Dynamic Imagery: A Computational Model of Motion and Visual Analogy

Croft, David; Thagard, Paul

doi:10.1007/978-1-4615-0605-8_15

Cited by 33 publications

(9 citation statements)

References 19 publications

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“…Nicola Tesla's invention of the selfalternating current motor), and thought experiments (e.g. Albert Einstein's generating of his relativity theory's predictions) (Croft & Thagard, 2002;Mathewson, 1999;Shepard, 1988;Sims & Hegarty, 1997). Chemists use mental rotation to distinguish similar molecular structures (Stieff, 2007), and surgeons report that they mentally inspect anatomical structures during surgery (Keehner et al, 2006).…”

Section: Dynamic Imagerymentioning

confidence: 97%

Exploring Verbal, Visual and Schematic Learners' Static and Dynamic Mental Images of Scientific Species and Processes in Relation to Their Spatial Ability

Al‐Balushi

Coll

2013

International Journal of Science Education

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The current study compared different learners' static and dynamic mental images of unseen scientific species and processes in relation to their spatial ability. Learners were classified into verbal, visual and schematic. Dynamic images were classified into: appearing/disappearing, linearmovement, and rotation. Two types of scientific entities and their related processes were investigated: astronomical and microscopic. The sample included 79 female students from Grades 9 and 10. For the purpose of the study, three instruments were used. The Mental Images by Guided Imagery instrument was designed to investigate participants' visualization of static and dynamic mental images. The Water-Level Task was adopted to estimate participants' spatial ability. The Learning Styles Inventory was used to classify participants into verbal, visual and schematic learners. The research findings suggest that schematic learners outperformed verbal and visual learners in their spatial ability. They also outperformed them in their vividness of microscopic images; both micro-static and micro-dynamic images; especially in the case of appearing/disappearing images. The differences were not significant in the case of astronomical images. The results also indicate that appearing/disappearing images received the least vividness scores for all three types of learners.

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Section: Dynamic Imagerymentioning

confidence: 97%

Exploring Verbal, Visual and Schematic Learners' Static and Dynamic Mental Images of Scientific Species and Processes in Relation to Their Spatial Ability

Al‐Balushi

Coll

2013

International Journal of Science Education

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“…The ground-theme is continuously perceived by senses and processed by every biological individual automatically, as this form of biological communication between a living system and the environment is intrinsic. All that information is reflected in its analog form, and the brain operates on sensory images (Kosslyn 1978(Kosslyn , 1980Croft and Thagard 2001). As both the addresser and the addressees have common informational background, the signal (figure-rheme) draws everybody's attention to a certain circumstance that demands a spontaneous reaction from the receiver of the signal.…”

Section: On-line and Off-line Communicationmentioning

confidence: 99%

The Role of Off-line Communication in Human Evolution

Abieva

2008

Biosemiotics

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The existence of embodied communication in humans places them among other living systems and helps to differentiate sign patterns that are common to all bioforms from those that are peculiarly human. Despite the fact that the biological roots of communication have been proven, the understanding of human forms of discourse is still far from being clarified. The main question remains: when and why did humans acquire the ability to exchange messages via speech? My thesis is that it became possible only after humans made a shift from on-line to off-line interaction and learned to communicate in the interpersonal mode via externalized analog codes that constitute the various forms of human culture.

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“…The radiation problem mapping was one of the examples to which VAMP.2 was applied. Croft and Thagard [32] created a computational model DIVA which does analogical mapping using ACME. What it maps are three-dimensional visuospatial situations using representations in hierarchically organized scene graphs.…”

Section: Discussionmentioning

confidence: 99%

Visuospatial Re-Representation in Analogical Reasoning

Davies¹,

Goel²

2008

TOAIJ

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Visual and spatial representations seem to play a significant role in analogy. In this paper, we describe a specific role of visual representations: two situations that appear dissimilar non-visuospatially may appear similar when rerepresented visuospatially. We present a computational theory of analogy in which visuospatial re-representation enables analogical transfer in cases where there are ontological mismatches in the non-visuospatial representation. Realizing this theory in a computational model with specific data structures and algorithms first requires a computational model of visuospatial analogy, i.e., a model of analogy that only uses visuospatial knowledge. We have developed a computer program, called Galatea, which implements a core part of this model: it transfers problem-solving procedures between analogs that contain only visual and spatial knowledge. In this paper, we describe both how Galatea accomplishes analogical transfer using only visuospatial knowledge, and how it might be extended to support visuospatial re-representation of situations represented non-visually.

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Dynamic Imagery: A Computational Model of Motion and Visual Analogy

Cited by 33 publications

References 19 publications

Exploring Verbal, Visual and Schematic Learners' Static and Dynamic Mental Images of Scientific Species and Processes in Relation to Their Spatial Ability

Exploring Verbal, Visual and Schematic Learners' Static and Dynamic Mental Images of Scientific Species and Processes in Relation to Their Spatial Ability

The Role of Off-line Communication in Human Evolution

Visuospatial Re-Representation in Analogical Reasoning

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