visualisation skills web simulation

ADRIAN TWISSELL

© Dr A Twissell 2017

Visualisation SkillsForms

Learning Strategy Reference:Web Simulation May 2017

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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 FormsThe term visualisation describes graphic artefacts, such as pictures, diagrams, schematics and many other graphic models.

Visualisation ProcessesVisualisation is also used to describe the process of creating, recognising, organising and manipulating structured visual imagery.

Teaching & Learning StrategiesThinking with graphic models provides a cognitive mechanism which supports learning with external representations and internal mental models.

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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

© Dr A Twissell 2017Visualisation 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 simplifiedand 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

© Dr A Twissell 2017Visualisation Forms Visualisation ProcessesGo to

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).5

Five


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.


http://bejlt.brookes.ac.uk/