Quantitative Analysis of Reading Comprehension and Reading Speed Based on Serif and Sans-Serif Fonts

Taylor Burke

Clemson University tdburke@clemson.edu

John Welter Clemson University

jcwelte@clemson.edu

Abstract

Our work investigates the effect of using the two general catego-ries of fonts, serif fonts and sans-serif fonts, on the rate at which a person reads and on how much of the material a person com-prehends. We have conducted an experiment in which each par-ticipant is given two articles, each using a different font, and asked to answer a short questionnaire between each article. After analyzing the data, we have come to the conclusion that serif vs sans-serif fonts produce no notable effects on reading speed or comprehension.

Keywords: reading; reading speed; serif; sans-serif; font; com-prehension

1 Introduction

When people read, whether it be by computer, newspaper, or book, words are usually displayed in one of two broad categories of fonts – serif fonts, and sans-serif fonts. Traditionally, serifs were said to be used in an attempt to help the horizontal flow of reading in conjunction with the smooth movements of the hu-man eye across a page, thus improving comprehension [1]. However, due to the spontaneous saccadic movements our eyes make in every moment, it is difficult to ascertain the validity of such a claim. Some say that sans-serif fonts take out complexity of lettering, thus making it easier for the eye to naturally distin-guish between letters. Others, however, claim that the complexi-ty of serif fonts makes it easier for the eye not to perceive the letters, but rather to distinguish similar letters from each other (for instance, when using a sans-serif font, a lower-cased L and an upper cased I look identical, whereas serif fonts allow the eye to distinguish between the two characters) [2].

Because reading is a fundamental part of our everyday lives, diving into some of the specificities of how we actually read can be intriguing. Does the style of font actually affect our ability to comprehend reading material? Could it also affect the speed at which we read? These are the two fundamental questions our work intends to answer. Furthermore, using the Gazepoint GP3 eye tracker, we will not only be able to attempt to answer these questions, but also obtain insight into the potential differences in eye movements that naturally may occur when reading passages written in different fonts.

People often prefer to use one font style over the other. Some, for instance, enjoy reading articles printed in sans-serif fonts because they seem easier on the eyes to me due to their simplici-ty. On the contrary, others may prefer serif fonts because they are aesthetically pleasing over long periods of time. Because individuals may have these preferences, preference may play a key role in the potential difference in reading performance. Nev-

ertheless, our hypothesis is that neither serif fonts nor sans-serif fonts have any pronounced difference on performance.

2 Background

Many studies have been done regarding eye movement and read-ing, such as the effect of reading out loud on fixations [3], and the comprehension of reading annotated passages [4]. While they studied various reading strategies, they never studied the effect the text style had on the reading itself. Cheng et. al came close with the annotated text, guiding reading with shaded box-es. Research has been done in regards to serif v. sans-serif study, but many methods and papers have been flawed [5, 6, 7]. One study determined that more than the font, things like size and color contrast have a greater effect on legibility [8]. However, there has never been any evidence regarding which type of font is better. In our experiment, we intend to observe for ourselves the potential impact.

3 Methodology

Apparatus

For this work, we used the Gazepoint GP3 Eye Tracker, a classic pupil/corneal reflection tracking device. The GP3 was mounted to a 22” DELL P2213t monitor. Gazepoint, the eye tracker manufacturer, claims accuracy within 0.5 to 1.0 degrees, and reads data at a rate of 60Hz.

Participants were seated at the desk and asked to move roughly 15-20 inches away from the monitor. Because this study is not primarily focused on exactly where participants are looking, and rather objectively how long they view a certain general area in the text (to determine at what point they finish reading the text and get a general idea of reading speed across the articles), the use of a chin rest or other such restraint was unnecessary. The eye tracker was calibrated using the default 5-point calibration test using Gazepoint’s included software.

Stimuli

The stimuli for our experiment are 4 images of two spate arti-cles, written in both serif an sans serif fonts. Both articles come from Wikipedia. Article A describes a laughter epidemic in Uganda, while Article B describes the informal Waffle House Index. The articles were chosen based on the assumption that they are not general knowledge, and would therefore lessen the chance of a participant having prior knowledge of the subjects. Furthermore, both articles are easy to understand. The serif im-ages are written in 29 pt. Times New Roman, while the sans serif images are written in 27.5 pt. Arial.

Figure 1 Group 1’s stimuli: serif article A, sans-serif article B

Figure 2 Group 2’s stimuli: sans-serif article A, serif article B

Subjects

To ensure some consistency with the experiment itself and to prevent large variances that naturally occur from person to per-son, we opted to do use a within subjects approach. Our primary subjects were university students at Clemson University. In our study, we have two groups of participants; participants in one group receive a sans-serif version of article A and a serif version of article B, and participants in the other group receive a serif version of article A and a sans-serif version of article B. Each group is composed of 10 participants. Subjects were Clemson University students between the ages of 19 and 29.

Experimental Design

The design of this experiment follows a 2x2 pattern, since there are two versions of two different stimuli. To reduce variance between each individual and to increase reliability, we opted to test within subjects rather than between subjects; each partici-pant will read an article displayed in a serif font followed by an article in sans-serif font, or vice versa. Each participant uses the Gazepoint GP3 system for the study. For the purposes of gather-ing line-by-line data regarding the time each participant spends reading, each line of each article is an independent area of inter-est (AOI).

Because we are not so concerned with pinpoint accuracy with the eye trackers and instead use them to get a general idea of where our participants are looking at any given time, devices such as chin rests to restrain stray head movement are not used.

After each article, participants are given short comprehension quizzes consisting of four multiple choice questions regarding the contents of the article. The questions cover specific infor-mation such as dates or names, as well as more general facts.

Procedures

After greeting the participant and gathering demographic infor-mation, we seat him in front of the testing monitor. We then guide him through the 5 point calibration process. Next, we expose him to the first stimulus. The participant may read at his own pace without a time limit. After he finishes reading, he is given a short quiz on the material read. Afterwards, the eye tracker is recalibrated, and the participant is exposed to the sec-ond stimulus. After reading the second stimulus, the participant asked to complete a second quiz. He is thanked for his time and dismissed.

4 Results

In total, participants performed 2*2*10 = 40 trials, of which all analyzed. Using the CSV files exported from Gazepoint and the graded test results, we were able to gather quantitative data re-garding reading speed and comprehension. Results were calcu-lated using a 90% confidence interval for the population mean. Scan paths were created for qualitative analysis by proprietary functions in Gazepoint.

Reading Speed

In order to gauge the effect on reading speed, it was first neces-sary to calculate the total time each participant spent reading the article. In order to find a participant’s total reading time, the total times spent in each AOI were added together. Using Minitab 17 statistical analysis software’s ANOVA One-Way

plugin, we generated data comparing the average total reading speed of participants between sans-serif and serif articles. Fig-ures 3.1 and 3.2 summarize the overall means.

Figure 3.1 Comparison of times between conditions of article A

Figure 3.2 Comparison of times between conditions of article B

Ultimately, these results are evidence that there is no correlating effect on reading speed between sans-serif and serif fonts (Arti-cle A: P=0.453; Article B: P=0.295).

Reading Comprehension

In order to gauge the effect on reading comprehension, it was first necessary to calculate the average score of each participant on each of their tests. Using Minitab 17 statistical analysis soft-ware’s ANOVA One-Way plugin, we generated data comparing the average total score of participants between sans-serif and serif articles. Figures 4.1 and 4.2 summarize the overall means.

Figure 4.1 Comparison of test scores between conditions of article A

Figure 4.2 Comparison of test scores between conditions of article B

Similar to the speed comparisons, these results seem to imply that there is no correlating effect on reading speed between sans-serif and serif fonts (Article A: P=0.211; Article B: P=0.691).

5 Discussion

Reading Speed vs. Comprehension results

It is interesting to note what appears to be a strange and contra-dictory correlation between the results of the reading speed analysis and the comprehension analysis within our sample. Where one would believe a longer reading time would denote a higher score, since it indicates more focused reading, the results within our sample happened to be the exact opposite. In figure 5.1 and 5.2, we show two scan paths from group B. The first shows a reader who skimmed the articles and made an average score of 75 on both tests, while the second shows a reader who read the article twice over and made an average score of 25 on both tests. Furthermore, average reading speed within our sam-ple seemed to be entirely unrelated to font style, since the aver-age reading time taken seemingly differs between articles A and B. While these certainly do not have any lasting value (since the P-values are so high), they do help point to the null hypothesis that it doesn’t matter which font style is used.

Overall, due to the incredibly high P-values and margin of error for our means, we believe this is evidence that there is little, if any, difference between comprehension and/or reading speed when using a serif or sans-serif font.

Figure 5.1 Scan path of a participant in group B who scored a 75 on this article’s quiz. Notice how the first half of the article is

seemingly ignored. (Reading time: 13s)

Figure 5.2 2-part scan path of a participant in group B who scored a 25 on this article’s quiz. Notice how they look back for

relevant information. (Reading time: 60s)

Reading Speed vs. Scan Paths

Another interesting note is the small difference in the shape, spacing, and fixations-per-line of the scan paths between partici-pants. Though some scan paths varied greatly from others (such as the examples in figure 5), scan paths mostly followed the

same general figure. Figure 6.1 and 6.2 demonstrate this, show-ing two participants’ scan paths whose reading times have a difference of greater than 20 seconds.

Figure 6.1 a fast reading participant’s scan path

Figure 6.2 a slow reading participant’s scan path

Possible improvements

Due to a small sample size, short questionnaire, and only testing one font per condition, we believe that the experiment could be improved upon to create more telling, concrete results. More participants would significantly narrow down the margin of error of the results and would be ideal, as well as having a more comprehensive questionnaire with a wider range of potential scores. The Gazepoint tracker itself is good for basic analysis, but more precise tracking devices could provide deeper insight into the possible effect of fonts on eye movement and fixations, since 1 degree is often enough to shift the assumed focal point of the participant up or down an entire line of text.

Future Work

While the effect of serifs on reading is still hard to determine, the idea of reading speed and comprehension is a wide topic with many possible testable variables. For instance, a possible

experiment could involve testing how a speed reader’s eyes move across a page as opposed to a person who simply skims a passage. The gaze data produced from this experiment could also be used as a means of modeling eye movements for use in creating more realistic 3D animations.

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