the Prefer-
ence Ratings. The result is given in Figure 6 (a), where the
fonts can be grouped in four different levels. However, not
all of these order relations are significant. Hence, the partial
orders at the right, (b) and (c), show the significant relations
for Reading Time and Preference Ratings, respectively. In
the case of (b), the wider relations show the fact that those
are also significant for Fixation Duration. From these partial
orders, the only three fonts that are not dominated in both
partial orders, (b) and (c), are Helvetica,CMU, and Arial.
These can be considered good fonts for dyslexia when we
also consider the subjective preferences of the participants.
The next two in importance are Verdana and Times.
7. CONCLUSIONS AND FUTURE WORK
The main conclusion is that font types have an impact on
readability of people with dyslexia. Good fonts for peo-
ple with dyslexia are Helvetica,Courier,Arial,Verdana and
CMU, taking into consideration both, reading performance
and subjective preferences. Also, sans serif,monospaced,
and roman font types increased significantly the reading per-
formance, while italic fonts decreased reading performance.
In particular, Arial It. should be avoided since it signifi-
cantly decreases readability.
These findings can have impact on systems that rely on text
as the main information medium, such as browsers, PDF
viewers, or eBook readers. We plan to integrate these find-
ings in the IDEAL eBook Reader6[19], and in the web ser-
vice Text4All.7The last two tools modify text layout for
people with dyslexia. Using fonts that are good for people
with dyslexia improves the accessibility for a large percent-
age of the population and should not impact other people.
Hence, the fonts we propose should be used in practice.
Future challenges involve studying the effect of the font
types on the comprehension and in different contexts and
devices. We also want to do the same analysis with people
without dyslexia.
Acknowledgments
This research was partially funded by the Spanish Ministry
of Education and Science (Grant TIN2009-14560-C03-01).
The research of the first author was also funded by the
Catalonian FI scholarship program. We also thank Mari-
Carmen Marcos for her assistance with the eye-tracker hard-
ware and Martin Pielot for his help with statistics.
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En este trabajo presentamos un procedimiento secuenciado para la detección de las dificultades lectoras en una muestra representativa de la población escolar constituida por el alumnado de 2º, 4º y 6º de primaria (N=2012), escolarizado en todos los centros públicos (14) y concertados (5) de un mismo municipio. En la primera fase, un test colectivo de lectura (Test de Eficiencia Lectora TECLE) nos permitió identificar 237 escolares con retraso lector, no explicado por la presencia de otros trastornos (cognitivo, sensorial, conductual, lingüístico, social, etc.). En la segunda fase se aplicaron pruebas de lectura (palabras y pseudopalabras) y de ortografía (palabras con correspondencias fonema-grafema inconsistentes) para seleccionar los casos con retraso lector asociados a dificultades en los mecanismos fonológico y/u ortográfico de base. Los resultados muestran mayor incidencia del retraso lector en 2º curso de primaria (15.2 %) frente a la encontrada en 4º (9.3 %) y 6º (10.9 %). Esta diferencia puede ser explicada por la inclusión en 2º de alumnos cuyo retraso podría desaparecer sin una intervención especifica. Las dificultades globales de lectura establecidas con el Test de Eficiencia Lectora TECLE se explican en gran parte por dificultades más básicas en descodificación y ortografía.
Article
The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
Conference Paper
We report from an eye-tracking experiment with 104 participants who performed reading tasks on the most popular text-heavy website of the Web: Wikipedia. Using a hybrid-measures design, we compared objective and subjective readability and comprehension of the articles for font sizes ranging from 10 to 26 points, and line spacings ranging from 0.8 to 1.8 (font: Arial). Our findings provide evidence that readability, measured via mean fixation duration, increased significantly with font size. Further, comprehension questions had significantly more correct responses for font sizes 18 and 26. For line spacing, we found marginal effects, suggesting that the two tested extremes (0.8 and 1.8) impair readability. These findings provide evidence that text-heavy websites should use fonts of size 18 or larger and use default line spacing when the goal is to make a web page easy to read and comprehend. Our results significantly differ from previous recommendations, presumably, because this is the first work to cover font sizes beyond 14 points.
Article
Objective: To report the incidence of reading disability among school-aged children. Subjects and Methods: In this population-based, retrospective birth cohort study, subjects included all 5718 children born between 1976 and 1982 who remained in Rochester, Minn, after the age of 5 years. Based on records from all public and nonpublic schools, medical facilities, and private tutorial services and on results of all individually administered IQ and achievement tests, extensive medical, educational, and socioeconomic information were abstracted. Reading disability was established with use of research criteria based on 4 formulas (2 regression-based discrepancy, 1 non-regression-based discrepancy, and 1 low achievement). Results: Cumulative incidence rates of reading disability varied from 5.3% to 11.8% depending on the formula used. Boys were 2 to 3 times more likely to be affected than girls, regardless of the identification methods applied. Conclusions: In this population-based birth cohort, reading disability was common among school-aged children and significantly more frequent among boys than girls, regardless of definition.
Article
The way in which a text is written can be a barrier for many people. Automatic text simplification is a natural language processing technology that, when mature, could be used to produce texts that are adapted to the specific needs of particular users. Most research in the area of automatic text simplification has dealt with the English language. In this article, we present results from the Simplext project, which is dedicated to automatic text simplification for Spanish. We present a modular system with dedicated procedures for syntactic and lexical simplification that are grounded on the analysis of a corpus manually simplified for people with special needs. We carried out an automatic evaluation of the system’s output, taking into account the interaction between three different modules dedicated to different simplification aspects. One evaluation is based on readability metrics for Spanish and shows that the system is able to reduce the lexical and syntactic complexity of the texts. We also show, by means of a human evaluation, that sentence meaning is preserved in most cases. Our results, even if our work represents the first automatic text simplification system for Spanish that addresses different linguistic aspects, are comparable to the state of the art in English Automatic Text Simplification.