The golden ratio as a model of aesthetic experience in UI design

1. Introduction

Every day we make decisions guided by our aesthetic preferences (Palmer, 2013). For example, we may end up buying artworks for our homes based on the aesthetic experiences they evoke, not because they provide us with utility in some other way. The influence of aesthetics on our information processing and decision-making is strong and multifaceted, as illustrated well by the design of many consumer products. Aesthetically pleasing products sell better than comparable products with better features (Tractinsky, 1997; Creusen, 2005). We also evaluate other attributes through the lens of aesthetics. For instance, we perceive user interfaces as more usable when they are visually pleasing (Sonderegger, 2010; Tractinsky, 1997). Examining this aesthetic experience and the factors behind visual aesthetics is the focus of this thesis. The topic is narrowed by focusing on the best-known model of visual aesthetics: the golden ratio, and its use in designing digital user interfaces.

User interfaces belong strongly to research in human–computer interaction. Often, the focus is on factors responsible for interface efficiency, such as errors, comprehensibility, learning, and performance over time (Michailidou, 2008; Tractinsky, 2003). However, interface research focused solely on usability and efficiency has over the years made room for the study of aesthetic properties as well. Still, the focus has often been on how aesthetics influences other evaluation metrics of the interface. The study of the factors that define interface aesthetics has remained limited (Tractinsky, 2003). Studies such as how visually pleasing interfaces provide subjectively better usability strongly exemplify this prevailing approach (Michailidou, 2008). Although such research argues strongly for the importance of aesthetic experience in human information processing, research into the determinants of aesthetics has not, at least so far, attracted great interest among researchers (Palmer, 2013). One reason is the difficulty of operationalizing aesthetics and its strong subjectivity—defining clear measures of aesthetics has so far not succeeded, and the generalizability of results has been low. In addition, in studies evaluating the aesthetics of user interfaces, the methods assumed to be responsible for aesthetics are often defined ad hoc, often only loosely grounded in earlier theories of aesthetics (Karvonen, 2000).

This thesis reviews research that engages with the study of aesthetic experience, touching on the challenges of studying aesthetics and applying findings in practice. First, it examines aesthetics and the definition of aesthetic experience, topics studied especially in philosophy. Next, the thesis presents the model of the golden ratio and research concerning it. The thesis considers aesthetics only from the perspective of visual aesthetics, narrowing the scope to the effect of composition (i.e., arrangement). The simplicity of the golden ratio and its applicability to assessing the relationships and placement of interface elements make it a relevant topic. Its long history—for example in art—and early research also make the golden ratio a worthwhile model of aesthetic experience to examine. Finally, the thesis discusses the golden ratio through models of aesthetic experience in user interfaces.

2. Aesthetics as a science and the definition of aesthetic experience

Research on aesthetic preference is one of the oldest topics in psychology, with Gustav Fechner often seen as its pioneer (Philips, 2010). Fechner's aesthetic experiments conducted in the late 19th century are also considered among the first in experimental psychology. After Fechner, however, research on aesthetic experience and aesthetics in psychology decreased significantly (Palmer, 2013). Before Fechner's experimental work, aesthetics had been studied in philosophy, where it is defined as "the study of the relationship between the human mind and emotions and the perception of beauty" (Liu, 2003; Palmer 2013). Although aesthetics is generally defined as a branch of philosophy that studies values of beauty, the study of experienced beauty has been strongly linked to art and the relationship between humans and art (Palmer, 2012). Such a boundary creates problems when examining aesthetic experience in contexts where the sources of aesthetic experience are not unambiguously stimuli defined as art. Another problem is defining beauty. Palmer notes that definitions of aesthetics rely on an abstract understanding of the concept "perceiving beauty." Aesthetics then becomes based on immeasurable qualia and is therefore difficult to operationalize.

Partly due to this vague definition, there are significant differences in aesthetics research across disciplines. Recently, due both to this cross-disciplinary tension and to the partial exclusion of experimental methods, there has been an effort to redefine aesthetics in psychological research. This has taken place as part of the emergence of a new "interdisciplinary aesthetic science" (Shimamura, 2012; Palmer, 2013). Shimamura and Palmer's foundations for aesthetic science are set out in a 2013 work that brings together practitioners of aesthetics, neuroscience, and psychology, aiming to integrate findings across these fields about aesthetics. The aim is especially to build a deeper understanding of aesthetics than before.

A newer, more comprehensive definition of aesthetics and aesthetic experience is thus offered through aesthetic science. According to Shimamura, the term should be broadened to include all "hedonic reactions" to sensory experiences while severing ties to art (Shimamura, 2012). In this definition, a hedonic reaction refers to an individual's preference-based judgment of aesthetics: one likes or does not like an object. Such a broad definition makes it possible to expand the research questions of aesthetics to a wider set of methods than before. In this thesis, aesthetics and aesthetic experience are therefore treated in line with Shimamura and Palmer's definitions within aesthetic science. Aesthetic science makes it possible to extend aesthetics to more targets than before, such as user interfaces (Shimamura, 2012; Weed, 2013).

3. Theories of visual aesthetics

Visual perception can be examined—both from neural and cognitive perspectives—as a combination of top-down and bottom-up information-processing processes (Shimamura, 2012; Liu, 2003). In bottom-up processes, lower-level processing proceeds from brain areas responsible for low-level perception toward higher-level brain areas responsible for processing sensory information. In aesthetics research specifically, Fechner's experiments on preferences for basic shapes and colors can be seen as emphasizing bottom-up processes. Fechner's aim was to form an understanding of the relationship between the visual properties of form and aesthetic experience (Philips, 2010; Shimamura, 2012; Liu, 2003).

A criticism of bottom-up processing in aesthetics is that an aesthetic response to a complex object, such as a work of art, is not merely the sum of its parts (Liu, 2003). In the opposing view—top-down processing—higher-level processes, such as memory, influence lower-level processing. An example is recognizing objects based on prior knowledge. While Fechner can be viewed as an example of a supporter of bottom-up processes, early 20th-century Gestalt psychology can be seen as an alternative supporting a top-down view (Shimamura, 2012). According to three German psychologists representing this tradition—Max Wertheimer, Kurt Koffka, and Wolfgang Köhler—visual perception could not be understood through a purely atomistic approach; rather, a holistic understanding of the organization of elements was necessary to construct visual perception.

Aesthetic experience cannot be said to be primarily composed of any single factor, nor is it possible to clearly limit its processing to purely bottom-up or purely top-down mechanisms (Liu, 2003). The list of theories describing the emergence of aesthetic experience is extensive, covering, for example, evolutionary psychological perspectives as well as ecological and sociological accounts (Liu, 2003). Within the framework of this thesis, however, the emergence of aesthetic experience is considered primarily as a bottom-up process.

4. The golden ratio

The golden ratio (also the golden section) is one of the oldest mathematical models (Konechi, 2003). Historically it has appeared across many disciplines and is still considered one of the most aesthetically pleasing ratios for composing arrangements—for example in photography (Konechi, 2003; Svobodova, 2014; Boselie, 1992). The model has also been applied as a model of an aesthetic ideal in interface design (Lee, 2015).

The golden ratio is a simple equation used to define the relationship between two numbers. In the case of a line segment, the golden ratio is obtained when a segment is divided into two parts such that the ratio of the shorter part to the longer part is the same as the ratio of the longer part to the whole segment. The model can be illustrated with the following formula.

When the length of the segment is 1 and the longer part is x, then the shorter part is 1 − x and x must satisfy the equation:

1/x = (1 − x)/x

Then:

x² + x − 1 = 0

The positive solution to this quadratic equation is:

x = ½(1 + √5)

In condensed form, the equation can be presented as:

1/x = ½(1 + √5) ≈ 1.618

The golden ratio thus approaches 1:1.618. Notably, this ratio is very close to 1:1.5, which is also commonly used, for example, in photographic composition (Svobodova, 2014; Boselie, 1984; Boselie, 1992). According to Boselie's research, this ratio is preferred just as much as the golden ratio (Boselie, 1992).

The golden ratio can be extended beyond line segments to other shapes as well. The side lengths of the so-called golden rectangle are in the golden ratio. Like the golden ratio itself, the golden rectangle has also been believed to have strong connections to aesthetics (McManus, 1997). Practically speaking, the golden ratio has been claimed to be found—or can be found—almost anywhere in the context of art and construction (Green, 1995). For example, Leonardo da Vinci's Mona Lisa has been claimed to follow the golden ratio, as has the Parthenon built by the ancient Greeks (Boselie, 1992). However, it is questionable how accurate these claims are (Boselie, 1992; Di Dio 2007; Green, 1995; Konechi, 2003).

4.1 How the golden ratio has been studied

Its frequent appearance in many contexts is one reason the golden ratio has been widely studied (Boselie, 1992). The studies can roughly be divided into two categories: preference studies based on evaluating geometric figures, and studies in which the golden ratio is evaluated in images or artworks (Green, 1995). Most studies have primarily examined geometric shapes with different ratios—triangles, rectangles, and line segments. In these cases, validity is higher and the aesthetic experience can be more strongly argued to stem from proportions. However, whether these lower-level shape preferences can be generalized to higher-level representations, such as artworks, is questionable (Stieger, 2015). Methodologically, studies have been limited to choosing the most pleasing figure (which is more pleasing) or producing a figure (divide a line "beautifully").

Research on the golden ratio has proceeded in a rhythm where for every study that refutes an aesthetic effect of the golden ratio, a handful of new studies emerge that challenge methods or criticize how results are presented in favor of refutation (Green, 1995). The same phenomenon has occurred in the other direction as well, and the history of the golden ratio includes many "proclamatory" studies attempting to overturn all previous research (Boselie, 1992). Over time, many studies have also been undermined simply due to poor documentation and fairly imprecise methods. For example, Fechner's results have nearly as many different interpretations as they have citations (Green, 1995). Criticism of the golden ratio has thus largely been built on personal interpretations of results and methods rather than genuine comparisons of outcomes (Green, 1995).

The most comprehensive review of psychological research on the golden ratio was conducted by Green, who examined studies from 1865–1995 (Green, 1995). Green concludes that the results presented in the reviewed studies are so sensitive that they could not establish the existence of a potentially meaningful psychological factor. Green continues:

"On the other hand, one might argue that there has been something of a concerted effort among some psychologists to show that there is nothing to the alleged effects of the golden section; that the unreliability of the effects is due to research practices geared to show it to be a fraud, rather than to an inherent weakness in the effect."

According to Green, many of the reviewed studies show a clear desire to disprove this "numerological fantasy" and exhibit obvious carelessness. The goal has not been to objectively demonstrate the nonexistence of the phenomenon. However, this also does not prove the golden ratio either.

In studies where a preference for the golden ratio is found, the result is most often an average effect: the group's preference converges toward the golden ratio, and the variance in preferences can be quite large (Green, 1995). Clear individual preference for the golden ratio is found only in a few experiments. Comparing results is complicated by the fact that in experiments where the golden ratio is highest on average, the mode or frequency is often not reported. Green concludes that the golden ratio is potentially a real phenomenon but on very shaky ground. It is difficult to say whether preference for the golden ratio is learned or innate. Although the golden ratio appears primarily in Western culture, there is evidence of the phenomenon in other cultures as well (Konecni, 2005; Green, 1995). Finally, Green states that the methods used to study the relationship between the golden ratio and aesthetic experience are too crude to refute the claims of skeptics or believers, and that the phenomenon cannot be disproven or proven solely by observing outward behavior.

4.1.1 Konecni's studies with artists

Among contemporary empirical studies of the golden ratio, the largest experimental setup appears in Konecni's 1997 research (Konecni, 1997). Across three separate experimental designs, the study uses methods of aesthetics earlier developed by Fechner. The first study applied methods previously used in studying the golden ratio (such as producing rectangles, dividing a line in two) as well as new methods (such as evaluating vases made with and without the golden ratio). The sample size was 260 students. In studies based on earlier methods, no evidence was found connecting the golden ratio to beauty. Nor did evaluation of the vases reveal a clear preference for those based on the golden ratio. In a second study conducted by Konecni in 2003, the presence of the golden ratio was tested in illustrations produced by professional artists (Konecni, 2003). The artists were tasked with producing illustrations of presented objects and paintings in which the golden ratio was clearly present. The results support the golden ratio: the relative accuracy of produced illustrations in copying the criterion proportions was high, and the golden ratio appeared in most of them very precisely. Criticism of the design is that it does not demonstrate that the golden ratio is more pleasing.

Konecni's results must be treated with caution, and Konecni also notes that the existence of the golden ratio is subtle but elusive. Importantly, none of the studies produced significant evidence of a relationship between the golden ratio and aesthetic experience (Konecni, 1997; Konecni, 2003). The results of experiments that did produce positive findings thus suggest more the presence of the golden ratio in art than that the golden ratio is exceptionally pleasing. Green's earlier conclusion about the crudeness of methods applies here as well: the possible existence of the golden ratio is likely impossible to verify solely by examining outward behavior.

4.1.2 Association studies

The golden ratio has continued to be studied even after Konecni's 2006 work (Stieger, 2015). In Stieger's 2015 study, no greater preference was found for the golden ratio than for other ratios (Stieger, 2015). Stieger's studies used the IAT method (Implicit Association Test), which can be used to examine implicit evaluation (Stiegler, 2015; Fiedler, 2006). In IAT studies, participants are shown a series of stimuli that they must categorize into the correct category from their perspective. The time allotted for categorizing a stimulus is so short that under time pressure, participants' decision-making is strongly shaped by familiarity, symmetry, and simplicity, reducing the role of conscious information processing in categorization. According to Stieger, the IAT method can bypass Green's criticism of methods based on observing external behavior. Stieger argues that IAT can better reveal decision-making based on low-level processing.

Stieger's research consisted of three separate sub-studies. In each, participants were shown artworks whose central element was placed either according to the golden ratio (first and second designs) or at a 3/4 ratio. The studies observed both explicit and implicit preferences for the artworks. The results were unfavorable for the golden ratio. None of the studies found evidence of preference for the golden ratio either implicitly or explicitly. The golden ratio also did not differ significantly from the 3/4 ratio, and often artworks with centrally (symmetrically) placed elements were rated as more pleasing. Stieger suggests that implicit preference may lean more toward symmetry, while appreciation for the golden ratio is learned, for example through art. Stieger notes that even the IAT method may not be suitable for detecting the golden ratio's effect because the stimulus (in this case the artwork) is shown briefly. According to Stiegler, the short presentation time—central to IAT—may prevent the golden ratio from "opening up" to participants. In that case, the golden ratio might only be detectable through conscious perception. However, Stieger's study did not find evidence that the golden ratio is preferred even with longer exposure times. The IAT method has also been criticized, and its reliability and validity have been questioned in several studies (Fiedler, 2006; Blanton, 2007; Rezaei, 2011).

4.2 The neural basis of the golden ratio

Based on the studies presented earlier, it is possible that the golden ratio is a bottom-up process, making its effects difficult to verify solely by observing outward behavior. It is possible that the phenomenon is so small that its effects do not straightforwardly appear in behavior (Stiegler, 2015; Green, 1995; Konecni, 2005). Studying the phenomenon should begin by examining the lowest-level information processing. In practice, this means locating neural responses to the golden ratio using brain-imaging methods.

Neural correlates of aesthetic experience have been a major recent addition to the study of aesthetic experience (Chatterjee, 2011; Zeki, 1999; Palmer, 2013; Ramachandran, 1999; Di Dio, 2007). The roots of the field known as neuroaesthetics can be seen in the neurological models of Ramachandran and Zeki, which argue for the critical role of a neural basis in understanding aesthetic experience (Zeki, 1999; Ramachandran, 1999;). Zeki in particular argues strongly for the importance of neural mechanisms for theories of aesthetics, stating that theories remain incomplete without a position on the neural foundation (Zeki, 1999). As a product of human information processing, aesthetic experience must be built on the rules of the system producing it—the brain. Palmer, however, questions the usefulness of searching for neural correlates. According to Palmer, locating the activation responsible for aesthetic experience requires first identifying the manifestation of that activity in behavior, and then demonstrating the dependency between the two. If behavioral measures of aesthetic experience cannot be found, then correlation cannot be demonstrated either.

The golden ratio has been examined in at least one neuroaesthetics study. Di Dio used fMRI to study the effects of art on brain activation (Di Dio, 2007). In the setup, participants were shown sculptures from ancient Greece and the Renaissance whose original proportions had been altered to conform to the golden ratio. The experiment evaluated participants' (n = 14) subjective and objective aesthetic experience. The study found evidence for objective aesthetics, meaning certain features could be said to specifically activate brain regions responsible for experiencing aesthetics. Conversely, the golden ratio was not found to cause activation in these regions (Di Dio, 2007).

5. The golden ratio in user interface design

Due to its simplicity, the golden ratio can be applied to many different shapes and targets. Its presence in architecture, art, products, and—depending on perspective—also in nature supports this claim. Notably, its presence in these cases has often been artificial: most artists have consciously included the golden ratio in their works, often in pursuit of maximal aesthetic experience, and evidence for naturally occurring outputs that follow the golden ratio cannot yet be confirmed (Green, 1995; Stieger, 2015). Because preference for the golden ratio may also be learned, the problem becomes even more complex (Green, 1995).

Although findings on the golden ratio's aesthetic value are contradictory, it can arguably be used at least as an early-stage design model in industrial design (Bloch, 1995). Design patterns have long been used to communicate established knowledge in interface design and to assist designers (Van Welie, 2001). With patterns, designers can avoid recurring problems and make better decisions about interfaces. The requirement of evidence is a weakness for the golden ratio, creating challenges in adopting it as a design pattern (Van Welie, 2001). Clear evidence for the golden ratio's effect as a measure of aesthetics is lacking and requires further investigation. To determine the golden ratio's suitability for user interfaces, experimental studies would be needed where the golden ratio is applied specifically in this context.

5.1 Background factors of user-interface aesthetics

User-interface aesthetics affect how users interact with an interface (Miniukovich, 2015). Interface designers aim to build a visually aesthetic whole that implicitly helps the user navigate to the desired part of the interface and understand the available actions. Aesthetics is also an important factor for approachability, and an unpleasant interface raises the user's threshold for interaction (Faraday 2009). In addition, cultural factors significantly affect interface aesthetics, and in Eastern cultures a Nordic minimalist interface may be seen as cheap and ugly (Karvonen 2000, Reinecke 2013).

Several measures have been proposed for user-interface aesthetics, such as: visual clutter, color scale, number of primary colors, figure/ground contrast, symmetry, balance, order, cohesion, proportion, and simplicity (Miniukovich, 2015). In many cases, these measures originate from research in human–computer interaction or psychology examining complexity and unpleasantness. In addition, interface aesthetics can also be examined temporally (Miniukovich, 2015). Tractinsky et al. found research on the relationship between first impressions of interface aesthetics and perceived overall aesthetics (Tractinsky, 2006). According to their results, a half-second first impression of aesthetics correlates strongly with a first impression formed over ten seconds as well.

Designing user interfaces is a complex, expensive, and time-consuming process (Sears, 1995; Cross, 2004). During design, multiple problems may be encountered, and multiple solutions may be derived. For frequently encountered problems, ready-made solution patterns can often be found, though using them requires a considerable amount of knowledge. Manually traversing the wide problem space and its solutions is neither feasible nor sensible (Poltrock, 1994). A possible solution is computational optimization, which applies models derived from research to solve design problems. One way to solve the design problem is therefore to convert it into a list of parameters that an optimizer based on a mathematical model explores, generating different interface proposals from the results.

5.2 Ngo et al.'s model of visual aesthetics for user interfaces

One of the most significant models for assessing the aesthetics of interface element placement is the one developed by Ngo et al., whose aesthetic measures are the same as those used in art (Ngo, 2003). The model consists of fourteen measures that can take values between zero (bad) and one (good). One measure is proportion, which evaluates how far the assessed element is from an aesthetically valued form, such as a square or a golden rectangle. Ngo et al.'s model is the only computational model of aesthetics in which the golden ratio appears as an aesthetic measure, though only in a single way of applying it. It should be noted that in Ngo et al.'s model, the golden ratio is one of five proportions toward which the model seeks to optimize, and the reasons for including it are not presented in the model.

Ngo et al.'s model was tested in an experiment with 79 students. The students had no prior experience with concepts of designing interface aesthetics. In the experiment, participants were shown five different interfaces for 20 seconds each. Participants rated the aesthetic quality of the interface on a low–medium–high scale. The setup produced weak evidence of a positive effect of aesthetics on perceived usability. The role of the golden ratio is not separately mentioned in the results, but in the experiment proportions were not found to have significant effects on aesthetics.

7. Discussion

This thesis has presented a cross-section of research on the golden ratio and aimed to form a holistic picture of the quality and methods of research over time concerning the golden ratio and the aesthetic experience it is claimed to produce. Based on the studies presented in this thesis, the golden ratio cannot be said to be a reliable measure of aesthetic experience. As a phenomenon, the golden ratio has been studied repeatedly throughout history and with many methods. The strongest evidence appears in older studies, many of which use methods from perceptual psychology. With contemporary methods—such as brain imaging—the aesthetic value of the golden ratio has not, however, been demonstrated.

Despite limited research evidence—or perhaps partly because of it—the golden ratio still seems to receive considerable attention today. In light of the earlier discussion, studying the neural basis of aesthetics will likely be the only way to either verify or refute the golden ratio as a phenomenon.

In view of the presented research, it is questionable whether using the golden ratio as a model of aesthetics—for example in user-interface design—is appropriate. Because the golden ratio does not differ significantly from other proportions, its influence on interface aesthetics is likely not significant either. There are also relatively few studies and models addressing the golden ratio in interface design.

8. References

Blanton, H., Jaccard, J., Christie, C., & Gonzales, P. M. (2007). Plausible assumptions, questionable assumptions and post hoc rationalizations: Will the real IAT, please stand up?. Journal of Experimental Social Psychology, 43(3), 399-409.
Boselie, F. (1984). The aesthetic attractivity of the golden section. Psychological Research, 45(4), 367-375.
Boselie, F. (1992). The golden section has no special aesthetic attractivity!. Empirical Studies of the Arts, 10(1), 1-18.
Bloch, P. H. (1995). Seeking the ideal form: Product design and consumer response. The Journal of Marketing, 16-29.
Chatterjee, A. (2011). Neuroaesthetics: a coming of age story. Journal of Cognitive Neuroscience, 23(1), 53-62.
Creusen, M. E., & Schoormans, J. P. (2005). The different roles of product appearance in consumer choice. Journal of product innovation management, 22(1), 63-81.
Cross, N. (2004). Expertise in design: an overview. Design studies, 25(5), 427-441.
Di Dio, C., Macaluso, E., & Rizzolatti, G. (2007). The golden beauty: brain response to classical and renaissance sculptures. PloS one, 2(11), e1201.
Faraday, P., & Sutcliffe, A. (1998, September). Making contact points between text and images. In Proceedings of the sixth ACM international conference on Multimedia (pp. 29-37). ACM.
Fiedler, K., Messner, C., & Bluemke, M. (2006). Unresolved problems with the "I", the "A", and the "T": A logical and psychometric critique of the Implicit Association Test (IAT). European Review of Social Psychology, 17(1), 74-147.
Green, C. D. (1995). All that glitters: A review of psychological research on the aesthetics of the golden section. PERCEPTION-LONDON-, 24, 937-937.
Karvonen, K. (2000, November). The beauty of simplicity. In Proceedings on the 2000 conference on Universal Usability (pp. 85-90). ACM.
Konecni, V. J. (2003). The golden section: Elusive, but detectable. Creativity Research Journal, 15(2-3), 267-275.
Konecni, V. J. (2005). On the "Golden Section". Visual Arts Research, 76-87.
Lee, C. B., & Lee, K. (2015). LG's G3 GUI. interactions, 22(1), 12-15.
Liu, Yili. "Engineering aesthetics and aesthetic ergonomics: theoretical foundations and a dual-process research methodology." Ergonomics 46.13-14 (2003): 1273-1292.
McManus, I. C., & Weatherby, P. (1997). The golden section and the aesthetics of form and composition: a cognitive model. Empirical Studies of the Arts, 15(2), 209-232.
Michailidou, E., Harper, S., & Bechhofer, S. (2008, September). Visual complexity and aesthetic perception of web pages. In Proceedings of the 26th annual ACM international conference on Design of communication (pp. 215-224). ACM.
Miniukovich, A., & De Angeli, A. (2015, April). Computation of Interface Aesthetics. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 1163-1172). ACM.
Ngo, D. C. L., Teo, L. S., & Byrne, J. G. (2003). Modelling interface aesthetics. Information Sciences, 152, 25-46.
Palmer, S. E., Schloss, K. B., & Sammartino, J. (2013). Visual aesthetics and human preference. Annual review of psychology, 64, 77-107.
Phillips, F., Norman, J. F., & Beers, A. M. (2010). Fechner's aesthetics revisited. Seeing and perceiving, 23(3), 263-271.
Poltrock, S. E., & Grudin, J. (1994). Organizational obstacles to interface design and development: two participant-observer studies. ACM Transactions on Computer-Human Interaction (TOCHI), 1(1), 52-80.
Ramachandran, V. S., & Hirstein, W. (1999). The science of art: A neurological theory of aesthetic experience. Journal of consciousness Studies, 6(6-7), 15-51.
Reinecke, K., & Bernstein, A. (2013). Knowing what a user likes: A design science approach to interfaces that automatically adapt to culture. Mis Quarterly, 37(2), 427-453.
Rezaei, A. R. (2011). Validity and reliability of the IAT: Measuring gender and ethnic stereotypes. Computers in human behavior, 27(5), 1937-1941.
Sears, A. (1995, December). AIDE: A step toward metric-based interface development tools. In Proceedings of the 8th annual ACM symposium on User interface and software technology (pp. 101-110). ACM.
Shimamura, A. P., & Palmer, S. E. (Eds.). (2012). Aesthetic science: Connecting minds, brains, and experience. Oxford University Press.
Sonderegger, A., & Sauer, J. (2010). The influence of design aesthetics in usability testing: Effects on user performance and perceived usability. Applied ergonomics, 41(3), 403-410.
Stieger, S., & Swami, V. (2015). Time to let go? No automatic aesthetic preference for the golden ratio in art pictures. Psychology of Aesthetics, Creativity, and the Arts, 9(1), 91.
Svobodova, K., Sklenicka, P., Molnarova, K., & Vojar, J. (2014). Does the composition of landscape photographs affect visual preferences? The rule of the golden section and the position of the horizon. Journal of Environmental Psychology, 38, 143-152.
Tractinsky, N., Cokhavi, A., Kirschenbaum, M., & Sharfi, T. (2006). Evaluating the consistency of immediate aesthetic perceptions of web pages. International journal of human-computer studies, 64(11), 1071-1083.
Tractinsky, N. (1997, March). Aesthetics and apparent usability: empirically assessing cultural and methodological issues. In Proceedings of the ACM SIGCHI Conference on Human factors in computing systems (pp. 115-122). ACM.
Van Welie, M., Van Der Veer, G. C., & Eliëns, A. (2001). Patterns as tools for user interface design. In Tools for Working with Guidelines (pp. 313-324). Springer London.
Weed, E. (2013). Stephen E. Palmer and Arthur P. Shimamura, eds. Aesthetic Science (review). Estetika: The Central European Journal of Aesthetics, (1), 128-133.
Zeki, S., & Nash, J. (1999). Inner vision: An exploration of art and the brain (Vol. 415). Oxford: Oxford University Press.