Visualisation Forms and Processes Guide

ADRIAN TWISSELL
© Dr A Twissell 2017
Visualisation SkillsForms
Learning Strategy Reference:
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This resource provides information about visual
forms, visualisation processes and links to learning
strategies useful in the development of
visualisation skills and conceptual understanding.
Information is linked with the theoretical literature
and learning strategies are based on empirical
research where possible.
Learning strategy reference: Web-based modelVisualisation Skills
VisualisationVisual Forms
The term visualisation describes graphic artefacts, such as
pictures, diagrams, schematics and many other graphic models.
Visualisation Processes
Visualisation is also used to describe the process of creating,
recognising, organising and manipulating structured visual
imagery.
Teaching & Learning Strategies
Thinking with graphic models provides a cognitive mechanism
which supports learning with external representations and
internal mental models.
Go to Background To This Resource

Visualisation Forms
• Concrete experience
• Dual coding-verbal/non-verbal
representation
• Foundation/grounded metaphor
• Levels of representation
(Observable, symbolic)
• Representation (visual forms)
• Spatial location
• Visual analogue
• Visual stimulus
Visualisation ProcessesGo to

Visualisation Forms: Concrete experience
Concrete representational forms include
pictures, photographs, drawings and
illustrations. They represent unambiguous
information, which can be related to referents
‘in the real world’.
‘Surface’ is also used to describe elements of
representations which are readily observed or
understood (Seufert and Brunken, 2006).
Concrete is opposite to abstract, which
describes referents which may be ambiguous
or generalised to the point where information
requires greater knowledge to enable
translation.
 Links with whole-to-parts.
 Begin with real-world examples as
concrete referents, then develop
abstractions (see Levels of
Representation).
 Link with Foundation/Grounded
Metaphor and use of early-years
experiences
Teaching & Learning Applications
Visualisation Forms Visualisation ProcessesGo to

Visualisation Forms: Dual Coding Theory
Dual Coding Theory (Paivio, 1986) - the use of
verbal (sequential) and nonverbal (synchronous)
mental processes and referents to support
memory, thinking and learning.
Dual Coding Theory links stimuli in verbal and
nonverbal form to responses, also in verbal and
nonverbal form, through a system of
representational and referential connections.
The use of variability of learning has been
shown to predict future learning (Siegler, 2005)
by encouraging different approaches, strategies
and tools. Here this relates to the use of verbal
and nonverbal referents in support of thinking
and learning.
 Emphasise word and image to
strengthen understanding on the basis of
multiple referents.
 Use word and image to encourage
variability of learning (Siegler, 2005).
 Provide opportunities to transform
words and images (link with
Transformation)
 Words explain. Images aid memory and
recall (Aleven and Koedinger, 2002).

Visualisation Forms: Foundation/Grounded Metaphor
Foundation metaphor, also referred to as
grounded metaphor (see Ritchie, 2013),
describes the meaning attached to experience,
often gained through the early years.
Foundations can include phenomena such as
height and temperature.
Learners apply the foundation metaphor to
support thinking in new situations, such as
describing voltage as ‘high’ or ‘low’.
 Emphasise common metaphors to
support learning in new situations.
 Cross referencing meaning in this
way can strengthen understanding,
memory and the development of
metaphorical models (Sibbet, 2008).

Visualisation Forms: Levels of Representation
Levels of representation (Johnstone, 1993; Wu et al.
2001):
 Observable – representations (and phenomena
they represent) are readily observable ‘in the real
world’. These include pictures, illustrations,
animations (2D media) and physical models (3D
media) that can be observed and manipulated in
real time.
 Symbolic – representations that may be simplified
and abstracted to characterise a phenomenon,
including symbols, numbers, letters, formulas and
equations. Can assist ‘search-recognition-inference’
techniques (Larkin and Simon, 1987).
 Abstract (see also Levels of Representation:
Abstract)– phenomena are represented in a form
not immediately related to first hand experience ‘in
the real world’, e.g., metaphorical representation.
 Use different levels to enhance
understanding about complex
abstract concepts.
 Begin with observable, tangible
referents.
 Incorporate transitions between
levels in activities to develop deeper
understanding of phenomena.
 Emphasise the referential elements
that enable transition.

Visualisation Forms: Graphic Representation
• The term representation can refer to a wide range of
2D graphic referents, including: symbols, pictures,
icons, illustrations, animations, schematics, sectional
drawings, exploded drawings, cutaways, orthographic
and isometric drawings.
• Representation can also refer to 3D modelling
including: block models, rapid prototyping, 3D printing
and electronic prototyping.
• Many representations are now produced virtually
using software to create 2D and 3D on-screen models.
 Use icons to aid text recall and learning about
textual features (see Griffen and Robinson,
2005; Steiner, 1974).
 Use icons to represent information and reduce
cognitive load.
 Emphasise the information attached to a
representation and practise
translation/transition to aid variability of
learning.
Symbol Schematic Section Exploded Cutaway Orthographic Isometric

Visualisation Forms: Spatial Location
Spatial location refers to the proximity of
elements of representations, the position of
which can help (if closely located), or hinder
(when remotely located).
Diagrammatic representations provide a
search efficiency absent from written
sentences, or sentential representations,
because multiple aspects of the same
object/phenomenon can be accessed at the
same time, or simultaneously (Larkin and
Simon, 1987).
 Locate elements that relate to one another
together to aid search and recognition (see
Larkin and Simon, 1987).
 Emphasise associations through grouping
to speed up search strategies.
 Emphasise standard forms e.g., circuit
diagrams are normally organised with
power source, input, process and output
spatially located left to right. This informs
the learner about the nature of the
elements located in those positions.
 Contrast synchronous representation with
sentential representation. Encourage
diagrammatic representation
transformation to access the power of
explanation using sentences.

Visualisation Forms: Visual Analogue
The creation of a mental picture representing
external phenomena. Visual analogues are
thought to support spatial operations such as
rotating an object within virtual 3 dimensional
space (see Shepard and Metzler, 1971; Zacks,
2008). See Spatial Visualisation/Rotation.
 Provide opportunities for manual
manipulation that replicates the
mental operation.
Shepard and Metzler’s (1971) mental rotation task

Visualisation Forms: Visual Stimulus
Visual stimuli are things in the environment
that provoke responses, thoughts or actions.
Within the context of representation use,
visual stimuli may include verbal and
nonverbal stimuli (see Dual Coding Theory).
The observer may process the Stimuli in
different ways, and make links with stored
knowledge in verbal or nonverbal form.
 Presentation of stimuli in different forms
leads to different responses.
 Consider how the observer may respond
to stimuli in various forms and whether
stimuli will help or hinder learning and
problem solving.
 Link with whole-to-parts – presentation
beginning with the whole stimulates
greater links with existing knowledge.

Visualisation Processes
• Analogy
• Cognitive load
• Conceptual change
• Dynamic spatial transformation
• Embodied cognition
• Levels of representation (abstract)
• Like modality perception
• Metaphor
• Object manipulation
• Object recognition
• Pattern matching
• Pattern-name association
• Redundancy
• Sequential/synchronous processing
• Spatial/object relation
• Spatial visualisation/rotation
• Subitising
• Transformation
• Transition
• Translation
• Whole-To-Parts

Visualisation Processes: Analogy
Analogy describes the process of comparing something
with something else . In electronics education, the ‘flow’
of current is often compared with the flow of water. This
provides an illustrative, recognisable referent for electric
current which cannot be observed ‘in the real world’.
See Gentner and Gentner (1983).
Analogies such as this can be limited to initial learning,
however, as they have been shown to hinder deeper
understanding and learning (Pitcher, 2014).
 Use recognisable referents to stimulate
thinking about abstract phenomena and
make links with existing knowledge.
 Choose sustainable analogies that
support learning about phenomena at
simple and complex levels.
Visual analogy using hydraulics (after Hughes and Smith, 1990: 90)

Visualisation Processes: Cognitive Load
The term cognitive load describes the mental
capacity required to translate visual
representations and understand the
phenomenon of interest.
If representation is too complex, cognitive
load increases and the observer becomes
overwhelmed.
Cognitive load can be reduced by simplifying,
removing and combining elements of
representations (see Redundancy). This leads
to increased automation during recognition
tasks (Kirschner, 2002).
 Remove unnecessary elements of
representations, particularly on first
viewing.
 Similarly simplify elements, then
introduce further information.
 Group elements to aid translation.
 Emphasise ‘codes’ that represent
elements within concepts to increase
automation. E.g., the code ‘RC Network’
represents the elements ‘resistor’,
‘capacitor’ and their spatial relationship.

Visualisation Processes: Conceptual Change
Conceptual change describes the gradual integration of new
knowledge into existing understandings. The following four
conditions are said to operate when learners undergo conceptual
change (Chen et al., 2013):
1. Learning material triggers dissatisfaction with existing
understandings
2. New concept visualisations provide intelligibility
3. Plausibility of concept is achieved when visualisation can be
matched with theoretical understanding
4. Visualisation needs to be linked with manipulation and
exploration opportunities to overcome long-standing
misconceptions
Within this model learners will hold and develop different
perspectives on phenomena at different times in their learning.
Understanding has been referred to as emergent (Chi, 2005) as
knowledge gradually develops over time.
 Use manipulation-based activities to
encourage physical engagement with
phenomena. E.g., physical modelling of
electronic circuits to simulate concepts.
 Emphasise current understandings and where
new knowledge ‘fits’ and replaces conceptual
understandings.
 Highlight links between physical
modelling/simulating and theoretical
understanding to ‘prove’ concepts.
 Develop transitions between representations,
leading to alternative perspectives on
phenomena.

Visualisation Processes: Dynamic Spatial Transformation
Dynamic spatial transformations (Clark and Paivio, 1991)
involve the use of nonverbal referents in generating
imaginary internal representations of phenomena. These
representations are personal to learners’ preferred
strategies for constructing understanding of the
phenomenon of interest (Twissell, 2016).
Dynamic spatial transformations allow visualisations such
as object rotation, image-based representations of events
and ideas and support for memory when learners are
presented with verbal and nonverbal stimuli (Clark and
Paivio, 1991). Examples include visualising the rotation of
an electronic component, movement of a relay armature,
direction of current flow in a circuit, or matching stored
knowledge concept when presented with verbal or
nonverbal stimuli.
 See Dual Coding Theory
 See Object Manipulation and
Transformation

Visualisation Processes: Embodied Cognition
Embodied cognition describes the role of
physical experience as an aid to thinking
about phenomena of interest. Shepard and
Metzler’s (1971) experiments (see Visual
Analogue), for example, show that physically
turning a handle in the same direction as a
visual rotation problem solving task decreases
the time taken to solve the problem.
Physically engaging with the problem
supports cognitive activity and task
completion.
See Davis and Markman (2012).
 Provide opportunities to support
thinking with ‘hands-on’ activity.
 In electronics education, component
placement is perfectly suited to
hands-on learning about electronics
theory.
 ‘Hands-on’ also includes
organisational activities such as card
sort.

Visualisation Processes: Levels of Representation (Abstract)
 Abstract (see also Levels of Representation)
phenomena are represented in a form not
immediately related to first hand experience
‘in the real world’, e.g., metaphorical
representation.
 Abstraction can include analogy, metaphor or
the application of theory from another area of
the field (e.g., understanding about analogue
electronics through computer programming).
 Abstractions are personal referents developed
by individuals. Even when provided within
teaching programmes, abstract
representations need to be recognised and
accepted by learners who draw them into
existing understandings (see Bruner, 1977).
 Develop abstractions from concrete
referents, such as observable examples
from the ‘real world’.
 Draw on existing knowledge as the point
of departure, even if the existing
knowledge falls outside of the field of
interest.
 Draw on the principles of transformation
and manipulation of knowledge to
enhance understanding about
phenomena (see also Variability of
Learning).

Visualisation Processes: Like Modality Perception
Like modality perception refers to the
common visualisation-based mechanism used
to process information. This is frequently
applied to visual, auditory and kinaesthetic
modes.
Research has indicated a strong visualisation
component within these modes, where
mental imagery is considered to support
thinking across the modes (Kosslyn, Ganis and
Thompson (2001).
 Emphasise imagery as support for
different modes of transmission.
 Use links between visualisation and
the mode of transmission to aid
problem solving (e.g., visualising
distance using thoughts based on
imagined physical movement-see
Kosslyn, Ganis and Thompson, 2001).

Visualisation Processes: Metaphor
Metaphor describes ‘seeing, experiencing, or
talking about something in terms of something
else’ (Lakoff and Johnson, 1980; Ritchie, 2013: 8).
Metaphors are compact representations which
allow information conversion and transfer, enable
communication and personify imagery related to
experience (Paivio and Begg, 1981).
The conversion of phenomena to metaphorical
form is thought to support learning through the
transformation/reinterpretation process.
 Use metaphor to link with existing
knowledge.
 Develop metaphor to explain
phenomena which cannot be accessed
‘in the real world’.
 Encourage personal metaphors to aid
memory and recall.
 Support with suggestions for visual
imagery or other representation.

Visualisation Processes: Object Manipulation
Object manipulation is here linked with
Conceptual Metaphor Theory (CMT).
In electronics and engineering related fields,
terms such as ‘turning on’, ‘turning off’, ‘high
voltage/low voltage’ are conceptually
metaphorical and relate to the experience of
object manipulation (e.g., turning and
rotation; dimensionally higher or lower).
See also Reinterpretation.
 Emphasise the concepts that learners
(and teachers) use as a matter of
course.
 Concepts can be easier to
understanding when the
representation is unpacked and
understood in relation to the
conceptual metaphor.
 See also Metaphor.

Visualisation Processes: Object Recognition
Object recognition describes the mental
alignment of perceived information with
stored information, leading to the recall of
experience or other prior event.
 Assist recall by ‘encoding’ the
information in a memorable way
(e.g., colour, pattern, icon,
representation type, word/image
association).

Visualisation Processes: Pattern Matching
In the pattern matching task example below (from
Gardner, 1984), visualisation skills are drawn from
spatial relation, object rotation and object
recognition strategies.
Viewers are required to decide which object view
aligns with the target form. The visualisation
strategies above are commonly employed to solve
this problem.
 In fields such as electronics education and
engineering, pattern matching strategies
can benefit the translation of diagrams and
schematics. Information which is spatially
located (see also Spatial Location) can be
accessed more efficiently when patterns
are used for search, recognition and
inference (Larkin and Simon, 1987).
 Emphasising relationships in this way
strengthens understanding and memory
(e.g., groups of circuit symbols form
patterns that embody information).
Pattern matching task (from Gardner, 1984: 170)

Visualisation Processes: Pattern-Name Association
A pattern-name association is a response
which has been developed to a particular
stimulus. It may work in either direction-a
named pattern or a pattern attached to a
name.
Link with Subitising.
 Frequent naming of number groupings
(such as on a die face) assist children in
learning about number and the
recognition of quantity without needing
to count (Bobis, 2008).
 In electronics education, arrangements
of components can be emphasised as
pattern formations and attract names
(e.g., ‘RC Network’ is used to describe
the pattern of resistor and capacitor
components arranged in series within
timing circuits).5Five
Linked pattern-name representations

Visualisation Processes: Redundancy
Redundancy refers to the parts of representations
not needed by the viewer to fully understand the
phenomena presented. As learners increase their
expertise and understanding certain features
become redundant and therefore can be
eliminated.
Redundant elements are typically represented in
other ways, such as text explanations referring to
aspects of diagrams covering the same
information.
Learners may benefit from the elimination of
redundant elements depending their stage of
development and preferred learning strategies.
See Ainsworth (2006).
 Reduce redundant elements as learners’
expertise with the representation of
interest grows (e.g., some circuit symbols
can be eliminated/replaced to reduce
cognitive load – i.e, power supply symbols
are often assumed or replaced by simple
supply rails for clarity).
 Emphasise where and how information can
be found when eliminating information
(e.g., links between logic gate symbols and
their pinout diagrams bring together two
dimensions of electronic system – both
provide enough information to support an
aspect of learning, but redundancy
enhances clarity).

Visualisation Processes: Reinterpretation
Reinterpretation, manipulation and transformation
describe similar processes whereby the learner
translates representational media and converts it
to another form (e.g., verbal to visual, between
representational types – orthographic to
isometric). See Bruner (1977).
The conversion process supports learning by
providing an additional perspective that clarifies
phenomena or provides additional information.
See Object Manipulation
/Metaphor/Transformation
 Provide opportunities to convert information from
one form to another.
 Program code is a useful reinterpretation medium
for thinking about circuit function (Twissell, 2016)
Circuit Symbol Truth Table Boolean Expression
A B F
0 0 0
0 1 0
1 0 0
1 1 1
F=A.B
Logic AND gate represented in three different ways

Visualisation Processes: Sequential/Synchronous Processing
Information can be accessed and processed sequentially,
such as text-based representations, or synchronously in
the form of graphics, icons or diagrams.
Synchronous representations allow several visual
elements to be presented at the same time, therefore
search, recognition and inference time can be reduced
(see Larkin and Simon, 1987).
Sequential representations require the observer to read
through the information step-by-step, such as words,
sentences or computer program code. Search,
recognition and inference takes longer for sequentially
presented information.
 Synchronous representations embody
information that is straightforward to
comprehend and recall, once the
information is understood.
 Sequential representations provide an
explanatory function absent from
synchronous representations (see Aleven
and Koedinger, 2002; Lauria, 2015).
 Emphasise the process of translation and
transition between these representation
types.

Visualisation Processes: Spatial/Object Relation
See Pattern Matching (spatial relation of 2D
forms)
See Whole-To-Parts (spatial relation related to
translation of 3D and 2D representations.

Visualisation Processes: Spatial Visualisation/Rotation
Spatial visualisation and spatial rotation
describes the process used to mentally rotate
a visual representation.
This is a useful skill where polarity of
electronic components is important and
allows the learner to quickly identify
misaligned elements.
See also Visual Analogue.
 Provide opportunities for manual
manipulation that replicates the mental
operation (see Visual Analogue).
 Shepard and Metzler’s (1971)
experiments showed that manual action
in the same direction as the direction of
mental rotation increased response
times, supporting the inclusion of
practical tasks in problem solving
exercises.

Visualisation Processes: Subitising
Subitising describes the identification of spatial
structure leading to object recognition and the
simultaneous inference of number value without
counting (Bobis, 2008).
Depending on grouping, arrangements can contribute
to understanding through a Part-To-Whole approach.
For example two groups of two equals four. This is
referred to as ‘Partitioning’ (Bobis, 2008).
 Spatially group objects where
numerical value is key to visual
interpretation or organisation.
 Link with Pattern-Name Association
 Link with Dual Coding Theory
 Link with Whole-To-Parts
Die faces showing spatial grouping

Visualisation Processes: Transformation
See Reinterpretation.

Visualisation Processes: Transition
Thinking about abstract phenomena often draws
from several representations (Multiple External
Representations - MERs). Moving between
representations requires a transition which has
been found to rely on personal characterisations of
knowledge (Twissell, 2016).
The analogue/digital voltage concept, for example,
was characterised by practical action, logic
systems, programmed systems and understanding
based on a dialectic appreciation of both analogue
and digital voltage behaviour (Twissell, 2016).
 Emphasise the links between MERs and
encourage the development of personal
characterisations.
 Explore learners’ different
characterisations and adapt teaching and
learning to exploit personal conceptions.

Visualisation Processes: Translation
Translation describes the connections made
between representational elements leading
to inference and the attachment of meaning.
See Ainsworth (2006).
 Link with Cognitive Load, Object
Recognition, Pattern-Name
Association and Pattern Matching.

Visualisation Processes: Whole-To-Parts
Whole-to-parts describes the use of a concrete,
recognisable referent as a starting point for
transition to more abstract representation.
This often takes the form of a 3D to 2D transition,
or pictorial to diagrammatic representation.
Whole-to-parts approaches have been shown to
support learning about complex abstract concepts
(Basson, 2002), by providing a link to real-world
example and experiences.
 Begin with real-world examples as
concrete referents, then develop
abstractions.
 Use 3D forms as starting points for the
exploration of phenomena, then use 2D
or diagrammatic representations to
develop meaning and understanding.

Whole-to-parts

Teaching and Learning Strategies
• Analogy generation and use
• Conceptual change and modify
• Dual-coded referents
• Hands-on and practical
• Interpret and reinterpret
• Levels of representation
• Metaphor generation and use
• Mix, match and relate
• Personalise and emphasise
• Pinpointing spatial location
• Recognise and organise
• Sequential representation and
explanation
• Variability of learning
• Whole-to-parts
Visualisation Forms Visualisation ProcessesGo to© Dr A Twissell 2017

Background To This Resource
This resource developed from previous literature
review (Twissell, 2014; Twissell, forthcoming) and
empirical research (Twissell, 2016), which explored
learners' visualisation skills and representation
translation in support of understanding about
complex abstract concepts. The review of
literature highlighted numerous visualisation skills
which were shown to be context dependent and
trainable.
The visualisation skills underpinned learners'
strategies for developing understanding about
abstract concepts, and were applied in ways
personal to the learner. My research (Twissell,
2016) revealed a taxonomy of four personal
learning strategies (the Operative, Logician,
Programmer and Dialectic) which were based on
the preferred use of different representation
types. Learners’ concepts were formed in
accordance with their preferred learning strategy
and use of representations.
The representation types and strategies featured
in this resource provide a visual interpretation of
the literature reviews cited above. It does not form
an exhaustive reference, but does reflect the key
literature reviewed during the period 2011-2017
within the context of cognitive psychology,
learning, electronics and engineering education.
Note: All text and graphics have been created by the author.
Where graphics have been influenced by source material
citation is given.

References/Further Information
• Ainsworth, S. (2006) DeFT: A Conceptual framework for considering learning with multiple representations, Learning and Instruction, 16(3), pp. 183-198.
• Akasah, Z. and Alias, M. (2010) Bridging the spatial visualisation skills gap through engineering drawing using the whole-to-parts approach, Australasian Journal of Engineering
Education, 16(1), pp. 81-86.
• Aleven, V. A. W. M. M. and Koedinger, K. R. (2002) An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor, Cognitive
Science, 26, pp. 147-179.
• Bobis, J. (2008) Early Spatial Thinking and the development of Number Sense, Australian Primary Mathematics Classroom, 13(3), pp. 4-9.
• Bruner, J. (1977) The Process of Education, Cambridge, Massachusetts: Harvard University Press.
• Chi, M. T. H. (2005) Commonsense Conceptions of Emergent Processes: Why some misconceptions are robust, The Journal of the Learning Sciences, 14(2), pp. 161-199.
• Clark, J. M. and Paivio, A. (1991) Dual Coding Theory and Education, Educational Psychology Review, 3(3), pp. 149-210.
• Davis, J. I. and Markman, A. B. (2012) Embodied Cognition as a Practical Paradigm: Introduction to the Topic, The Future of Embodied Cognition, Topics in Cognitive Science, 4, pp.
685-691.
• Gardner, H. (1984) Frames of mind: the theory of multiple intelligences, London: Heinemann.
• Gentner, D. and Gentner, D. R. (1983) Flowing waters or teeming crowds: Mental models of electricity. In Gentner, D. and Stevens, A. L. (Eds) Mental Models, (pp. 99-129).
Hillsdale, NJ: Lawrence Erlbaum Associates.
• Hughes, E. and Smith, I.M. (1995) Hughes Electrical Technology (7th edition), Harlow: Wiley.
• Johnstone, A. H. (1993) The Development of Chemistry Teaching, Journal of Chemical Education, 70(9), pp. 701-705.
• Kirschner, P. A. (2002) Cognitive load theory: implications of cognitive load theory on the design of learning, Learning and Instruction, 12, pp. 1-12.
• Kosslyn, S. M., Ganis, G. and Thompson, W.L. (2001) Neural Foundations of Imagery, Nature Reviews, 2, pp. 635-642.
• Lakoff, G. and Johnson, M. (1980) Metaphors we live by, Chicago: University of Chicago Press.

References/Further Information
• Larkin, J. H. and Simon, H. A. (1987) Why a Diagram is (Sometimes) Worth Ten Thousand Words, Cognitive Science, 11, pp. 65-99.
• Lauria, S. (2015) Ready, steady, program! How children can learn coding (and teach numeracy to a robot) during STEM school visit events, Brookes eJournal of Teaching and
Learning. Available from: http://bejlt.brookes.ac.uk. [Accessed: 18th January 2016].
• Paivio, A. (1986) Mental Representations: A Dual Coding Approach, New York: Oxford University Press.
• Paivio, A. and Begg, I. (1981) Psychology of Language, Englewood Cliffs, New Jersey: Prentice-Hall.
• Pitcher, R. (2014) Getting the picture: The role of metaphors in teaching electronics theory, Teaching in Higher Education, 19(4), pp. 397-405.
• Ritchie, L. D. (2013) Metaphor, New York: Cambridge University Press.
• Seufert, T. and Brunken, R. (2006) Cognitive load and the format of instructional aids for coherence formation, Applied Cognitive Psychology, 20, pp. 321-331.
• Shepard, R. N. and Metzler, J. (1971) Mental Rotation of Three-Dimensional Objects, Science, 171(3972), pp. 701-703.
• Sibbet, D. (2008) Visual Intelligence: Using the Deep Patterns of Visual Language to Build Cognitive Skills, Theory Into Practice, 47, pp. 118-127.
• Siegler, R. S. (2005) Children’s Learning, American Psychologist, 60(8), pp. 769-778.
• Steiner, G. (1974) On the Psychological Reality of Cognitive Structures: A Tentative Synthesis of Piaget’s and Bruner’s Theories, Child Development, 45, pp. 891-899.
• Twissell, A. (2014) Visualisation in applied learning contexts: A review, Educational Technology and Society, 17(3), pp. 180-191.
• Twissell, A. (2016) Mental Representation and the Construction of Conceptual Understanding in Electronics Education. Unpublished EdD thesis, Oxford Brookes University.
• Twissell, A. (forthcoming) Modelling and simulating electronics knowledge: Conceptual understanding through active agency, Journal of Educational Technology and Society.
• Wu, H.-K., Krajcik, J. S. and Soloway, E. (2001) Promoting Understanding of Chemical Representations: Students’ Use of a Visualization Tool in the Classroom, Journal of Research
In Science Teaching, 38(7), pp. 821-842.
• Zacks, J. M. (2008) Neuroimaging Studies of Mental Rotation: A Meta-analysis and Review, Journal of Cognitive Neuroscience, 20(1), pp. 1-19.

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