Delivering A Unified Design Model (UDM) -To Align Design to the Way the Human Brain Processes Visual Information

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Journal of Teaching and Education,
CD-ROM. ISSN: 2165-6266 :: 06(02):215–232 (2017)
DELIVERING A UNIFIED DESIGN MODEL (UDM) – TO ALIGN DESIGN
TO THE WAY THE HUMAN BRAIN PROCESSES VISUAL
INFORMATION
Bruce Hilliard, Jocelyn Armarego, Andrew Turk and Tanya McGill
Murdoch University, Australia
Presentation tools like PowerPoint are used extensively (Park & Feigenson, 2013), but they are
regularly criticised because poor application obfuscates the message (Schoeneborn, 2013). The project
introduced in this paper focussed on developing a Unified Design Model (UDM) and an integrated set
of research-based design principles, which would help users overcome identified weaknesses in the use
of presentation aids. As a bi-product of the research, this project also addressed issues related to other
computer-based visualisations. The first step taken to achieve this objective was to review research in
neuroscience, biopsychology, and cognitive science. Collected information was used to develop an
integrated understanding of the way the human brain processes information, and particularly visual
content. This knowledge was then integrated with guidance and results from psychophysics and design
related publications, to create a set of draft principles that holistically covered the key aspects of visual
design. In all, the information from 1640 publications was used to develop these draft design
principles. The validity of these draft principles was tested through an experimental program, which is
explained in the PhD thesis at Hilliard (2016). In the interests of brevity, this paper only introduces the
UDM framework. However, even this short introduction to the UDM gives important insights into the
design of presentations, and other forms of computer-based visualisations, including web pages and
e-learning material.
Keywords: Learning design, Psychophysics, Cognitive science, Presentation aids, Web design.
Introduction
Presentation software, such as Microsoft PowerPoint, is widely used in education (Brown, 2007;
Coleman, 2009; James, Burke, & Hutchins, 2006; Parette, Blum, Boeckmann, & Watts, 2009), business
(Mahin, 2004), and a range of other fields (Schoeneborn, 2013). This type of software is popular, because
visual aids can be very effective in improving communication, by generating good comprehension,
positive impressions, and viewer attention (Nouri & Shahid, 2005). However, there are also problems
associated with its use. For example, authors like Tufte (2003), Aldrich (2008), Taylor (2013), and
Thompson (2003) have strongly argued that visual aids such as PowerPoint are often misused, and can
therefore be counterproductive in terms of facilitating communication.
Many books and articles have been published that aim to assist designers to improve presentation
design. However, even a cursory review of existing ‘design’ books and articles demonstrates that different
publications provide contradictory advice, and in many cases the empirical basis for the recommendations
is unclear. This issue is borne out by Fritschi (2008, p. 6), who stated that design guidance ‘is still
215

216 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
primarily based on the intuitive beliefs of designers instead of empirical evidence’. Consequently, some
of the guidance in these design related sources may not be based on sound research. Additionally, as
there is disagreement between design authors, it is unclear which set of advice is most appropriate.
On the other hand, there is extensive literature from psychology related fields (including educational
psychology, psychophysics, biopsychology, neuroscience, and cognitive science). This material provides
recommendations based on empirical research, which can be applied for the optimisation of visual design
(Fritschi, 2008). However, the applicability of this work in managing visual design is typically restricted,
because of the following limitations:
xThe research often does not focus on the broader implications of the findings within a
comprehensive design model. As an example, many psychophysical, biopsychological, and
neuroscience related publications do not attempt to link the findings back to the optimisation of
visual material. Consequently, it can be difficult for designers to apply this type of science-based
understanding, to directly improve their visual aids, screen design, web pages, or e-learning
systems.
xMost experimentation in these fields has a narrow research focus. For instance, the majority of
experiments address singular, or small numbers of, visual attributes (design parameters). This
means that the experiments typically do not take into account the complex interaction between
different aspects (design factors) within the visualisation.
These limitations illustrate that many research based findings do not directly support the development of
holistic design principles, which can be readily applied by designers to improve the quality and
effectiveness of their visual material. Consequently, designers are left with a conundrum. On the one
hand there has been a significant amount written about visual design, but the validity of the content is
unclear. Alternately, there is a great deal of valid research information available, but this material is
typically narrowly focussed and not readily usable for managing visual design.
Aim of the Research
A research project was initiated with the aim of helping overcome these problems, by developing a
validated set of principles that can be used to optimise the effectiveness of presentations in particular, and
visual design in general. In practice, this meant rigorously assessing the validity of design publications,
by cross-matching the recommendations with science-based sources. To facilitate this endeavour a
Unified Design Model (UDM) was created.
This document introduces the UDM and outlines the key design attributes within this framework.
The paper also provides a short overview of the UDM development process, and it concludes with the
hypotheses investigated to validate the draft principles.
The Unified Design Model
Laying the Foundation
It became obvious when assessing a wide range of design publications and research papers, that various
authors use different nomenclature to categorise the visual attributes. The first step toward achieving the
research objective was therefore to create a common framework for understanding the various visual
attributes.
After investigating a range of options, Tufte’s (1990) design advice was used as the foundation for
the model. Tufte’s (1990, 2006, 2007) research provided a sensible starting framework for categorising
most of the visual attributes. Just as importantly, it seemed apposite to apply the research from one of
PowerPoint’s greatest critics, to help develop a set of design guidelines that would help to overcome the
problems he identified.

Bruce Hilliard et al. 217
Tufte’s (1990) framework of visual attributes included aspects such as complexity, colour,
background, layout, arraying of the information, typography, and graphics. However, Tufte’s (1990,
2006, 2007) design guidance was predominantly focussed on static elements, so animation was not a
principal part of his design framework. Appropriate animations can, however, assist in generating
comprehension, positive impressions (Kim, Yoon, Whang, Tversky, & Morrison, 2007; Rebetez,
Bétrancourt, Sangin, & Dillenbourg, 2010), and attention (Dorr, Martinetz, Gegenfurtner, & Barth, 2010;
Jamet, Gavota, & Quaireau, 2008). For this reason, animation has been added to the framework
developed from Tuft’s (1990, 2006, 2007) material. Finally, a key thrust of Tufte’s (2003) argument
against the use of PowerPoint is that the visualisation overwhelms the message structure and content. He
therefore recommended that the message structure and content should take precedence.
Figure 1. The attributes within the Unified Design Model
These attributes were then validated against other design and science literature, to ensure that the
identified elements provided a suitable holistic framework. As a result of this extensive review, the
UDM framework shown in Figure 1 was developed.
The attributes within this framework can be described as follows:
xComplexity. Within this context, complexity relates to ‘the number of independent features of
the stimuli and meaningfulness, that is to say, a factor related with the number and variability of
the elements [on the screen and in the content], and a factor related with the overall structure of
the elements’ (Roberts, 2007, pp. 22-23). According to Tufte (1990), inappropriate use of
complexity can adversely affect the communication of the pertinent information. For example,
overly complex information imposes significant cognitive processing costs (Aksentijevic &
Gibson, 2012), which can adversely affect learning and communication outcomes (Kyndt, Dochy,
Sruyven, & Cascallar, 2011; Parks, Murray, Elfman, & Yonelinas, 2011), and create negative
impressions about the content (Roberts, 2007). Alternately, low levels of complexity can also
reduce the level of comprehension (McNamara, Kintsch, Songer, & Kintsch, 1996), attention
(Geissler, Zinkhan, & Watson, 2006), and impressions (Balfanz, Herzog, & Mac Iver, 2007;
Marks, 2000).
xMessage content and structure. This attribute refers to the content being communicated through
the presentation of the material. For instance, this covers the structure and amount of
information to be processed by the audience. The message content and structure is an important
source of complexity (Lang, Park, Sanders-Jackson, Wilson, & Wang, 2007), and can have a
significant impact on comprehension (O’Keefe and McCornack, 1987; Peterson, 2011; Tennyson,
1980), impressions (Stoner, 2007; Whalen, 1996) and attention (Grosz and Sidner, 1986; Økland,
2011). Consequently, this attribute forms a fundamental element of the design.
xVisualisation attributes. The visualisation attributes formed the key focus of this research
project, and include the following seven categories of variables:
Colour. The term colour refers to the application of hues, saturation, luminance and
contrasts within the visual display. Colour is an important variable, because it can

218 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
significantly affect the communication of information (Hanke, 1998). For instance, colour
can add reality, assist the viewer to discriminate between visual elements, focus attention on
the important information (e.g. by using salience), code and link logically related elements,
create impressions, and generate emotional responses (Jones, 1997; Kose, 2008; Pett &
Wilson, 1996).
Background. This attribute refers to the background colour, texture, and other visual
elements on the screen that act as a backdrop, and their interaction with the foreground
content. These background colours and visual elements can appreciably influence the
effectiveness of the communication (Tufte, 1990). As an example, background clutter
(Bravo & Farid, 2006), background content and context (e.g. gist information) (Epstein,
2005; Larson & Loschky, 2009; Otsuka & Kawaguchi, 2007), as well as background contrast,
luminance (Engmann et al., 2009) and colour (Bedwell, Brown, & Orem, 2008) can all affect
perception and cognition.
Layout. Tufte (1990) refers to layout as the structuring of the entire visible content, which is
processed holistically. Therefore, in the context of the UDM, the term layout refers to the
general arrangement of objects over the entire expanse of the screen/slide. The layout of visual
information can have a significant effect on viewer impressions (Altaboli & Lin, 2011) and
comprehension (Wästlund, Norlander, & Archer, 2008). Additionally, good layout can shape
attention, so the viewer processes the most important aspects of the information (Pralle, 2007).
Array. The term array refers to the localised grouping, positioning, or conjoining of visual
objects (Donderi, 2006). In other words, whereas layout addresses the entire screen
arrangement, array signifies the grouping of sub-elements within the layout. This
differentiation from layout is important, because visual material is processed at two levels
(Sanocki, Michelet, Sellers, & Reynolds, 2006). Firstly, the entire gist of a scene (e.g. the
entire screen/slide) is typically analysed as a whole entity by viewers once it is exposed
(Henderson & Hollingworth, 1999; Henderson, Williams, Catstelhano, & Falk, 2003).
Significant meaning is generated through this initial gist analysis of the layout (Tileagă, 2011;
Wolfe, Võ, Evans, & Greene, 2011). For instance, object recognition within a scene is
greatly influenced by the context generated by the gist analysis (Jiang, Sigstad, & Swallow,
2013; Wolfe et al., 2011). From the gist analysis, up to about 13 objects, or arrays of objects,
can be assimilated (Sanocki, Sellers, Mittelstadt, & Sulman, 2010), and attention is then
applied to process these (Betz, Kietzmann, Wilming, & König, 2010; Matsukura, Luck, &
Vecera, 2007). It is this second layer of processing that is affected by the arraying of
individual screen elements (Sanocki et al., 2006). Tufte (1990) identified that this arraying
of the information within visual groupings is an important aspect of visual communication.
Typography. This visual attribute relates to the way in which the words and sentences (text)
are represented on the screen. As discussed in Sanocki and Dyson (2012), aspects such as the
size, type, and the colour of the fonts used can directly affect comprehension of the textual
information. Additionally, typography can influence emotions (Koch, 2011), and attention
(Fondren, 2009).
Graphics. The term graphics covers pictures, graphs, and any form of pictorial element used
within the display (i.e. anything that is not just text). The use of appropriate graphics can
significantly enhance comprehension (Mayer, 2001), generate viewer attention (Tangen et al.,
2011), and positively shape people’s impressions (Gu, Liu, Van Dam, Hof, & Fan, 2013).
Animation. Within this UDM framework, animation means the utilisation of techniques to
create transitions, changes, or movements of material on the screen. The application of
appropriate animations can assist in generating comprehension and positive impressions (Kim
et al., 2007; Rebetez et al., 2010). Additionally, motion or change within the visual field can
attract attention to appropriate visual elements (Dorr et al., 2010; Jamet et al., 2008),
or interfere with the communication of the material if the animations are poorly applied
(Lowe & Boucheix, 2011)

Bruce Hilliard et al. 219
The UDM also illustrates key interactions between the various attributes. For instance, colour,
background, layout, array, typography, and graphical elements all interact (Tufte, 1990). Additionally,
the application of animation can affect each of the other attributes (de Koning, Tabbers, Rikers, & Paas,
2007). Visualisation attributes also interact with the message and structure (Medley & Haddad, 2011).
As an example, complex message content can be made more or less understandable, dependent on the
way it is visualised (Chaiken & Eagly, 1976).
Lastly, as shown in Figure 1, complexity encompasses all of the other attributes. This is because all
of these other attributes interact to generate complexity. For instance, the colour combinations used
(Cummings & Tsonis, 2006; Pathiavadi, 2009), pictorial/graphical design techniques applied (De
Westelinck, Valcke, De Craene, & Kirschner, 2005; Makaramanee, 1985; Moreno & Mayer, 1999), the
typography utilised (Green, 1981; Rayner, Reichle, Stroud, Williams, & Pollatsek, 2006), and the
animations that are implemented (Huff & Schwan, 2011; Mineo, Peischl, & Pennington, 2008; Schnotz &
Rasch, 2005) directly influence viewer assessments of complexity.
Applying the UDM
The UDM framework was used as a foundation for rationalising and amalgamating information in diverse
research and design publications. The full listing of the 1640 publications used for this analysis is
provided in Hilliard (2016). However, the various documents can be broadly grouped as explained in the
following subsections.
Neuroscience, Biopsychology and Cognitive Science Publications
More than 600 neuroscience, biopsychology and cognitive science papers were assessed in the literature
review, and key information from these was integrated to develop an understanding of perceptual and
cognitive processes. In particular, the following key models were developed:
xAn end-to-end visual processing model was created, which integrated available research on neural
physiology and the behaviours and roles of key structures in the eyes and brain. This reverse
engineering of the neural systems allowed the likely effects of different aspects of the visual
elements to be determined.
xAs the concepts of attention and awareness were critical to understanding how visual content is
processed; Attention and Continuum of Awareness models were created. These integrated
models provide a useful holistic framework for understanding how differences in the visualisation
affect perception and cognition at a fundamental level.
xA model that explains visual grouping was also developed, and applied to understand the
optimisation of layouts and arrays.
xInformation related to other key processes (e.g. reading and motion tracking) was also collated, so
this material could be applied to determine likely effects of different visual treatments.
Presentation Design Publications
There has been so much design material published that it would have been impossible to assess all of it in
detail. Consequently, it was decided to focus on suitable representatives of this material. After analysing
numerous presentation design publications, five books were selected as exemplars. This selection was
also simplified by leveraging expert advice on the most influential books within this domain. The five
publications used in this project were identified in Gabrielle and Alvarez (2012), who ‘asked 7 of the top
presentation experts in the world to tell us what books most inspired them to be better presenters’. In this
survey, each expert was asked to evaluate widely used and popular books in terms of their coverage of
content development, design, and delivery techniques. The top five visual design publications that they
selected are shown in Table 1.

220 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
Table 1. Selected publications for presentation design analysis
Title Panel Rating Author/Reference
Slide:ology #1 for design Duarte (2008)
Presentation Zen #2 for design Reynolds (2012)
Presentation Zen Design #3 for design Reynolds (2010)
Speaking PowerPoint #4 for design Gabrielle (2010)
Clear and to the Point #5 for design Kosslyn (2007)
This group of publications was representative, because it demonstrated the gamut between
philosophically design-focussed and more science-defined publications. For example, Reynolds (2010,
2012) predominantly concentrated on aesthetic design concepts based on the Zen philosophy.
Conversely, Kosslyn (2007), and to a lesser extent Gabrielle (2010) and then Duarte (2008), appeared to
found more of their recommendations on science-based research. Consequently, these five publications
were likely to provide advice that represented the range of design publications available. The selected
publications were reviewed in detail, to identify common and divergent recommendations that could then
be assessed in relation to the psychology related research.
Psychophysics Related Publications
Psychophysics ‘studies the relationships between stimulus characteristics and the perception of those
stimuli’ (Matsumoto, 2009, p. 412). In relation to this project, the term psychophysics refers to research
and findings examining different visualisation attributes. Information from more than 1000
psychophysics related publications was integrated within this literature review, to help assimilate design
recommendations and create a set of science-based draft principles. These publications typically covered
narrowly focussed experiments, so they needed to be assessed in terms of the UDM and other papers
covering similar topics. Additionally, the psychophysics material was cross-linked to the models and
frameworks created through the neuroscience, biopsychology and cognitive science research review, to
help determine low level relationships between outcomes and likely causation.
As a direct result of this analysis a range of additional models were developed to facilitate
understanding of key design issues. These models included developing a Complexity Curve (discussed
below), a Colour Salience Model (which identified fundamental colour prominence measures), a Gestalt
Interaction Model (that delivers a framework for understanding the relationship between various Gestalt
and aesthetic design principles), a font size readability calculator (to determine optimal point sizes for
different fonts, so they could be applied effectively to promote legibility and/or readability), a rigorous
process for graphics selection, and a clear methodology for identifying optimal animation strategies.
Each of these models is explained in more detail within Hilliard (2016).
The information from the psychophysics publications was applied to:
xvalidate recommendations made in the design publications;
xidentify other design principles that had not been expounded in the presentation design
publications; and
xidentify areas of ambiguity that required further investigation, to ratify the design principles.
This last point was of particular import, because it facilitated the development of hypotheses that
were most applicable for investigation within the framework of this research.
Identified Ambiguities
The key ambiguities identified through the literature review are shown in Table 2. Each of these
ambiguities reflect situations in which empirical research on these issues was not available, or conflicting
information had been identified in the literature review.

Bruce Hilliard et al. 221
Table 2. Ambiguities selected for investigation in this project
Attribute
(Code)
Description of the Ambiguity
Colour &
Background
(RCB1)
The effects of warm and cool colours. Warm hues like yellow are highly stimulating colours,
which may promote arousal, memory, perception, awareness (Massachusetts General Hospital,
2009), and attention (Berman, 2007). However large areas of full hue warm colours are often
disliked (Berman, 2007), and overuse of these hues appear to cause over-stimulation that can
induce psychological stress (Daggett, Cobble, & Gertel, 2008). Alternatively, as identified by
Mehta and Zhu (2009) cool colours like blue can enhance cognition and performance, and blue
light with higher luminance levels may also enhance arousal (Lehrl et al., 2007). Conversely,
cool colours are also reported as being calming (Madden, Hewett, & Roth, 2000), which
appears counter-intuitive noting the arousal these hues can create. Therefore, variations have
been identified in the effects of warm and cool colours, but earlier research had not defined
where the extent and characteristics associated with warm and cool colours transition from one
effect to the other.
Layout/ Array
(RLA1)
Conforming to standard scanning patterns. Design publications such as Duarte (2008) and
Gabrielle (2010) recommend that the layout of slide elements should take into account the
viewer’s expected scan path. However, identified standard scan paths (e.g. Gutenberg, F, Z, or
Zig-Zag patterns) were defined for text heavy content viewed by people from western cultures
(Bradley, 2011). Consequently, these layouts are unlikely to be as appropriate for people from
non-western cultures (Abed, 1991; Brockman, 1991; Plocher, Rau, & Choong, 2012).
Additionally, non-text layouts may be processed in very different ways (Bindemann, 2010;
Engmann et al., 2009; Suvorov, 2013). From the literature assessed in this project, it was
unclear where differing scan paths would be appropriate, and what the effects would be if
various layout approaches applied.
Layout/ Array
(RLA2)
Slide titles. Gabrielle (2010) provided clear design advice on separating the slide title from the
body text. Consequently, the draft principles included recommendations on creating this type
of separation. However, no definitive research could be identified to validate these
recommendations. This design advice therefore needed to be substantiated through an
empirical assessment.
Complexity
(RX1)
Defining the peak of the complexity curve. Information from Vitz (1966), Wang, Yang, Liu,
Cao, and Ma (2014), Berlyne (1970), Day (1967), Hillyard (1979), Roberts (2007), Thorson,
Reeves, and Schleuder (1985), McNamara, Kintsch, Songer, and Kintsch (1996), Surenda,
Nikunj, and Spears (2005), Geissler, Zinkhand, and Watson (2006), Granger (2012), Schnotz
and Kurschner (2007), and Schnotz and Rasch (2005) was coalesced to develop a framework
for selecting optimal complexity. A key element of this approach was applied within the
Complexity Curve, which is illustrated in Figure 2.
Figure 2. The Complexity Curve – Illustrating the generalised relationship between complexity
and attention, preference and interest

222 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
Attribute
(Code)
Description of the Ambiguity
This curve indicates that moderate complexity provides the optimal balance for visual aid
design. However, the literature review used to develop this Complexity Curve model identified
that there was a paucity of readily usable material that could be applied to quantify moderate
complexity. For instance, Cognitive Load Theory (CLT) provides a general framework for
understanding the complexity issues and their interaction (Schnotz & Kurschner, 2007), but it
does not directly support the definitive identification of the peak for the Complexity Curve.
This fundamental aspect of complexity was therefore unclear and required additional
investigation.
Typography
(RT1)
Serif and sans serif fonts. According to many researchers (e.g. Mackiewicz (2007); Earnest
(2003); Beymer, Russell, and Orton (2008)) there may not be a significant difference between
serif and san serif fonts for supporting readability. However, as discussed in more detail within
Hilliard (2016), it was possible that some characteristics of serif fonts (such as Times New
Roman) may positively affect readability and comprehension. This aspect therefore required
further investigation, because it was possible that some of the preceding research may not have
appropriately isolated causative factors from confounding variables, to isolate differences in
experimental outcomes.
Typography
(RT2)
Rotated text. Although a substantial amount of research has been conducted into the utilisation
of rotated text (e.g. Koriat and Norman (1985); Yu, Park, Gerold, and Legge (2010)), it was
unclear from these experiments what effects this font modification would have in a complex
visual environment. For example, it was possible that this change would reduce readability, or
that the disfluency created by this change might actually improve comprehension.
Typography
(RT3)
Bullet effects. Authors such as Gabrielle (2010) and Kosslyn (2007) propose the utilisation of
bullets to clarify and reinforce the message. Other authors such as Aspillaga (1996), and
Hilligoss and Howard (2002), recommend the specific use of meaningful icons as bullets
(e.g. 9 ). Bachfischer, Robertson, and Agnieszka (2007) suggest that using these types of
iconic bullet points can generate semiotic benefits (e.g. creating inferred meanings). However,
a detailed investigation conducted for the literature review identified a paucity of specific
empirical experimentation that would support these propositions. Further research was
therefore required.
Graphics
(RG1)
The effects of graphics in titles. According to Horton (1993) the provision of graphical content
that is directly associated with the text, can assist in generating universal understanding.
However, the literature review conducted for this project found no advice that advocated
utilising graphics in the title area, to facilitate viewer understanding. The absence of such
recommendations does not align to the possible benefits that could be generated by utilising
text and graphics in the title, to support multimodal communication. Therefore, this aspect
required additional investigation.
Animation
(RN1)
The effects of text clearing. The concept of text clearing was defined in this project, as an
approach that could help to manage visual complexity in slideware, by removing or greying-out
text and graphics after moving on to the next point. However, there appeared to be a lack of
detailed science-based evidence to support the efficacy of this approach within a complex
visual environment, like a PowerPoint presentation.
Animation
(RN2)
Multiple cueing. The term multiple cueing relates to an approach that may be of assistance in
generating attention by providing multiple visual stimuli simultaneously or in sequence.
However, researchers such as Alvarez and Franconeri (2007) indicated that when used
incorrectly, these techniques may create perceptual inhibitions that could suppress processing
of the visual information. This aspect therefore required additional investigation to determine
the optimal utilisation of these techniques.
Animation
(RN3)
Animation fly-over. Research by Moore, Mordkoff, and Enns (2007) found that the perception
of moving visual elements was influenced by (and influences) the background over which the
object moves. It was therefore assumed that moving animated objects over existing visual
elements on the screen could possibly interfere with accurate perception. However, an
extensive investigation of existing research did not disclose any experiments into the practical

Bruce Hilliard et al. 223
Attribute
(Code)
Description of the Ambiguity
implications of this effect during presentations. This aspect therefore required additional
exploration, to determine the practical consequences of animation fly-over.
Animation
(RN4)
Vertical fly-in. The default direction for fly-in animations within PowerPoint is from the
bottom. However, this approach does not accord with the advice provided by Ke, Lam, Pai,
and Spering (2013) and Tatler, Hayhoe, Land, and Ballard (2011), who indicated that horizontal
visual tracking is superior to vertical tracking. Just as importantly, Ke et al. (2013) identified
that upward vertical tracking (which is what is induced by fly-in from bottom animations) is
very poorly handled by the human perception systems. It therefore appeared apropos to
investigate whether the PowerPoint default was the most suitable approach, or whether this
form of animation is suboptimal.
Hypotheses
The 12 ambiguities identified for investigation can be aligned to the UDM as illustrated in Figure 3,
which applies the same coding used in Table 2.
Figure 3. Mapping the ambiguities and hypotheses to the UDM
This figure also shows the 15 research hypotheses selected for assessment. The first 12 of these
hypotheses aimed to directly investigate the identified ambiguities. Hypotheses H1#13 to H1#15 focussed
on assessing the aggregated outcomes of the different experiments. This integrated assessment was
intended to help determine whether previous narrowly-focussed research could be effectively integrated
to create detailed design principles, and therefore fulfil the primary aim of this research project. Table 3
outlines the hypotheses in more detail.

224 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
Table 3. The research hypotheses
Ambiguity
Investigated
Research
Hypothesis
(H1) Number
Research Hypothesis
RCB1 H1# 1 The amount, and presence or absence, of warm or cool colours affects
viewer comprehension and impressions.
RLA1 H1# 2 The application of layouts and arrays that conform to standard scanning
patterns (as listed in the draft principles) positively affects viewer
comprehension and impressions.
RLA2 H1# 3 Removing the separation and highlighting from the content slide titles
affects viewer comprehension and impressions.
RX1 H1# 4 Moderate complexity (as achieved through the application of the
identified draft principles) enhances viewer comprehension and
impressions.
RT1 H1# 5 Utilising serif fonts affects viewer comprehension and impressions,
when compared with sans serif fonts.
RT2 H1# 6 The application of rotated text in a complex visual environment affects
viewer comprehension and impressions.
RT3 H1# 7 The use of bullets, and particularly connoting bullets, affects viewer
comprehension and impressions.
RG1 H1# 8 The presence or absence of graphics in the content slide titles affects
viewer comprehension and impressions.
RN1 H1# 9 The application of text clearing (by greying-out the text as specified in
the draft principles) affects viewer comprehension and impressions.
RN2 H1# 10 The use of multiple cueing and synchronous symmetrical animation (as
specified in the draft principles) affects viewer comprehension and
impressions.
RN3 H1# 11 Animation of objects over extant visual content affects viewer
comprehension and impressions.
RN4 H1# 12 Vertical fly-in of content affects viewer comprehension and impressions.
Holistic Issues H1# 13 The integrated application of the draft principles generate better
comprehension for viewers than variations that do not apply these
principles.
H1# 14 The integrated application of the draft principles generate more positive
impressions for viewers than variations that do not apply these
principles.
H1# 15 The integrated application of the draft principles generate more positive
attention for viewers than variations that do not apply these principles.
As illustrated in the preceding table, many of these hypotheses are relatively broad, and
hence required a range of different experiments to adequately test them. Consequently, the complex
hypotheses were further delineated into sets of Key Testable Propositions (KTPs). A total of 25 KTPs
were identified and these are mapped to the ambiguities, hypotheses and UDM, as illustrated in Figure 4.
This diagram shows that some KTPs just map to one hypothesis, while other hypotheses use many
KTPs. For instance, KTPs 1.A., 1.B., 1.C., 2.A., 2.B., 2.C., and 2.D. were used to support the
investigation of H1 # 1.

Bruce Hilliard et al. 225
Figure 4. Mapping the KTPs to the ambiguities, hypotheses and the UDM
The first step in testing these hypotheses was to apply the draft principles to develop experimental
presentations and associated materials. As these presentations directly reflected the aggregation of
design and science-based recommendations, the effectiveness of the draft principle integration could be
investigated holistically. These presentations were defined as the controls. Variations of these
principles-based control presentations were then created. Each of these variant presentations covered the
same material as the associated control, but the slideshow was modified in line with the KTPs being
investigated. Comprehension, impressions and attention data were then captured in the experiments, and
assessed to investigate:
xeach of the ambiguities; and
xwhether the integration of previously narrowly focussed research could be applied effectively
within a holistic design model.
These aspects, and the methodologies applied to conduct the investigation detailed in Hilliard (2016) will
be discussed in future papers.
Research Implications
The UDM, models, and principles developed through this project provide a framework that can assist
designers by:
xleveraging a wide range of science-based research and practical design advice, which helps to
separate the fact from fiction in the implementation of visual design;

226 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
xinvestigating identified ambiguities, to resolve gaps and uncertainties related to existing research;
and
xproviding this information within an integrated design methodology that addresses each of the
visual attributes individually and holistically.
The research introduced in this paper can therefore provide guidance that may be used to enhance visual
design, and also provide a consolidated framework to facilitate future science-based exploration of this
topic. The results of this project can therefore have direct implications for a range of different fields,
which include:
xEducation. As illustrated in Hilliard (2016), the application of the UDM and principles can
definitively improve comprehension, impressions, and attention outcomes in educational
situations. Consequently, the developed guidance may be applied to enhance instructional
presentations. Additionally, as a bi-product of this research, these design principles are also
likely to be useful in the creation of e-learning systems.
xOther types of presentations. These models and principles are based on elemental
psychophysical, neuroscience, cognitive, and biopsychological research. The recommendations
are therefore focussed on optimising the design, to conform with fundamental human processing
methods for visual information. As a result, the developed principles may be very broadly
generalisable, which means that they can be applied to most types of presentations and
visualisation tools. The research may therefore be of use to anyone developing presentations for
business, marketing, sales, or any other form of structured communication that applies visual aids.
xWider visual design. As discussed in the preceding point, the guidelines leveraged fundamental
aspects of human visual processing to identify methods for enhancing design. Consequently, the
resulting recommendations may also be applied to many other situations. For example, similar
techniques are likely to be applicable when designing and implementing web pages, or other
types of Graphic User Interface (GUI).
xPsychology. By integrating diverse psychological research material and then testing the
outcomes, the project provided many useful insights for research in psychology, and the
associated sub-disciplines used in this research. In particular, assimilative frameworks such as
the Attention Model, Continuum of Awareness, Complexity Curve, and Gestalt Interaction Model
developed for this project provide a constructive theoretical foundation for understanding these
issues.
Conclusion
A primary aim of this research project was to integrate diverse multidiscipline material to create a Unified
Design Model aligned to the way people process visual information. This article just introduced the
UDM, which integrates aspects related to colour, background, layout, array, typography, graphics,
animation, message structure and content, and complexity within a holistic framework.
The introduction of the UDM in this paper has also laid the foundation for the discussion of the
experiments, which will be explained in following papers. These following papers will flesh out the
concepts, to give guidance on developing presentations, web pages, or e-learning platforms.
Additionally, these frameworks can assist future researchers to develop experiments that better manage
attribute interaction.
References
1. Abed, F. (1991). Cultural influences on visual scanning patterns. Journal of Cross-Cultural Psychology,
22(4), 525-534. doi:10.1177/0022022191224006
2. Aksentijevic, A., & Gibson, K. (2012). Psychological complexity and the cost of information processing.
Theory and Psychology, 22(5), 572-590. doi:10.1177/0959354311423435

Bruce Hilliard et al. 227
3. Aldrich, H. (2008). Fight PowerPoint Abuse! Retrieved from
http://www.unc.edu/~healdric/Powerpoint.html
4. Altaboli, A., & Lin, Y. (2011). Investigating effects of screen layout elements on interface and screen
aesthetics. Advances in Human-Computer Interaction, 1-10. doi:10.1155/2011/659758
5. Alvarez, G. A., & Franconeri, S. L. (2007). How many objects can you track?: Evidence for a resource-
limited attentive tracking mechanism. Journal of Vision, 7(13). doi:10.1167/7.13.14
6. Aspillaga, M. (1996). Perceptual foundations in the design of visual displays. Computers in Human Behavior,
12(4), 587-600.
7. Bachfischer, G., Robertson, T., & Agnieszka, Z. (2007). Understanding influences of the typographic quality
of text. Journal of Internet Commerce, 6(2), 97-122.
8. Balfanz, R., Herzog, L., & Mac Iver, D. (2007). Preventing student disengagement and keeping students on
the graduation path in urban middle-grades schools: Early identification and effective interventions.
Ecological Psychology, 42(4), 223-235.
9. Bedwell, J. S., Brown, J. M., & Orem, D. M. (2008). The effect of red background on location backward
masking by structure. Perception and Psychophysics, 70(3), 503-507.
10. Berlyne, D. E. (1970). Novelty, complexity and hedonic value. Perception and Psychophysics, 8(5A),
279-286.
11. Berman, M. (2007). Street smart advertising: How to win the battle of the buzz. Lanham, Maryland, USA:
Rowman & Littlefield.
12. Betz, T., Kietzmann, T. C., Wilming, N., & König, P. (2010). Investigating task-dependent top-down effects
on overt visual attention. Journal of Vision, 10(3). doi:10.1167/10.3.15
13. Beymer, D., Russell, D., & Orton, P. (2008). An eye tracking study of how font size and type influence online
reading. Retrieved from London, UK: http://www.bcs.org/upload/pdf/ewic_hc08_v2_paper4.pdf
14. Bindemann, M. (2010). Scene and screen center bias early eye movements in scene viewing. Vision
Research, 50(23), 2577-2587.
15. Bradley, S. (2011). 3 Design layouts: Gutenberg diagram, Z-Pattern, and F-Pattern. Retrieved from
http://www.vanseodesign.com/web-design/3-design-layouts/
16. Bravo, M. J., & Farid, H. (2006). Object recognition in dense clutter. Perception and Psychophysics, 68(6),
911-918.
17. Brockman, R. J. (1991). The unbearable distraction of colour. IEEE transactions on professional
communication, 34(3), 153-159.
18. Brown, V. (2007). The power of PowerPoint: Is it in the user or the program? Childhood Education, 83(4),
231-233.
19. Chaiken, S., & Eagly, A. H. (1976). Communication modality as a determinant of message persuasiveness
and message comprehensibility. Journal of Personality and Social Psychology, 34(4), 605-614.
doi:10.1037//0022-3514.34.4.605
20. Coleman, M. B. (2009). PowerPoint” is not just for business presentations and college lectures: Using
“PowerPoint” to enhance instruction for students with disabilities. Teaching eEceptional Children Plus, 6(1).
21. Cummings, M. L., & Tsonis, C. G. (2006). Partitioning complexity in air traffic management tasks. The
International Journal of Aviation Psychology, 16(3), 277-295. doi:10.1207/s15327108ijap1603_3
22. Daggett, W. R., Cobble, J. E., & Gertel, S. J. (2008). Color in an optimal learning environment. Retrieved
from http://www.leadered.com/pdf/color%20white%20paper.pdf
23. Day, H. (1967). Evaluations of subjective complexity, pleasingness and interestingness for a series of random
polygons varying in complexity. Perception and Psychophysics, 2(7), 281-286.
24. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2007). Attention cueing as a means to
enhance learning from an animation. Applied Cognitive Psychology, 21(6), 731-746. doi:10.1002/acp.1346
25. De Westelinck, K., Valcke, M., De Craene, B., & Kirschner, P. (2005). Multimedia learning in social
sciences: Limitations of external graphical representations. Computers in Human Behavior, 21(4), 555-573.
26. Donderi, D. C. (2006). Visual complexity: A review. Psychological Bulletin, 132(1), 73-97.
doi:10.1037/0033-2909.132.1.73

228 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
27. Dorr, M., Martinetz, T., Gegenfurtner, K. R., & Barth, E. (2010). Variability of eye movements when viewing
dynamic natural scenes. Journal of Vision, 10(10). doi:10.1167/10.10.28
28. Duarte, N. (2008). Slide:ology. Sebastopol, California, USA: O’Reilly Media.
29. Earnest, W. J. (2003). Developing strategies to evaluate the effective use of electronic presentation software
in communication education. (Doctor of Philosophy), The University of Texas, Austin, Texas, USA.
30. Engmann, S., Hart, B. M., Sieren, T., Onat, S., König, P., & Einhäuser, W. (2009). Saliency on a natural
scene background: Effects of color and luminance contrast add linearly. Attention, Perception and
Psychophysics, 71(6), 1337-1352. doi:10.3758/app.71.6.1337
31. Epstein, R. (2005). The cortical basis of visual scene processing. Visual Cognition, 12(6), 954-978.
doi:10.1080/13506280444000607
32. Fondren, W. E. (2009). Warning-side effects may not include paying attention: Variables that effect attention
to warning information in direct-to-consumer advertisements. (Ph.D.), The University of Alabama, Alabama,
USA. (3369741)
33. Fritschi, J. (2008). Examining pre-service instructor’s use of PowerPoint based on pre-service students’
perceptions: A mixed methods study. (Doctor of Philosophy), The University of Alabama at Birmingham,
Birmingham, Alabama, USA.
34. Gabrielle, B. R. (2010). Speaking PowerPoint. The new language of business. The business leader’s guide
to boardroom-style slides. Sevierville, Tennessee, USA: Insignt Publishing.
35. Gabrielle, B. R., & Alvarez, G. (2012). The top 35 books on presentations. Retrieved from
http://www.slideshare.net/gonalvmar/the-top-35-books-on-presentations-14642219
36. Geissler, G. L., Zinkhan, G. M., & Watson, R. T. (2006). The influence of home page complexity on
consumer attention, attitudes and purchase intent. Journal of Advertising, 35(2), 69-80.
37. Granger, B. P. (2012). Enhancing training outcomes in the context of e-Learning: The impact of objective
learner control, training content complexity, cognitive load, learning goal orientation, and metacognitive
strategies. (3545794 Ph.D.), University of South Florida, Florida, USA.
38. Green, R. (1981). Remembering ideas from text: The effect of modality of presentation. British Journal of
Educational Psychology, 51(1), 83-89. doi:10.1111/j.2044-8279.1981.tb02458.x
39. Gu, X., Liu, X., Van Dam, N. T., Hof, P. R., & Fan, J. (2013). Cognition–motion integration in the anterior
insular cortex. Cerebral Cortex, 23(1), 20-27. doi:10.1093/cercor/bhr367
40. Hanke, J. (1998). The psychology of presentation visuals. Presentations, 12(5), 42-51.
41. Henderson, J. M., & Hollingworth, A. (1999). High-level scene perception. Annual Review of Psychology, 50,
243-271.
42. Henderson, J. M., Williams, C. C., Catstelhano, M. S., & Falk, R. J. (2003). Eye movements and picture
processing during recognition. Perception and Psychophysics, 65(5), 725-734.
43. Hilliard, B. A. (2016). Optimising viewer comprehension and shaping impressions and attention: through the
formatting of content in tools like Microsoft PowerPoint. (PhD), Murdoch University, Perth, Western
Australia.
44. Hilligoss, S., & Howard, T. (2002). Visual communication: A writer’s guide (2nd ed.). New York, New York,
USA: Longman Publishers.
45. Hillyard, A. L. (1979). Stimulus complexity during original learning and generalization. (0353229 Ph.D.),
University of Alberta (Canada), Alberta, Canada.
46. Horton, W. (1993). The almost universal language: Graphics for international documents. Technical
Communication, 40, 682-682.
47. Huff, M., & Schwan, S. (2011). Integrating information from two pictorial animations: Complexity and
cognitive prerequisites influence performance. Applied Cognitive Psychology, 25(6), 878-886.
doi:10.1002/acp.1762
48. James, K. E., Burke, L. A., & Hutchins, H. M. (2006). Powerful or pointless? Faculty versus student
perceptions of PowerPoint use in business education. Business Communication Quarterly, 69(4), 374-396.
doi:10.1177/1080569906294634
49. Jamet, E., Gavota, M., & Quaireau, C. (2008). Attention guiding in multimedia learning. Learning and
Instruction, 18(2), 135-145. doi:10.1016/j.learninstruc.2007.01.011

Bruce Hilliard et al. 229
50. Jiang, Y. V., Sigstad, H. M., & Swallow, K. M. (2013). The time course of attentional deployment in
contextual cueing. Psychonomic Bulletin and Review, 20(2), 282-288. doi:10.3758/s13423-012-0338-3
51. Jones, S. L. (1997). A guide to using colour effectively in business communication. Business Communication
Quarterly, 60, 76-88.
52. Ke, S. R., Lam, J., Pai, D. K., & Spering, M. (2013). Directional asymmetries in human smooth pursuit eye
movements. Investigative Ophthalmology and Visual Science, 54(6), 4409-4421.
53. Kim, S., Yoon, M., Whang, S. M., Tversky, B., & Morrison, J. B. (2007). The effect of animation on
comprehension and interest. Journal of Computer Assisted Learning, 23(3), 260-270. doi:10.1111/j.1365-
2729.2006.00219.x
54. Koch, B. E. (2011). Human emotion response to typographic design. (Ph.D.), University of Minnesota,
Minneapolis, Minnesota, USA. (3490660)
55. Koriat, A., & Norman, J. (1985). Reading rotated words. Journal of Experimental Psychology: Human
Perception and Performance, 11(4), 490-508. doi:http://dx.doi.org/10.1037/0096-1523.11.4.490
56. Kose, E. (2008). Modelling of colour perception of different age groups using artificial neural networks.
ScienceDirect, 34, 2129-2139.
57. Kosslyn, S. M. (2007). Clear and to the point. 8 psychological principles for compelling PowerPoint
presentations
58. Kyndt, E., Dochy, F., Sruyven, K., & Cascallar, E. (2011). The perception of workload and task complexity
and its influence on student’s approaches to learning: A study in higher education. European Journal of
Psychology of Education, 26(3), 393-415.
59. Lang, A., Park, B., Sanders-Jackson, A. N., Wilson, B. D., & Wang, Z. (2007). Cognition and emotion in TV
message processing: How valence, arousing content, structural complexity, and information density affect the
availability of cognitive resources. Media Psychology, 10(3), 317-338.
60. Larson, A. M., & Loschky, L. C. (2009). The contributions of central versus peripheral vision to scene gist
recognition. Journal of Vision, 9(10). doi:10.1167/9.10.6
61. Lehrl, S., Gerstmeyer, K., Jacob, J. H., Frieling, H., Henkel, A. W., Meyrer, R., . . . Bleich, S. (2007). Blue
light improves cognitive performance. Journal of Neural Transmission, 114(4), 457-460.
62. Lowe, R. K., & Boucheix, J.-M. (2011). Cueing complex animations: Does direction of attention foster
learning processes? Learning and Instruction, 21(5), 650-663.
63. Mackiewicz, J. (2007). Audience perceptions of fonts in projected PowerPoint text slides. Communication,
54(3), 295-307.
64. Madden, T. J., Hewett, K., & Roth, M. S. (2000). Managing images in different cultures: A cross-national
study of colour meanings and preferences. Journal of International Marketing, 8(4), 90-107.
65. Mahin, L. (2004). Powerpoint pedagogy. Business Communication Quarterly, 67(2), 219-222.
doi:10.1177/1080569904672010
66. Makaramanee, R. (1985). Pictorial stimulus complexity in texbooks (Design, Visual Aids, Grades 1-12
Analysis). (8528347 Ph.D.), Texas A&M University, College Station, Texas, USA.
67. Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle and
high school years. American Educational Research Journal, 37(1), 153-184.
68. Massachusetts General Hospital. (2009). Color me creative: How color affects the brain; Lightwave
frequencies associated with different colors can cause changes in mood, attention, and more. Mind, Mood and
Memory, 5(5), 3.
69. Matsukura, M., Luck, S. J., & Vecera, S. P. (2007). Attention effects during visual short-term memory
maintenance: Protection or prioritization? Perception and Psychophysics, 69(8), 1422-1434.
70. Matsumoto, D. (2009). The Cambridge dictionary of psychology: Cambridge University Press.
71. Mayer, R. E. (2001). Multi-media learning. Cambridge, UK: Cambridge University Press.
72. McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better?
Interactions of text coherence, background knowledge, and levels of understanding in learning from text.
Cognition and Instruction, 14(1), 1-43. doi:10.2307/3233687
73. Medley, S., & Haddad, H. (2011). The realism continuum, representation and perception. The International
Journal of the Image, 1(2), 145-156.

230 Delivering A Unified Design Model (UDM) - To Align Design to the Way the Human Brain ...
74. Mehta, R., & Zhu, R. (2009). Blue or red? Exploring the effect of color on cognitive task performances.
Science, 323(5918), 1226-1229. doi:10.1126/science.1169144
75. Mineo, B. A., Peischl, D., & Pennington, C. (2008). Moving targets: The effect of animation on identification
of action word representations. AAC: Augmentative & Alternative Communication, 24(2), 162-173.
76. Moore, C. M., Mordkoff, J. T., & Enns, J. T. (2007). The path of least persistence: Object status mediates
visual updating. Vision Research, 47(12), 1624-1630.
77. Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning - The role of modality and
contiguity. Journal of Educational Psychology, 91(2), 358-358.
78. Nouri, H., & Shahid, A. (2005). The effect of PowerPoint presentations on student learning and attitudes.
Global Perspectives on Accounting Education, 2, 53-73.
79. Otsuka, S., & Kawaguchi, J. (2007). Natural scene categorization with minimal attention: Evidence from
negative priming. Perception and Psychophysics, 69(7), 1126-1139.
80. Parette, H. P., Blum, C., Boeckmann, N. M., & Watts, E. H. (2009). Teaching word recognition to young
children who are at risk using Microsoft® PowerPoint(TM) coupled with direct instruction. Early Childhood
Education Journal, 36(5), 393-401.
81. Park, J., & Feigenson, N. (2013). Effects of a visual technology on mock juror decision making. Applied
Cognitive Psychology, 27(2), 235-246. doi:10.1002/acp.2900
82. Parks, C. M., Murray, L. J., Elfman, K., & Yonelinas, A. P. (2011). Variations in recollection: The effects of
complexity on source recognition. Journal of Experimental Psychology Learning Memory and Cognition,
37(4), 861-873.
83. Pathiavadi, C. S. (2009). Exploring efficient design approaches for display of multidimensional data to
facilitate interpretation of information. (3420611 Ph.D.), University of South Florida, Florida, USA.
84. Pett, D., & Wilson, T. (1996). Colour research and its application to the design of instructional materials.
Educational Technology Research and Development, 44(3), 19-35.
85. Plocher, T., Rau, P.-L. P., & Choong, Y.-Y. (2012). Cross-cultural design. In G. Salvendy (Ed.), Handbook of
Human Factors and Ergonomics (4th ed., pp. 162-191). Hoboken, New Jersey, USA: John Wiley & Sons,
Inc.
86. Pralle, M. J. (2007). Visual design in the online learning environment. (M.F.A.), Iowa State University,
Ames, Iowa, USA. (1446035)
87. Rayner, K., Reichle, E. D., Stroud, M. J., Williams, C. C., & Pollatsek, A. (2006). The effect of word
frequency, word predictability, and font difficulty on the eye movements of young and older readers.
Psychology and Aging, 21(3), 448-448.
88. Rebetez, C., Bétrancourt, M., Sangin, M., & Dillenbourg, P. (2010). Learning from animation enabled by
collaboration. Instructional Science, 38(5), 471-485.
89. Reynolds, G. (2010). Presentation zen design : Simple design principles and techniques to enhance your
presentations. Berkeley, California, USA: New Riders.
90. Reynolds, G. (2012). Presentation Zen - Simple Ideas on Presentation Design and Delivery K. Johnson (Ed.)
91. Roberts, M. N. (2007). Complexity and aesthetic preference for diverse visual stimuli. (Doctoral), Universitat
de les Illes Balears, Palma, Spain.
92. Sanocki, T., & Dyson, M. C. (2012). Letter processing and font information during reading: Beyond
distinctiveness, where vision meets design. Attention, Perception and Psychophysics, 74(1), 132-145.
doi:10.1016/0042-6989(71)90087-3
93. Sanocki, T., Michelet, K., Sellers, E., & Reynolds, J. (2006). Representations of scene layout can consist of
independent, functional pieces. Perception and Psychophysics, 68(3), 415-427.
94. Sanocki, T., Sellers, E., Mittelstadt, J., & Sulman, N. (2010). How high is visual short-term memory capacity
for object layout? Attention, Perception and Psychophysics, 72(4), 1097-1109. doi:10.3758/app.72.4.1097
95. Schnotz, W., & Kurschner, C. (2007). A reconsideration of Cognitive Load Theory. Educational Psychology
Review, 19, 469-508.
96. Schnotz, W., & Rasch, T. (2005). Enabling, facilitating, and inhibiting effects of animations in multimedia
learning: Why reduction of cognitive load can have negative results on learning. Educational Technology,
Research and Development, 53(3), 47-58.

Bruce Hilliard et al. 231
97. Schoeneborn, D. (2013). The pervasive power of PowerPoint: How a genre of professional communication
permeates organizational communication. Organization Studies, 34(12), 1777-1801.
doi:10.1177/0170840613485843
98. Surenda, N. S., Nikunj, D., & Spears, N. (2005). Understanding web home page perception. European
Journal of Information Systems(14), 288-302.
99. Suvorov, R. (2013). Interacting with visuals in L2 listening tests: An eye-tracking study. (3597397 Ph.D.),
Iowa State University, Ann Arbor, Michigan, USA, USA.
100. Tangen, J. M., Constable, M. D., Durrant, E., Teeter, C., Beston, B. R., & Kim, J. A. (2011). The role of
interest and images in slideware presentations. Computers and Education, 56, 865-872.
101. Tatler, B. W., Hayhoe, M. M., Land, M. F., & Ballard, D. H. (2011). Eye guidance in natural vision:
Reinterpreting salience. Journal of Vision, 11(5). doi:10.1167/11.5.5
102. Taylor, C. (2013). Design guru slams NSA’s PowerPoint skills. Retrieved from
http://mashable.com/2013/06/07/prism-nsa-powerpoint-tufte/
103. Thompson, C. (2003). PowerPoint makes you dumb. Retrieved from
http://www.nytimes.com/2003/12/14/magazine/14POWER.html
104. Thorson, E., Reeves, B., & Schleuder, J. (1985). Message complexity and attention to television.
Communication Research, 12(4), 427-454.
105. Tileagă, C. (2011). Context, mental models and discourse analysis. Journal of Sociolinguistics, 15(1), 124-
134. doi:10.1111/j.1467-9841.2010.00475.x
106. Tufte, E. R. (1990). Envisioning information. Cheshire, Connecticut, USA: Graphics Press.
107. Tufte, E. R. (2003). The cognitive style of PowerPoint. Cheshire, Connecticut, USA: Graphics Press.
108. Tufte, E. R. (2006). Beautiful evidence. Cheshire, Connecticut, USA: Graphics Press.
109. Tufte, E. R. (2007). The visual display of quantitative information (2nd ed.). Cheshire, Connecticut, USA:
Graphics Press.
110. Vitz, P. C. (1966). Preference for different amounts of visual complexity. Psychology / Social Sciences
(General), 11(2), 105-114.
111. Wang, Q., Yang, S., Liu, M., Cao, Z., & Ma, Q. (2014). An eye-tracking study of website complexity from
cognitive load perspective. Decision Support Systems, 62, 1-10.
112. Wästlund, E., Norlander, T., & Archer, T. (2008). The effect of page layout on mental workload: A dual-task
experiment. Computers in Human Behavior, 24(3), 1229-1245.
113. Wolfe, J. M., Võ, M. L. H., Evans, K. K., & Greene, M. R. (2011). Visual search in scenes involves selective
and nonselective pathways. Trends in Cognitive Sciences, 15(2), 77-84.
114. Yu, D., Park, H., Gerold, D., & Legge, G. E. (2010). Comparing reading speed for horizontal and vertical
English text. Journal of Vision, 10(2). doi:10.1167/10.2.21