Visualization in Mathematics, Reading and Science Education

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The accuracy of these mental schema will rely heavily on the precision with which the information is internalized. Koedinger and Anderson report that once information has been internalized it is organized into coherent patterns called chunks. This chunking may be followed by selecting and rearranging of information, cognitive processes that require a greater cognitive effort and attention.

All these principles reflect the behaviour of the cognitive system towards new visual information that has been perceived. Research in molecular biology has also confirmed the applicability of these Gestalt principles among students studying theoretical concepts. For example, Novick and Catley indicate that students have more learning difficulties with understanding phylogenetic ladders compared with phylogenetic trees. This is because the Gestalt principle of good continuation proximity obscures the hierarchical structure of ladders which is not the case with phylogenetic trees. The Gestalt principles.

In A , the principle of closure signifies our tendency to see complete figures even when part of the information is missing. In such a diagram we perceive three black circles covered by a white triangle, even though it could just as easily be three incomplete circles. In B , as stipulated by the principle of proximity, those parts that are closest together, we perceive the group 1 as three vertical lines of dots and the group 2 as three horizontal lines of dots. The dots in 3 are equally spaced and do not suggest an orientation. Hence in C , we see separate white diagonal lines and black diagonal lines rather than vertical or horizontal lines of black and white dots.

This student seemed to lack conceptual meaning associated with the visual model presented. As a result, extracting meaningful knowledge i. IVM is limited and misconceptions develop. ER in which students perceived the electron cloud as a background adapted from Mnguni By implication therefore, IVM is linked to the availability of conceptual knowledge from long term memory.

Once information has been successfully internalized, CVM follows. According to Mast et al. A number of studies have been conducted to understand what exactly occurs when students view visual models leading to CVM. One such study was conducted by DeSantis and Housen who investigated how students process information when viewing artistic work. The Housen model used to characterize people into different stages of cognitive processing based on their actions as they view visual models DeSantis and Housen , p.

In the accountive stage, students conceptualize visual models based on what is known and also what is liked as found in their long term memory DeSantis and Housen ; Housen In the constructive stage, students employ logical and accessible tools of knowledge to make judgements about the visual model DeSantis and Housen ; Housen In the classifying stage students attempt to classify what is perceived into categories that occur in their memory DeSantis and Housen ; Housen In the interpretive stage students allow the meaning of the work to unfold rather than them imposing it DeSantis and Housen ; Housen And finally, in the re-creative stage students allow an establishment of varying meanings each time they view an image, even if they had a previous meaning DeSantis and Housen ; Housen In this regard prior knowledge is used to make new discoveries about the image at hand.

Visualizations and Visualization in Mathematics Education | SpringerLink

According to DeSantis and Housen , students tend to move from one stage to the next based on factors such as gain of new knowledge and experience in the field. The overall process is influenced by the quality of experiences in the physical and social world, together with the drive for equilibrium. Equilibrium is the balance between the process of assimilation and accommodation, where assimilation is the fitting of new information into an existing mental structure and accommodation is the creation of new schemata knowledge structures or modification of an existing schema Thompson Research is deficient regarding the applicability of the Housen model in science education.

However the model has sensible theoretical basis. The CVM can also be understood according to the dual coding and the constructivist theories. According to the dual coding theory Wastelinck et al. The theory states that human cognition is capable of dealing with verbal or linguistic and non-verbal knowledge as independent knowledge structures in their own right Wastelinck et al.

Through referential connections, the two systems work together to construct and integrate mental visual models which are then memorized and stored in the long term memory Clark and Paivio However, according to the limited capacity theory the working memory has a limited capacity for holding and manipulating information Mayer and Anderson This limited capacity suggests that if the visual-pictorial channel is presented with enormous visual information it can be overwhelmed and fail to integrate information properly Whelan ; Mayer and Anderson The resulting overload leads to an inability to process new information effectively and hence, the construction of mental visual models is compromised.

Therefore, effective CVM depends very much on the amount of information presented to each of the cognitive channels. McClean et al. Their argument is that animations and the lecture allow students to process information using the two channels. This is further enhanced when students work with the animation at their preferred pace which ensures that their cognitive structures are not overwhelmed. Mnguni argues that the ability to recognize which is IVM and interpret visual models of a concept that is represented in different orientations is an example of CVM.

What this example illustrates also is that visualization cannot be understood in isolation, instead there is always a certain degree of content linked to it.


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Two ERs where students were required to observe the differences in orientation of the amino acids adapted from Mnguni A A depiction of Alanine as a ball-and-stick model with an electron cloud, B a depiction of alanine using a stick model. Visualization also involves EVM which is expressing mental visual models which occurs in the mind as external visual models in the form of drawings for instance or verbal descriptions. According to Rundgren et al.

These are the macroscopic level, the microscopic level, and symbolic level. In the macroscopic level students attempt to produce a visual model of the phenomenon as they directly experienced it through any of their senses. In the microscopic level, students attempt to produce a visual model of phenomena as they exist in nature, even though such phenomena cannot be observed directly with the naked eye, meaning that students may not have any previous direct experience with the phenomena.


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In the symbolic level the visual model produced by students is a qualitative abstraction such as a mathematical model which is used to represent phenomena. Examples include a chemical equation of glucose metabolism which attempts to explain a metabolic process which cannot be directly observed. Stokes suggests that the production of a visual model i. EVM is a process where a student expresses a mental visual model into an external visual model. West argues that some students may attempt to express the mental model externally in the exact way that it occurs in their mind, even though this may be difficult to do.

In other cases however, a mental visual model may be expressed externally in a different format to that in which it occurs in the mind, e. It is critical to state that expressing mental models as external visual models depends on various factors such as intelligences. Also, logical-mathematical intelligence would play a role in the expression of mental visual models numerically.

Visualization in Secondary Math and Science

As a result, it may be suggested that the manner in which students express visual models depends highly on their cognitive and physical abilities. To test for EVM, Mnguni asked students to study i. IVM and CVM part of a biochemical process with parts intentionally removed from the visual model and then predict and express the missing parts of such a process in a drawing.

A visual model of protein synthesis from mRNA using codons was used in this regard. However, looking at the blue box, the student fails to use the extracted information red box to express the subsequent stages which were missing in the blue box and hence, provides an incorrect outcome of the process.

Opening the Door: Teaching Students to Use Visualization to Improve Comprehension

This example demonstrate a case where students need to use content knowledge from prior knowledge to produce visual models by way of externalizing visual models. An example of a student generated diagram where the student has difficulties inferring or predicting adapted from Mnguni The above discussion presents a detailed theoretical account of the cognitive process of visualization which demonstrates the complexity of visualization. It is evident that visualization is not a linear process. Instead various interconnected actions occur, which are driven by the need to generate knowledge.

It emerges that these are dependent of prior knowledge which is used to construct new knowledge.

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Given this, it is critical therefore that visual literacy education be formalized in a similar way to other competencies such as content literacy McKenna and Robinson , academic communication literacy Spektor-Levy et al. Furthermore, the author argues that teachers need to be alerted to the complexity of visualization and its significant, in order to assist them develop tools with which learning difficulties could be minimized.

Science education teachers need to be able to identify the source of a learning difficulty associated with visualization and use appropriate remedial strategies to assist students. For example, it is important that teachers understand the significance of each of the stages of the theoretical cognitive process of visualization so that they can design relevant instructional strategies to facilitate learning. Given this, it is important that the visualization skills be identified within the context of visual literacy for science education.

To this end, the following applications need to be considered in order to better understand, teach or study visual literacy in science education:. It is particularly important in science, which seeks causal explanations for phenomena in the world-as-experienced. Visualization must therefore play a major role in science education. This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages, especially in chemistry.

The first section explores the significance and intellectual standing of visualization. The second section shows how the skills of visualization have been developed practically in science education.

This is followed by accounts of how the educational value of visualization has been integrated into university courses in physics, genomics, and geology. By continuing to use this site you agree to our use of cookies. To find out more, see our Privacy and Cookies policy. Close this notification. Journal of Physics: Conference Series. Download Article PDF. Share this article.

Article information. Author e-mails. Cook M P Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles Science education 90 Crossref Google Scholar.