Next Article in Journal
Infrared Image Detection and Recognition of Substation Electrical Equipment Based on Improved YOLOv8
Previous Article in Journal
Human-Centered AI for Migrant Integration Through LLM and RAG Optimization
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 15
Issue 1
10.3390/app15010326
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Eye-Tracking Study on Reading Fluency in Relation to Typeface Pleasantness Influenced by Cross-Modal Correspondence Between Taste and Shape

by
Tanja Medved
1,*,
Anja Podlesek
2 and
Klementina Možina
1
1
Faculty of Natural Sciences and Engineering, University of Ljubljana, SI-1000 Ljubljana, Slovenia
2
Faculty of Arts, University of Ljubljana, SI-1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(1), 326; https://doi.org/10.3390/app15010326
Submission received: 20 November 2024 / Revised: 18 December 2024 / Accepted: 23 December 2024 / Published: 31 December 2024
Browse Figures
Versions Notes

Abstract

:
Reading fluency depends on the typographic design. Letters can have different shapes that evoke different feelings in the reader and influence reading fluency. Previous studies that explored the link between typeface shape and taste and its impact on reading and readers’ attitudes mainly focused on shorter texts or individual words. In contrast, our study investigated how the taste (sweetness) attributed to the typeface is related to reading fluency and the pleasantness of the typeface during reading longer texts, and whether these relationships are the same in children and adult readers. We found that readers of both age groups perceived rounded letters as sweeter than angular letters. The perceived sweetness correlated positively with the pleasantness of the typeface and reading fluency. Younger readers showed a higher general rating of sweetness and a stronger relationship between the perceived sweetness and the pleasantness of the typeface than older, more experienced readers. This suggests that the sweeter and more pleasant the typeface is perceived to be, the faster it can be read. When fast processing of longer texts is required, we recommend the use of rounded typefaces with more organic shapes, including serif typefaces with some characteristics of old-style typefaces, rather than using angular, sans serif typefaces.

1. Introduction

Typographic design, especially the shape of typefaces, plays a crucial role in reading as it influences both perception and cognitive processing during reading as well as the reader’s mood by affecting their emotional response and sense of pleasantness when interacting with certain letterforms [1,2,3].
The shape of letters and typography as a whole have a direct impact on text legibility [1,2,3], clarity of the information presentation [4,5], and reading fluency [6,7,8,9,10,11]. Typography can also affect the comprehension of content [12], which has been identified as an important aspect of reading fluency [13,14], alongside letter recognition and reading speed [15,16]. Reading fluency is influenced by various typographic factors, including type size [17,18], typeface shape, legibility [11,19,20], overall typographic design [21], and resolution when reading on a screen—higher resolutions enable a more precise rendering of letters and better reading fluency [6,22,23].
Poor reading fluency hinders information processing and weakens comprehension [24,25,26,27,28,29,30,31,32]. Reading fluency influences the learning process [33] and metacognition [34,35]. Research on difficult-to-read typefaces, which some claim to introduce a “desirable difficulty”, such as Sans Forgetica, has mostly found no benefits for comprehension, memory, or even negative effects [36,37,38,39,40]. However, some studies suggest that a more challenging reading experience can enhance processing and recall [29,41,42,43,44]. Typography can also provide clues about the type and content of a text [22,45,46,47,48,49,50], allowing readers to estimate the time needed to read it [8,51]. Better reading fluency generally leads to a more positive attitude toward the text and better comprehension. On the other hand, poorer fluency can lead to a negative attitude, as readers expect to spend more time with a text [29,52,53,54,55,56].
Age is an important factor in reading fluency. Children and adults differ in their cognitive and physiological abilities up to about the fourth grade, after which their letter recognition skills align [57]. For younger readers, typefaces with serifs and varying stroke widths promote more fluent reading [7], while sans serif typefaces with minimal stroke variation lead to fewer errors [58]. Children also benefit from varied letter shapes [58,59], especially children with visual impairments [7]. However, the effect of typography on reading fluency may not be the same for younger (less experienced) and older (more experienced) readers. Research suggests that increasing the desired difficulty level of a typeface can improve reading fluency in adults but may have a negative effect on children [60]. Larger type sizes improve the decoding speed and memory retention in children, but not in adults [59].
Typographic design, especially the shape of typefaces, plays a crucial role not only in the cognitive processing of a text and reading fluency but also in the reader’s mood by influencing their emotional response and sense of pleasantness when interacting with certain letterforms [61,62,63]. Perceptual studies have shown that shapes, tastes, and sounds can evoke certain emotions, including pleasure [46,61,62,63,64,65,66,67,68,69]. Rounded and symmetrical shapes trigger more positive feelings than angular or asymmetrical ones [70,71]. Due to cross-modal perception, different sensory modalities are often associated with each other, although these associations may vary across cultures [72,73,74,75,76,77]. For example, round shapes are associated with sweetness, while square, angular shapes are associated with bitterness and sourness [71,78,79,80,81]. Since sweetness is often associated with pleasantness [80,82], round shapes tend to evoke pleasant feelings [83,84,85]. This concept is widely used in marketing and packaging design [79,86,87]; however, its use in typography for longer texts is still relatively unexplored. The available research suggests that the general effects of shape on emotions can also be applied to this area. Rounded, organic shapes with softer transitions are perceived as more pleasant, while geometric strokes and sharp transitions are perceived as less pleasant [74,88]. The enjoyment of reading different typefaces can influence motivation, focus [21,89], comprehension, and recall [89]. However, there is little research on the relationship between the emotional responses to letter shapes and reading fluency.
This study had two main aims: (1) We aimed to investigate how letter shape influences the perceived sweetness and, consequently, the pleasantness of typefaces. Additionally, we sought to examine how this cross-modal correspondence between shape and taste impacts reading fluency, measured by reading speed, and reading comprehension. Based on previous studies, we anticipated a cross-modal correspondence in the perception of typefaces, such that typefaces with round/rounded shapes would be perceived as sweeter compared to those with angular/pointed shapes. We also hypothesised that round/rounded typefaces would be easier to read than angular/pointed ones. (2) In addition, we wanted to investigate whether the relationship between the perceived sweetness and pleasantness of a typeface and reading fluency differs between younger readers with less experience in reading longer texts and adult, more experienced readers. Previous studies have shown that changing the characteristics of typefaces affects children and adults differently [59,60]. Children also respond differently to colours, shapes, tastes, and smells than adults [90,91]. For this reason, we wanted to compare the relationships between reading fluency and emotional responses to different typefaces in these two groups of readers.

2. Materials and Methods

2.1. Participants

Eighty-eight participants took part in this study during the COVID-19 pandemic. We divided them into two age groups, namely university students and elementary school students. The first age group was composed of 36 university students between 19 and 25 years of age with a mean age of 19.9 years (SD = 1.4); 22 of them were female and 14 were male. The second age group comprised 49 (28 female and 21 male) 4th to 6th grade elementary school students aged 10 to 12 years, with an average age of 10.9 years (SD = 0.6). We chose children of this age because they are already fluent readers and can read longer texts (according to Chall [92], they entered the developmental stage of reading for learning), but they are not yet experienced readers like university students who can be considered expert (adult) readers (who have reached the construction and reconstruction stages of reading skills) [92].
All participants had normal or corrected-to-normal vision and received no payment for their participation in the study. This study was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from the participants or their parents/guardians prior to participation in this study.

2.2. Stimuli

Before the main study, we conducted two preliminary studies, which are presented in detail in our 2023 publication [2]. In the first study, we selected the texts for the main study. From various excerpts from textbooks and children’s encyclopaedias, we selected 10 texts with 459–509 characters that had comparable content complexity and led to a similar reading fluency. The selected texts provided the highest and most homogeneous reading speed. We also analysed the number of fixations for each text as an additional indicator of reading fluency. The fewer the fixations, the more fluently participants read the text. The texts appeared to be content-wise comparable and suitable for fluent reading by a broader population, including both 4th to 6th graders and adults, and did not include distracting elements such as overly long or complex words and unclear content. We hypothesised that the selected texts would induce a similar cognitive load, as they had comparable content difficulty, similar reading speeds, and a comparable number of fixations. In the second study, we selected the typefaces for the main study.
We categorised typefaces into two groups based on the shape of their main strokes, transitions, and stroke ends (serifs). Typefaces can be described based on their shape characteristics: the form of main (especially rounded) strokes, transitions between strokes, and stroke endings, categorising them as either round/rounded or angular/pointed. Round/rounded typefaces included those with letters that have softer or more organic shapes—forms that resemble natural shapes such as waves, curves, and shapes found in the natural environment. On the other hand, angular/pointed typefaces include those with letters of a more technical design, featuring more angular and sharp forms. Typical typefaces that could be classified as round/rounded include typefaces with characteristics of venetian, garalde, and transitional typefaces [93,94]. Typefaces that could be classified as angular/pointed include some typefaces with characteristics of didone, slab serif, and sans serif typefaces [93,94].
The shape of letters significantly impacts the reader’s mood, specifically their emotional response or the sense of pleasantness they feel when reading certain letter shapes [21,95,96,97]. Previous research [74,81,82,88] has shown that letters with softer or more organic stroke shapes and smoother transitions between strokes and their endings are perceived as more pleasant and are, through multimodal perception, associated with a sweet taste. Letters that are more geometric in shape and have sharper transitions between strokes and their endings are perceived as less pleasant and are not as strongly associated with a sweet taste through multimodal perception. Figure 1 shows two examples of round/rounded typefaces, while Figure 2 shows two examples of angular/pointed typefaces. The term “rounded” or “angular” refers to the round shapes of counters, bowls, lobes, and loops, while “rounded” or “pointed” refers to the transitions between strokes, serifs, and stroke endings and the overall shape of the strokes—stems, crossbars, diagonals, etc.—which in some typefaces (i.e., FG April) are curved rather than straight (as in Verdana).
In the second preliminary study, we selected ten typefaces to be analysed (Figure 3). The five most appealing typefaces were Chaparral Pro, Comic Sans, FG April Trial, Matilda, and Times New Roman, and had the characteristics of round/rounded shapes, while the five least appealing typefaces had the characteristics of angular/pointed shapes, i.e., Arial Nova, Anka, Nogomet, Sans Forgetica, and Verdana.
Each text was set in one of the typefaces. The type size was adjusted to achieve as uniform an x-height as possible for all typefaces, which varied between 0.17 and 0.20 degrees of visual angle. The average x-height was 0.19 degrees of visual angle (SD = 0.01). Due to the different shapes of letters, the number of lines in various texts varied between 10 and 11, with the average number of lines being 10.30 (SD = 0.48). In all cases, the line spacing was 140% of the type size.

2.3. Apparatus and Instruments

We used eye-tracking technology to objectively measure reading fluency. We used a Tobii X120 (Stockholm, Sweden) eye-tracking system in combination with Tobii Studio 3.4.8 software [98] (which was available at the time of our study) to monitor the participants’ eye movements. The device works by detecting the reflection of infrared light on the cornea. Infrared emitters on the front of the device project specific IR light patterns, which are then reflected by the cornea. An inbuilt infrared-sensitive camera captures these reflections, enabling the tracking of both the movement and fixation of the eyes [98]. Before starting the measurements, participants were given five minutes to adjust to the lighting conditions in the test environment. Each participant also underwent a five-point screen-based calibration procedure. The experiment was conducted using an LCD with a resolution of 2400 × 1900 pixels (0.27 mm pixel size) and a refresh rate of 60 Hz.

2.4. Procedure

The measurements with a group of university students were conducted in a quiet room with walls painted with grey matte paint in accordance with the ISO 3664 standard [99]. Due to coronavirus restrictions, we could not test children in the visual science laboratory; hence, we set up a comparable test room in their elementary school, which was a bright room with artificial lighting.
The letters of the texts that the participants read on the screen were dark on a light background (text colour: #000; background colour: #eee) in accordance with the ISO 12646 standard [100]. The participants were at a distance of 60 cm ± 1 cm from the screen, in line with the recommendations of the ISO 9241-303 standard [101]. Their movements were not restricted by any method; however, they were asked to remain in a still position.
To account for the potential effects of fatigue, the texts were presented to each participant in a unique sequence created by the Latin square method. The order in which the texts were read varied for each participant, ensuring that no specific text consistently appeared at the same point in the sequence, which might have otherwise influenced the results due to fatigue. We measured the reading speed and the length of fixations for all participants during the entire reading time.
After the participants read the text on the screen, they answered an additional question to check their understanding of the text content. They had to select the correct answer from three possible alternatives. They also used two 5-point scales to rate the pleasantness (1—very unpleasant; 2—unpleasant; 3—neutral; 4—pleasant; 5—very pleasant) and perceived sweetness (1—not sweet at all; 2—slightly sweet; 3—sweet; 4—quite sweet; 5—very sweet) of the typeface used to display the text. Before rating the typefaces, participants received brief instructions to rate the typefaces based on their intuition or first association. When rating pleasantness, they were asked to consider the feeling they experienced while reading each typeface. For the sweetness evaluation, they were instructed to answer the following question: “What level of sweet taste would you assign to the shape of the letters?”.

2.5. Data Analysis

We considered the ratings of pleasantness and sweetness as subjective measures of emotional response to typefaces. Reading speed and text comprehension were analysed as indicators of reading fluency.
The data were analysed using linear mixed modelling. For each person (level-2 unit of analysis), different data were collected on ten typefaces (level-1 unit of analysis), i.e., ratings of pleasantness, ratings of sweetness, reading speed, and text comprehension. In all models, data were nested within participants. Intercepts were considered random coefficients, and slopes were considered fixed across all participants.
In the first model, we investigated the relationship between the ratings of typeface sweetness and pleasantness to ensure that higher perceived (imagined) sweetness corresponds to more pleasant feelings, as expected from the literature on cross-modal interactions. Typeface pleasantness was predicted based on typeface sweetness (entered into the model as an interval predictor, i.e., level-1 covariate; the values were centred within individuals). To account for possible differences between children and adults in the strength of the relationship between typeface pleasantness and sweetness, we also included the age group as a level-2 factor (a factor with two levels, i.e., 0—elementary school students; 1—university students) in this model.
In the second model, we analysed the relationship between the typeface shape and its perceived sweetness in different age groups to assess the cross-modal interaction between shape and taste in the perception of typography. Typeface shape (round/rounded vs. angular/pointed) and age of participants (children vs. adults) were included as level-2 factors in the model. The rating of sweetness was considered an outcome variable.
In the last two models, we analysed the relationship between the rating of sweetness and two measures of reading fluency. The sweetness of the typeface was used as a level-1 covariate, while the reading speed and text comprehension were used as outcome variables. For the text comprehension analysis, we used a mixed-effects logistic regression, as the outcome variable was binary.

3. Results

Figure 4 and Table 1 show how the ratings of the sweetness of a typeface were related to the ratings of the pleasantness of a typeface. According to the literature, we expected that typefaces rated as more pleasant would also be rated as sweeter. The results show a statistically significant correlation between the rating of the sweetness of the typeface and the rating of its pleasantness. There was a statistically significant interaction between the age group and the rating of sweetness—the relationship between sweetness and pleasantness was slightly stronger in elementary school students (children) than in university students (adults). In general, age per se was also a statistically significant predictor of pleasantness ratings, with children using slightly higher pleasantness ratings than adults. An inspection of the random effects in the model showed that the between-subject variance (0.02) was much smaller than the within-subject variance (1.16). The intraclass correlation coefficient was small (ICC = 0.02) and adding random intercepts did not improve the model fit significantly (LRT(1) = 1.19, p = 0.276). These results indicate that there was very little variation in the ratings of typeface pleasantness between individuals of the same age. On average, children rated the typefaces very similarly, as did adults. However, different typefaces were rated with significant differences in pleasantness—meaning typefaces with different shapes received varying pleasantness ratings.
Next, we examined the cross-modal correspondence between typeface shape and perceived taste. Adding random intercepts improved the model fit significantly (varbetween subjects = 0.17, varwithin subjects = 1.41, ICC = 0.107, LRT(1) = 28.7, p = < 0.001), indicating that the differences in sweetness ratings across individuals (e.g., due to personal preferences or individual biases) needed to be taken into account when modelling the data. The large within-subject variance nevertheless suggests that typefaces were perceived as different in their sweetness. Figure 5 and Table 2 show how typeface shape predicted readers’ imagined sweetness ratings. Typeface shape and age group were found to be statistically significant factors for sweetness ratings, while no significant interaction was found between the two factors. Both younger and older readers rated round/rounded typefaces as sweeter compared to angular/pointed typefaces. In general, elementary school students rated sweetness higher than adults.
Finally, we analysed the relationship between the ratings of typeface sweetness and two indicators of reading fluency in both age groups (Figure 6, Table 3 and Table 4). Accounting for the between-subject differences by adding random intercepts in the model for predicting the reading speed improved the model fit significantly (varbetween subjects = 739, varwithin subjects = 232, ICC = 0.761, LRT(1) = 913, p < 0.001). There were large differences in reading times between individuals of the same age. Meanwhile, the between-subject variance in text comprehension was low (varbetween subjects = 0.00, varwithin subjects = 1.00, deviance = 586.1, χ2/df = 1.01, p = 1.00). Concerning the fixed effects in the models, there was no interaction between the age group and the sweetness of the typeface in the prediction of the reading speed (Table 3) and the prediction of text comprehension (Table 4). The relationship between the ratings of typeface sweetness and reading speed or text comprehension was therefore similar for younger and older readers. The sweetness of the typeface had a statistically significant relationship with the reading speed, an indicator of reading fluency—the sweeter the typeface, the shorter the reading time per character (Table 3, Figure 6A). The relationship between the rating of the sweetness of the typeface and text comprehension did not reach statistical significance (Table 4), although a similar trend was observed—the higher the rated sweetness, the slightly better the text comprehension (Figure 6B). A clear and statistically significant effect of age group on both reading fluency and text comprehension was also observed—elementary school students read more slowly than university students and showed poorer text comprehension, which was to be expected as they are less experienced readers, and their cognitive abilities are less developed.

4. Discussion

The following sections present the findings of our study, focusing on the relationship between typeface shape and reading outcomes. This research explored how cross-modal correspondences between typeface shapes and taste (specifically sweetness) influence perceived pleasantness, reading fluency, and text comprehension. This analysis was conducted across two age groups—children (elementary school students) and adults (university students)—to examine potential differences in their perception and performance.
By integrating subjective ratings (sweetness and pleasantness ratings) with objective indicators of reading fluency (reading speed and text comprehension), our study provides a more comprehensive insight into cognitive and emotional processes involved in reading. In this section, we address the role of typeface shape in facilitating reading fluency, the limitations of this study, and suggestions for future research directions.

4.1. Cross-Modal Correspondence Between Typeface Shape and Taste (Sweetness)

Typefaces of round/rounded shapes were rated as sweeter than typefaces with pointed/angular shapes. In addition, typefaces that were rated as sweeter were also rated as more pleasant for the reader. It is known that the sweet taste typically evokes pleasant feelings [81,85], as does a round or rounded shape [83,84,85]. Our results support the notion that shape can be associated with taste [72,73,74,75,76], specifically that round or rounded shapes are associated with a sweet taste, while angular or pointed shapes are associated with a bitter and sour taste [78,79,80,81,82]. Cross-modal correspondence between shape and taste thus also takes place in typography.
For younger readers, the correlation between the sweetness and pleasantness of the typeface was stronger than for older readers. Younger readers also rated the sweetness of typefaces higher on average than adults. The reason for these results is not clear. Several other studies have also shown that children respond to colour, shape, taste, and smell differently than adults [90,91], and that the characteristics of typefaces affect children and adults differently [59,60]. It could be that children tend to emphasise the differences between pleasant and unpleasant shapes more strongly compared to adults. It could also be that the children were more motivated to participate in our study since they were exposed to such an experimental design for the first time and they found our texts more appealing than university students who had already been exposed to such studies. The texts used in our study were taken from school textbooks and children’s encyclopaedias, and the familiarity of such texts may be reflected in the ratings of pleasantness and sweetness. Further studies are needed to investigate why the children rated the typefaces as sweeter and why the association between the ratings of sweetness and pleasantness was stronger in this group.

4.2. Relationship Between Typeface Perceived Sweetness and Reading Fluency

We used two indicators of reading fluency, i.e., reading speed and reading comprehension [14,16]. Sweeter typefaces were read faster; however, no significant correlation was found between the sweetness of the typeface and text comprehension. It is possible that our comprehension test was not sufficiently discriminating. Future studies should use a better measure of text comprehension, yet this also requires longer texts, which could increase the duration of the experiment and lead to fatigue or reduced motivation to participate in the study. Nevertheless, the influence of age on text comprehension was clear enough in the present study. More experienced readers understood the texts better. They also read the texts more quickly.
From the results of our study, we can conclude that reading fluency and the emotional reactions of the reader during the reading depend on the shape of the typeface. Due to the cross-modal correspondence between different senses, some typefaces are perceived as sweeter and more pleasant than others. Since our study was a correlational study and both the emotional response and reading fluency were observed simultaneously, we cannot say with certainty at this stage whether the emotional response has an effect on reading fluency, or whether it is the other way around. This question needs to be investigated in the future using an experimental approach.

4.3. Limitations

Our research encountered several limitations that should be considered. While the texts used were of similar difficulty, there were additional factors beyond typeface shape that may have influenced the outcomes. Firstly, participants might have reacted differently to specific texts based on their interests. For instance, adults and children might show varied emotional responses to content such as descriptions of animals. This variability could have contributed to the differences observed across age groups.
Secondly, the typefaces employed in this study varied in certain shape features that could influence reading metrics, including typographic tonal density and character size. Although the x-height was standardised, other elements such as the dimensions of ascenders and descenders differed among typefaces. This discrepancy altered the amount of white space around the ascenders and descenders, which consequently affected line spacing, even when the leading was uniformly set (at 140%). Variations in white space and the internal shapes of typeface letters inevitably led to differences in typographic tonal density, even with consistent x-height adjustments. Future investigations could focus on isolating specific features of typefaces, such as stroke shape, while controlling for all other attributes, to better understand their effects on reading.
Thirdly, the COVID-19 pandemic posed challenges to the inclusion of larger sample sizes, reducing the statistical power of our analyses. Future studies would benefit from involving more participants to strengthen the findings.
Due to pandemic restrictions, measurements with the university students were conducted in the laboratory for visual perception, whereas measurements with elementary school students were conducted on the premises of the elementary school. The differences in the experimental conditions might have affected our results. However, we made every effort to replicate the conditions of the laboratory on school premises as closely as possible to minimise differences in room illumination and, consequently, the effect of light on the readers (we ensured that the windows were covered, the lighting was artificial and uniform, and there were no surfaces that could cause glare or reflections on the computer screen; we also made sure the environment was quiet and peaceful).
Despite these limitations, we believe that our results provide valuable insights into the effect of typeface shape on reading. The study utilised multiple measures of text processing, and although the fixed effects examined were not very pronounced, the results consistently suggest that reading with round/rounded typefaces, which were perceived as sweeter and consequently more pleasant than angular/pointed ones, was smoother, more pleasant, and somewhat more effective.
These initial findings emphasise the importance of considering typeface shape and cross-modal correspondence in reading research and comparing the results of different studies. Future research is needed to corroborate these observations and to investigate the wider effects of typeface shape and cross-modal correspondence in the process of reading.

4.4. Conclusions

The present study pursued two main aims. The first one was to investigate how typeface shape influences the perceived sweetness and pleasantness of a typeface and reading fluency. Specifically, this study aimed to determine whether round/rounded typefaces are perceived as sweeter and more pleasant than angular/pointed ones and how the perception of typeface sweetness is related to reading fluency (reading speed and comprehension). The second aim was to examine differences between younger, less experienced readers and adult, more experienced readers in their responses to typeface shape. This study aimed to explore whether the relationship between perceived sweetness, pleasantness, and reading fluency varies between these two age groups.
Round/rounded typefaces were consistently rated as sweeter and more pleasant than angular/pointed typefaces. This correlation aligns with prior research suggesting that sweetness and pleasantness are often associated with rounded shapes. Interestingly, younger readers exhibited a stronger association between sweetness and pleasantness and provided higher sweetness ratings overall compared to adults.
Sweetness ratings were significantly correlated with reading speed: sweeter typefaces were read faster by both age groups. However, no significant relationship was found between sweetness and reading comprehension, likely due to limitations in our comprehension test. As expected, university students, being more experienced readers, outperformed younger students in both reading speed and comprehension.
Children displayed a greater sensitivity to typeface shape, which may be due to their heightened responsiveness to sensory stimuli, their limited exposure to typographic diversity, or their familiarity with the text materials used in this study. In contrast, adults rated typefaces with slightly lower sweetness and pleasantness, suggesting that their perceptions are less influenced by typeface design.
When evaluating emotional responses to different typefaces, the ratings of sweetness can be an adequate substitute for the ratings of pleasantness. In our study, typefaces that were rated as sweeter were read faster. Using typefaces that evoke a stronger sense of sweetness in the reader could make reading more enjoyable, which in turn could have a positive effect on the reading process for both younger and older readers. Sweeter typefaces could be recommended for the design of the reading materials for less experienced and more experienced readers. We suggest using typefaces that are not sans-serif but have more organic forms, including serif typefaces with some characteristics of old-style typefaces.
These findings reinforce the importance of considering typeface shape and cross-modal correspondences in both research and practical applications. Future studies should build on these insights to better understand the broader implications of typography for reading efficiency and enjoyment across different age groups.

Author Contributions

Conceptualisation: T.M., A.P. and K.M.; methodology: T.M., A.P. and K.M.; formal analysis: T.M.; validation: T.M. and A.P.; data collection: T.M.; resources: T.M.; visualisation: T.M.; writing—original draft: T.M.; writing—review and editing: A.P. and K.M.; funding acquisition: T.M., A.P. and K.M.; supervision: A.P. and K.M. All authors have read and agreed to the published version of the manuscript.

Funding

The research was founded by the Slovenian Research Agency (research core fundings No. P2-0450 and No. P5-0110).

Institutional Review Board Statement

The studies involving human participants were reviewed and approved by the Ethics Commission of the Faculty of Arts, University of Ljubljana. The protocol code is 270-2022, date of approval is 3 May 2022. Informed consent to participate in this study was provided by the participants or their legal guardian/next of kin.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the research.

Data Availability Statement

The data presented in this study are available on https://osf.io/zqa46/ accessed on 20 November 2024.

Acknowledgments

We would like to thank Ann Bessemans of Hasselt University for allowing us to use her original typeface Matilda for the purpose of our research.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Beier, S.; Sand, K.; Starrfelt, R. Legibility Implications of Embellished Display Typefaces. Visible Lang. 2017, 51, 107. [Google Scholar]
  2. Medved, T.; Podlesek, A.; Možina, K. Influence of Letter Shape on Readers’ Emotional Experience, Reading Fluency, and Text Comprehension and Memorisation. Front. Psychol. 2023, 14, 1107839. [Google Scholar] [CrossRef] [PubMed]
  3. Oderkerk, C.; Beier, S. Fonts of Wider Letter Shapes Improve Recognition in Peripheral Vision. Ergonomics 2020, 65, 753–761. [Google Scholar] [CrossRef]
  4. Brath, R.; Banissi, E. Using Typography to Expand the Design Space of Data Visualization. She Ji J. Des. Econ. Innov. 2016, 2, 59–87. [Google Scholar] [CrossRef]
  5. Brath, R. Text in Visualization: Extending the Visualization Design Space. Ph.D. Thesis, London South Bank University, London, UK, 2018. [Google Scholar]
  6. Bessemans, A. Matilda: A Typeface for Children with Low Vision. In Digital Fonts and Reading; World Scientific: Singapore, 2016; pp. 19–36. [Google Scholar]
  7. Bessemans, A. Typefaces for Children’s Reading. TMG 2016, 19, 1–9. [Google Scholar] [CrossRef]
  8. Beier, S.; Larson, K. How Does Typeface Familiarity Affect Reading Performance and Reader Preference? IDJ 2013, 20, 16–31. [Google Scholar] [CrossRef]
  9. Cacali, E. The Effects of Font on Vocabulary Memorization. Humanit. Rev. 2016, 21, 63–72. [Google Scholar]
  10. Gasser, M.; Boeke, J.; Haffeman, M.; Tan, R. The Influence of Font Type on Information Recall. N. Am. J. Psychol. 2005, 7, 181–188. [Google Scholar]
  11. Day, S.L.; Atilgan, N.; Giroux, A.E.; Sawyer, B.D. The Influence of Format Readability on Children’s Reading Speed and Comprehension. Educ. Sci. 2024, 14, 854. [Google Scholar] [CrossRef]
  12. Choi, S.; Jang, K.E.; Lee, Y.; Song, H.; Cha, H.; Lee, H.J.; Oh, A.-G.; Kang, H.; Kim, Y.-T.; Chang, Y. Neural Processing of Lower- and Upper-Case Text in Second Language Learners of English: An fMRI Study. Lang. Cogn. Neurosci. 2018, 33, 165–174. [Google Scholar] [CrossRef]
  13. Cadime, I.; Rodrigues, B.; Santos, S.; Viana, F.L.; Chaves-Sousa, S.; Do Céu Cosme, M.; Ribeiro, I. The Role of Word Recognition, Oral Reading Fluency and Listening Comprehension in the Simple View of Reading: A Study in an Intermediate Depth Orthography. Read. Writ. 2017, 30, 591–611. [Google Scholar] [CrossRef]
  14. Pikulski, J.J.; Chard, D.J. Fluency: Bridge Between Decoding and Reading Comprehension. Read. Teach. 2005, 58, 510–519. [Google Scholar] [CrossRef]
  15. Cruz, J.; Mendes, S.A.; Marques, S.; Alves, D.; Cadime, I. Face-to-Face Versus Remote: Effects of an Intervention in Reading Fluency During COVID-19 Pandemic. Front. Educ. 2022, 6, 817711. [Google Scholar] [CrossRef]
  16. Meyer, M.S.; Felton, R.H. Repeated Reading to Enhance Fluency: Old Approaches and New Directions. Ann. Dyslexia 1999, 49, 283–306. [Google Scholar] [CrossRef]
  17. Duranovic, M.; Senka, S.; Babic-Gavric, B. Influence of Increased Letter Spacing and Font Type on the Reading Ability of Dyslexic Children. Ann. Dyslexia 2018, 68, 218–228. [Google Scholar] [CrossRef] [PubMed]
  18. Mueller, M.L.; Dunlosky, J.; Tauber, S.K.; Rhodes, M.G. The Font-Size Effect on Judgments of Learning: Does It Exemplify Fluency Effects or Reflect People’s Beliefs about Memory? J. Mem. Lang. 2014, 70, 1–12. [Google Scholar] [CrossRef]
  19. Ali, A.Z.M.; Wahid, R.; Samsudin, K.; Idris, M.Z. Reading on the Computer Screen: Does Font Type Has Effects on Web Text Readability? IES 2013, 6, 26–35. [Google Scholar] [CrossRef]
  20. Su, N.; Li, T.; Zheng, J.; Hu, X.; Fan, T.; Luo, L. How Font Size Affects Judgments of Learning: Simultaneous Mediating Effect of Item-Specific Beliefs about Fluency and Moderating Effect of Beliefs about Font Size and Memory. PLoS ONE 2018, 13, e0200888. [Google Scholar] [CrossRef]
  21. Koch, B.E. Emotions in Typographic Design: An Empirical Examination. Visible Lang. 2012, 46, 206–227. [Google Scholar]
  22. Bigelow, C. Typeface Features and Legibility Research. Vis. Res. 2019, 165, 162–172. [Google Scholar] [CrossRef]
  23. Hsieh, Y.-C.; Kuo, C.-T.; Lin, H. The Effect of Screen Size of Mobile Devices on Reading Efficiency. In Human Aspects of IT for the Aged Population. Design for Aging; Zhou, J., Salvendy, G., Eds.; Springer International Publishing: Cham, Switzerland, 2016; Volume 9754, pp. 435–445. [Google Scholar]
  24. Bjork, R.A.; Yue, C.L. Commentary: Is Disfluency Desirable? Metacognition Learn. 2016, 11, 133–137. [Google Scholar] [CrossRef]
  25. Dressler, E. Understanding the Effect of Font Type on Reading Comprehension/Memory under Time-Constraints” (2019). Theses/Capstones/Creative Projects. 70. Available online: https://digitalcommons.unomaha.edu/university_honors_program/70 (accessed on 29 June 2024).
  26. Meyer, A.; Frederick, S.; Burnham, T.C.; Guevara Pinto, J.D.; Boyer, T.W.; Ball, L.J.; Pennycook, G.; Ackerman, R.; Thompson, V.A.; Schuldt, J.P. Disfluent Fonts Don’t Help People Solve Math Problems. J. Exp. Psychol. Gen. 2015, 144, e16–e30. [Google Scholar] [CrossRef]
  27. Novemsky, N.; Dhar, R.; Schwarz, N.; Simonson, I. Preference Fluency in Choice. JMR 2007, 44, 347–356. [Google Scholar] [CrossRef]
  28. Oppenheimer, D.M.; Frank, M.C. A Rose in Any Other Font Would Not Smell as Sweet: Effects of Perceptual Fluency on Categorization. Cognition 2008, 106, 1178–1194. [Google Scholar] [CrossRef]
  29. Pieger, E.; Mengelkamp, C.; Bannert, M. Metacognitive Judgments and Disfluency—Does Disfluency Lead to More Accurate Judgments, Better Control, and Better Performance? Learn. Instr. 2016, 44, 31–40. [Google Scholar] [CrossRef]
  30. Rummer, R.; Schweppe, J.; Schwede, A. Fortune Is Fickle: Null-Effects of Disfluency on Learning Outcomes. Metacognition Learn. 2016, 11, 57–70. [Google Scholar] [CrossRef]
  31. Sanchez, C.A.; Naylor, J.S. Disfluent Presentations Lead to the Creation of More False Memories. PLoS ONE 2018, 13, e0191735. [Google Scholar] [CrossRef]
  32. Wu, R.; Shah, E.D.; Kardes, F.R. “The Struggle Isn’t Real”: How Need for Cognitive Closure Moderates Inferences from Disfluency. J. Bus. Res. 2020, 109, 585–594. [Google Scholar] [CrossRef]
  33. Weissgerber, S.C.; Reinhard, M.-A. Is Disfluency Desirable for Learning? Learn. Instruc. 2017, 49, 199–217. [Google Scholar] [CrossRef]
  34. İlic, U.; Akbulut, Y. Effect of Disfluency on Learning Outcomes, Metacognitive Judgments and Cognitive Load in Computer Assisted Learning Environments. Comput. Hum. Behav. 2019, 99, 310–321. [Google Scholar] [CrossRef]
  35. Yue, C.L.; Castel, A.D.; Bjork, R.A. When Disfluency Is—And Is Not—A Desirable Difficulty: The Influence of Typeface Clarity on Metacognitive Judgments and Memory. Mem. Cogn. 2013, 41, 229–241. [Google Scholar] [CrossRef] [PubMed]
  36. Cushing, C.; Bodner, G.E. Reading Aloud Improves Proofreading (but Using Sans Forgetica Font Does Not). J. App. Res. Mem. Cogn. 2022, 11, 427–436. [Google Scholar] [CrossRef]
  37. Geller, J.; Davis, S.D.; Peterson, D.J. Sans Forgetica Is Not Desirable for Learning. Memory 2020, 28, 957–967. [Google Scholar] [CrossRef] [PubMed]
  38. Maxwell, N.P.; Perry, T.; Huff, M.J. Perceptually Fluent Features of Study Words Do Not Inflate Judgements of Learning: Evidence from Font Size, Highlights, and Sans Forgetica Font Type. Metacognition Learn. 2022, 17, 293–319. [Google Scholar] [CrossRef]
  39. Taylor, A.; Sanson, M.; Burnell, R.; Wade, K.A.; Garry, M. Disfluent Difficulties Are Not Desirable Difficulties: The (Lack of) Effect of Sans Forgetica on Memory. Memory 2020, 28, 850–857. [Google Scholar] [CrossRef] [PubMed]
  40. Wetzler, E.L.; Pyke, A.A.; Werner, A. Sans Forgetica Is Not the “Font” of Knowledge: Disfluent Fonts Are Not Always Desirable Difficulties. Sage Open 2021, 11, 21582440211056624. [Google Scholar] [CrossRef]
  41. Bjork, R.A.; Dunlosky, J.; Kornell, N. Self-Regulated Learning: Beliefs, Techniques, and Illusions. Annu. Rev. Psychol. 2013, 64, 417–444. [Google Scholar] [CrossRef] [PubMed]
  42. Diemand-Yauman, C.; Oppenheimer, D.M.; Vaughan, E.B. Fortune Favors the (Bold and the Italicized): Effects of Disfluency on Educational Outcomes. Cognition 2011, 118, 111–115. [Google Scholar] [CrossRef] [PubMed]
  43. Halin, N. Distracted While Reading? Changing to a Hard-to-Read Font Shields against the Effects of Environmental Noise and Speech on Text Memory. Front. Psychol. 2016, 7, 1096. [Google Scholar] [CrossRef] [PubMed]
  44. Macdonald, J.S.P.; Lavie, N. Visual Perceptual Load Induces Inattentional Deafness. Atten. Percept. Psychophys. 2011, 73, 1780–1789. [Google Scholar] [CrossRef] [PubMed]
  45. Celhay, F.; Boysselle, J.; Cohen, J. Food Packages and Communication through Typeface Design: The Exoticism of Exotypes. Food Qual. Prefer. 2015, 39, 167–175. [Google Scholar] [CrossRef]
  46. Davis, S.W.; Horváth, C.; Gretry, A.; Belei, N. Say What? How the Interplay of Tweet Readability and Brand Hedonism Affects Consumer Engagement. J. Bus. Res. 2019, 100, 150–164. [Google Scholar] [CrossRef]
  47. Lupton, E. Rhetorical Handbook. Design Papers 5; Nova Scotia College of Art and Design: Halifax, NS, Canada, 1987. [Google Scholar]
  48. Lewis, C.; Walker, P. Typographic Influences on Reading. Br. J. Psychol. 1989, 80, 241–257. [Google Scholar] [CrossRef]
  49. Raden, A.Z.M.; Qeis, M.I. Song And Typography: Expressing The Lyrics Visually Through Lyrical Typography. Int. J. Sci. Technol. Res. 2019, 3, 61–64. [Google Scholar]
  50. Wilkins, A.; Smith, K.; Penacchio, O. The Influence of Typography on Algorithms That Predict the Speed and Comfort of Reading. Vision 2020, 4, 18. [Google Scholar] [CrossRef] [PubMed]
  51. Price, J.; McElroy, K.; Martin, N.J. The Role of Font Size and Font Style in Younger and Older Adults’ Predicted and Actual Recall Performance. Aging Neuropsychol. Cogn. 2016, 23, 366–388. [Google Scholar] [CrossRef] [PubMed]
  52. Bigozzi, L.; Tarchi, C.; Vagnoli, L.; Valente, E.; Pinto, G. Reading Fluency as a Predictor of School Outcomes across Grades 4–9. Front. Psychol. 2017, 8, 200. [Google Scholar] [CrossRef]
  53. Labroo, A.A.; Pocheptsova, A. Metacognition and Consumer Judgment: Fluency is Pleasant but Disfluency Ignites Interest. Curr. Opin. Psychol. 2016, 10, 154–159. [Google Scholar] [CrossRef]
  54. Mead, J.A.; Hardesty, D.M. Price Font Disfluency: Anchoring Effects on Future Price Expectations. J. Retail. 2018, 94, 102–112. [Google Scholar] [CrossRef]
  55. Mueller, M.L.; Tauber, S.K.; Dunlosky, J. Contributions of Beliefs and Processing Fluency to the Effect of Relatedness on Judgments of Learning. Psychon. Bull. Rev. 2013, 20, 378–384. [Google Scholar] [CrossRef] [PubMed]
  56. Song, H.; Schwarz, N. If It’s Hard to Read, It’s Hard to Do: Processing Fluency Affects Effort Prediction and Motivation. Psychol. Sci. 2008, 19, 986–988. [Google Scholar] [CrossRef] [PubMed]
  57. Woods, R.J.; Davis, K.; Scharff, L.; Austin, S. Effects of Typeface and Font Size on Legibility for Children. Am. J. Psychol. Res. 2005, 1, 86–102. [Google Scholar]
  58. Wilkins, A.; Cleave, R.; Grayson, N.; Wilson, L. Typography for Children May Be Inappropriately Designed. J. Res. Read. 2009, 32, 402–412. [Google Scholar] [CrossRef]
  59. Abubaker, A.A.; Lu, J. The Optimum Font Size and Type for Students Aged 9–12 Reading Arabic Characters on Screen: A Case Study. J. Phys. Conf. Ser. 2012, 364, 012115. [Google Scholar] [CrossRef]
  60. Katzir, T.; Hershko, S.; Halamish, V. The Effect of Font Size on Reading Comprehension on Second and Fifth Grade Children: Bigger Is Not Always Better. PLoS ONE 2013, 8, e74061. [Google Scholar] [CrossRef]
  61. Amare, N.; Manning, A. Seeing Typeface Personality: Emotional Responses to Form as Tone. In Proceedings of the 2012 IEEE International Professional Communication Conference, Orlando, FL, USA, 8–10 October 2012; pp. 1–9. [Google Scholar] [CrossRef]
  62. Haenschen, K.; Tamul, D.J. What’s in a Font?: Ideological Perceptions of Typography. Commun. Stud. 2020, 71, 244–261. [Google Scholar] [CrossRef]
  63. Tsonos, D.; Kouroupetroglou, G. Modeling Reader’s Emotional State Response on Document’s Typographic Elements. Adv. Hum.-Comput. Interact. 2011, 2011, 1–18. [Google Scholar] [CrossRef]
  64. Brumberger, E. The Rhetoric of Typography: The Persona of Typeface and Text. Tech. Commun. 2003, 50, 206–223. [Google Scholar]
  65. Childers, T.L.; Jass, J. All Dressed Up with Something to Say: Effects of Typeface Semantic Associations on Brand Perceptions and Consumer Memory. J. Consum. Psychol. 2002, 12, 93–106. [Google Scholar] [CrossRef]
  66. Crisinel, A.-S.; Jones, S.; Spence, C. ‘The Sweet Taste of Maluma’: Crossmodal Associations Between Tastes and Words. Chem. Percept. 2012, 5, 266–273. [Google Scholar] [CrossRef]
  67. Jordan, T.R.; AlShamsi, A.S.; Yekani, H.A.K.; AlJassmi, M.; Al Dosari, N.; Hermena, E.W.; Sheen, M. What’s in a Typeface? Evidence of the Existence of Print Personalities in Arabic. Front. Psychol. 2017, 8, 1229. [Google Scholar] [CrossRef]
  68. MacKiewicz, J. How to Use Five Letterforms to Gauge a Typeface’s Personality: A Research-Driven Method. J. Tech. Writ. Commun. 2005, 35, 291–315. [Google Scholar] [CrossRef]
  69. Shaikh, A.D.; Chaparro, B.; Fox, D. Perception of Fonts: Perceived Personality Traits and Uses. Usability News 2006, 8, 1–6. [Google Scholar]
  70. Manippa, V.; Tommasi, L. The Shape of You: Do Individuals Associate Particular Geometric Shapes with Identity? Curr. Psychol. 2023, 42, 10042–10052. [Google Scholar] [CrossRef]
  71. Turoman, N.; Velasco, C.; Chen, Y.-C.; Huang, P.-C.; Spence, C. Symmetry and Its Role in the Crossmodal Correspondence between Shape and Taste. Atten. Percept. Psychophys. 2018, 80, 738–751. [Google Scholar] [CrossRef] [PubMed]
  72. Bremner, A.J.; Caparos, S.; Davidoff, J.; De Fockert, J.; Linnell, K.J.; Spence, C. “Bouba” and “Kiki” in Namibia? A Remote Culture Make Similar Shape–Sound Matches, but Different Shape–Taste Matches to Westerners. Cognition 2013, 126, 165–172. [Google Scholar] [CrossRef]
  73. Shukla, A. The Kiki-Bouba Paradigm: Where Senses Meet And Greet. IJMH 2016, 3, 240–252. [Google Scholar] [CrossRef]
  74. Spence, C.; Deroy, O. Crossmodal Correspondences: Innate or Learned? i-Perception 2012, 3, 316–318. [Google Scholar] [CrossRef]
  75. Wan, X.; Woods, A.T.; Van Den Bosch, J.J.F.; McKenzie, K.J.; Velasco, C.; Spence, C. Cross-Cultural Differences in Crossmodal Correspondences between Basic Tastes and Visual Features. Front. Psychol. 2014, 5, 1365. [Google Scholar] [CrossRef]
  76. Walker, P. Cross-Sensory Correspondences and Symbolism in Spoken and Written Language. J. Exper. Psychol. Learn. Mem. Cogn. 2016, 42, 1339–1361. [Google Scholar] [CrossRef]
  77. Velasco, C.; Woods, A.T.; Wan, X.; Salgado-Montejo, A.; Bernal-Torres, C.; Cheok, A.D.; Spence, C. The Taste of Typefaces in Different Countries and Languages. Psychol. Aesthet. Crea. 2018, 12, 236–248. [Google Scholar] [CrossRef]
  78. Salgado-Montejo, A.; Alvarado, J.A.; Velasco, C.; Salgado, C.J.; Hasse, K.; Spence, C. The Sweetest Thing: The Influence of Angularity, Symmetry, and the Number of Elements on Shape-Valence and Shape-Taste Matches. Front. Psychol. 2015, 6, 1382. [Google Scholar] [CrossRef]
  79. Velasco, C.; Salgado-Montejo, A.; Marmolejo-Ramos, F.; Spence, C. Predictive Packaging Design: Tasting Shapes, Typefaces, Names, and Sounds. Food Qual. Prefer. 2014, 34, 88–95. [Google Scholar] [CrossRef]
  80. Velasco, C.; Woods, A.T.; Deroy, O.; Spence, C. Hedonic Mediation of the Crossmodal Correspondence between Taste and Shape. Food Qual. Prefer. 2015, 41, 151–158. [Google Scholar] [CrossRef]
  81. Velasco, C.; Woods, A.T.; Hyndman, S.; Spence, C. The Taste of Typeface. i-Perception 2015, 6, 1–10. [Google Scholar] [CrossRef]
  82. Velasco, C.; Hyndman, S.; Spence, C. The Role of Typeface Curvilinearity on Taste Expectations and Perception. Internat. J. Gastron. Food Sci. 2018, 11, 63–74. [Google Scholar] [CrossRef]
  83. Bar, M.; Neta, M. Visual Elements of Subjective Preference Modulate Amygdala Activation. Neuropsychologia 2007, 45, 2191–2200. [Google Scholar] [CrossRef] [PubMed]
  84. Ngo, M.K.; Velasco, C.; Salgado, A.; Boehm, E.; O’Neill, D.; Spence, C. Assessing Crossmodal Correspondences in Exotic Fruit Juices: The Case of Shape and Sound Symbolism. Food Qual. Prefer. 2013, 28, 361–369. [Google Scholar] [CrossRef]
  85. Velasco, C.; Beh, E.J.; Le, T.; Marmolejo-Ramos, F. The Shapes Associated with the Concept of ‘Sweet and Sour’ Foods. Food Qual. Prefer. 2018, 68, 250–257. [Google Scholar] [CrossRef]
  86. Matthews, P.; Simmonds, G.; Spence, C. Establishing Boundary Conditions for Multiple Design Elements Congruent with Taste Expectations. Food Qual. Prefer. 2019, 78, 103742. [Google Scholar] [CrossRef]
  87. Wang, Q.J.; Reinoso Carvalho, F.; Persoone, D.; Spence, C. Assessing the Effect of Shape on the Evaluation of Expected and Actual Chocolate Flavour. Flavour 2017, 6, 2. [Google Scholar] [CrossRef]
  88. Hyndman, S. Why Fonts Matter: A Multisensory Analysis of Typography and Its Influence from Graphic Designer and Academic Sarah Hyndman; Ebury Publishing: London, UK, 2016. [Google Scholar]
  89. Mano, H. Affect and Persuasion: The Influence of Pleasantness and Arousal on Attitude Formation and Message Elaboration. Psychol. Mark. 1997, 14, 315–335. [Google Scholar] [CrossRef]
  90. Gollety, M.; Guichard, N. The Dilemma of Flavor and Color in the Choice of Packaging by Children. Young Consum. 2011, 12, 82–90. [Google Scholar] [CrossRef]
  91. Piqueras-Fiszman, B.; Ares, G.; Varela, P. Semiotics and perception: Do labels convey the same messages to older and younger consumers? J. Sens. Stud. 2011, 26, 197–208. [Google Scholar] [CrossRef]
  92. Chall, J.S. Stages of Reading Development; McGraw-Hill: New York, NY, USA, 1983. [Google Scholar]
  93. McLean, R. The Thames and Hudson Manual of Typography; Thames and Hudson: London, UK, 2000. [Google Scholar]
  94. Možina, K. Knjižna Tipografija; BiblioThecaria Filozofska fakulteta: Ljubljana, Slovenia, 2003. [Google Scholar]
  95. Larson, K.; Hazlett, R.L.; Chaparro, B.S.; Picard, R.W. Measuring the Aesthetics of Reading. In People and Computers XX—Engage; Bryan-Kinns, N., Blanford, A., Curzon, P., Nigay, L., Eds.; Springer: London, UK, 2007; pp. 41–56. [Google Scholar]
  96. Petit, O.; Velasco, C.; Cheok, A.D.; Spence, C. Consumer Sensory Neuroscience in the Context of Food Marketing. In Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology, Iskandar, Malaysia, 16 November 2015; pp. 1–4. [Google Scholar]
  97. Picard, R.W. The Aesthetics of Reading. Available online: https://www.media.mit.edu/publications/the-aesthetics-of-reading-2/ (accessed on 29 June 2024).
  98. Tobii Pro Tobii Studio. User’s Manual, Version 3.4.8; Tobii AB: Stockholm, Sweden, 2017. [Google Scholar]
  99. ISO 3664; Graphic Technology and Photography—Viewing Conditions. ISO: Geneva, Switzerland, 2009.
  100. ISO 12646; Graphic Technology—Displays for Colour Proofing—Characteristics. ISO: Geneva, Switzerland, 2015.
  101. ISO 9241-303; Ergonomics of Human-System Interaction—Part 303: Requirements for Electronic Visual Displays. ISO: Geneva, Switzerland, 2011.
Applsci 15 00326 g001
Figure 1. Examples of two round/rounded typefaces: (A) Matilda and (B) Comic Sans MS.
Figure 1. Examples of two round/rounded typefaces: (A) Matilda and (B) Comic Sans MS.
Applsci 15 00326 g001
Applsci 15 00326 g002
Figure 2. Examples of two angular/pointed typefaces: (C) Arial Nova and (D) Birch Std.
Figure 2. Examples of two angular/pointed typefaces: (C) Arial Nova and (D) Birch Std.
Applsci 15 00326 g002
Applsci 15 00326 g003
Figure 3. Ten typefaces selected for study.
Figure 3. Ten typefaces selected for study.
Applsci 15 00326 g003
Applsci 15 00326 g004
Figure 4. Effects of typeface sweetness ratings and age group on typeface pleasantness ratings.
Figure 4. Effects of typeface sweetness ratings and age group on typeface pleasantness ratings.
Applsci 15 00326 g004
Applsci 15 00326 g005
Figure 5. Effects of typeface shape and age group on ratings of typeface imagined sweetness.
Figure 5. Effects of typeface shape and age group on ratings of typeface imagined sweetness.
Applsci 15 00326 g005
Applsci 15 00326 g006
Figure 6. Effect of typeface sweetness and age group on indicators of reading fluency: (A) reading speed and (B) text comprehension.
Figure 6. Effect of typeface sweetness and age group on indicators of reading fluency: (A) reading speed and (B) text comprehension.
Applsci 15 00326 g006
Table 1. Fixed effects in the linear mixed model used for predicting typeface pleasantness based on typeface sweetness ratings and age group.
Table 1. Fixed effects in the linear mixed model used for predicting typeface pleasantness based on typeface sweetness ratings and age group.
Source of VariabilitybSEb95% CI for b tdfp
Intercept3.280.04[3.20, 3.36]79.1787.9<0.001
Typeface sweetness0.400.03[0.34, 0.46]13.37805.0<0.001
Age group−0.180.08[−0.34, −0.02]−2.1587.90.034
Typeface sweetness × Age group−0.200.06[−0.31, −0.08]−3.28805.0<0.001
Table 2. Fixed effects in the linear mixed model used for predicting typeface sweetness ratings based on typeface shape and age group.
Table 2. Fixed effects in the linear mixed model used for predicting typeface sweetness ratings based on typeface shape and age group.
Source of VariabilitybSEb95% CI for b tdfp
Intercept2.790.06[2.68, 2.91]45.7383.8<0.001
Typeface shape−0.620.08[−0.78, −0.46]−7.51763.5<0.001
Age group−0.480.12[−0.72, −0.24]−3.9383.8<0.001
Typeface shape × Age group−0.090.17[−0.41, 0.24]−0.53763.50.596
Table 3. Fixed effects in the linear mixed model used for predicting reading time per character (in ms) based on typeface sweetness ratings and age group.
Table 3. Fixed effects in the linear mixed model used for predicting reading time per character (in ms) based on typeface sweetness ratings and age group.
Source of VariabilitybSEb95% CI for b tdfp
Intercept80.763.01[74.86, 86.67]26.8184.6<0.001
Typeface sweetness−1.630.46[−2.54, −0.73]−3.54773.1<0.001
Age group−17.596.03[−29.40, −5.78]−2.9284.60.005
Typeface sweetness
× Age group		−0.120.93[−1.93, 1.70]−0.13773.10.900
Table 4. Results of generalised mixed modelling (with binary dependent variable) used for predicting text comprehension based on typeface sweetness ratings and age group.
Table 4. Results of generalised mixed modelling (with binary dependent variable) used for predicting text comprehension based on typeface sweetness ratings and age group.
Source of VariabilitybSEbOR95% CI for OR zp
Intercept2.190.138.90[6.95, 11.37]17.39<0.001
Typeface sweetness0.140.101.15[0.95, 1.39]1.460.14
Age group0.670.251.96[1.20, 3.21]2.670.008
Typeface sweetness
× Age group		0.140.191.15[0.79, 1.68]0.730.47
Note. OR = odds ratio.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Medved, T.; Podlesek, A.; Možina, K. Eye-Tracking Study on Reading Fluency in Relation to Typeface Pleasantness Influenced by Cross-Modal Correspondence Between Taste and Shape. Appl. Sci. 2025, 15, 326. https://doi.org/10.3390/app15010326

AMA Style

Medved T, Podlesek A, Možina K. Eye-Tracking Study on Reading Fluency in Relation to Typeface Pleasantness Influenced by Cross-Modal Correspondence Between Taste and Shape. Applied Sciences. 2025; 15(1):326. https://doi.org/10.3390/app15010326

Chicago/Turabian Style

Medved, Tanja, Anja Podlesek, and Klementina Možina. 2025. "Eye-Tracking Study on Reading Fluency in Relation to Typeface Pleasantness Influenced by Cross-Modal Correspondence Between Taste and Shape" Applied Sciences 15, no. 1: 326. https://doi.org/10.3390/app15010326

APA Style

Medved, T., Podlesek, A., & Možina, K. (2025). Eye-Tracking Study on Reading Fluency in Relation to Typeface Pleasantness Influenced by Cross-Modal Correspondence Between Taste and Shape. Applied Sciences, 15(1), 326. https://doi.org/10.3390/app15010326

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop