Visual Thinking | Center for Teaching | Vanderbilt University
tional differences between visual and verbal information, data on eye .. This example not only illustrates a tight relationship between image and .. gories do not map seamlessly onto visual/verbal collaboration, even though. Given the differences in how visual and verbal information is new, learners may have to think carefully about the relationships between For example, Ainsworth and Loizou () found that asking .. This is most likely due to the directness of mapping complex systems to a visual-spatial format. Visual thinking is a learning style where the learner better understands and retains strategies include creating graphic organizers, diagramming, mind mapping, in ways that are easy to understand and help reveal relationships and patterns. Linked verbal and visual information helps students make connections.
Screen shot of spreadsheet annotation of verbal LSRs between clauses. When the clause did not enter into a relation with another clause, it was annotated as simplex. The example in Table 8 illustrates this type of occurrence.
Example of a clause simplex. Then Little Nutbrown Hare had a good idea. Screen shot of spreadsheet annotation of ideational meanings in verbal text.straight to the point: what is a value stream map
A spreadsheet with annotation is shown in Figure 6. Screen shot of spreadsheet annotation of ideational meanings in visual text. Verbal-visual LSRs were annotated in the central column of the spreadsheet. Screenshot of spreadsheet annotation of verbal-visual LSRs. If a piece of text did not enter into a relation with an image, or an image did not enter into a relation with a piece of text, it was annotated as simplex.
The categories proposed in our study were grouped on the basis of two basic systems, as presented below: The same clause can present different kinds of relations of Expansion with an image, as we have different elements construing representations in both verbal and visual texts. Unlike Projection, no speech or thought bubbles occur. There may be Projection in verbal text, but this operates within verbal text, not being projected by visual text, as Figure 8 illustrates. One aspect to explore is whether visual and verbal productions contain different types of information.
- Creating visual explanations improves learning
- Verbal To Visual
Ainsworth and Iacovides addressed this issue by asking two groups of learners to self-explain while learning about the circulatory system of the human body. Learners given diagrams were asked to self-explain in writing and learners given text were asked to explain using a diagram. The results showed no overall differences in learning outcomes, however the learners provided text included significantly more information in their diagrams than the other group.
Aleven and Koedinger argue that explanations are most helpful if they can integrate visual and verbal information. It is important to remember that not all studies have found advantages to generating explanations. Wilkin found that directions to self-explain using a diagram hindered understanding in examples in physical motion when students were presented with text and instructed to draw a diagram.
She argues that the diagrams encouraged learners to connect familiar but unrelated knowledge.
Visual-Verbal Learning (Aleven & Butcher Project) - Pslc
Wilkin argues that these learners are novices and that experts may not make the same mistake since they have the skills to analyze features of a diagram according to their relevant properties. She also argues that the benefits of self-explaining are highest when the learning activity is constrained so that learners are limited in their possible interpretations. The role of spatial ability Spatial thinking involves objects, their size, location, shape, their relation to one another, and how and where they move through space.
How then, might learners with different levels of spatial ability gain structural and functional understanding in science and how might this ability affect the utility of learner-generated visual explanations? Several lines of research have sought to explore the role of spatial ability in learning science. Kozhevnikov, Hegarty, and Mayer found that low spatial ability participants interpreted graphs as pictures, whereas high spatial ability participants were able to construct more schematic images and manipulate them spatially.
Hegarty and Just found that the ability to mentally animate mechanical systems correlated with spatial ability, but not verbal ability. In their study, low spatial ability participants made more errors in movement verification tasks. The authors argue that their results can be interpreted within the context of dual-coding theory.
They suggest that low spatial ability participants must devote large amounts of cognitive effort into building a visual representation of the system. High spatial ability participants, on the other hand, are more able to allocate sufficient cognitive resources to building referential connections between visual and verbal information.
Benefits of testing Although not presented that way, creating an explanation could be regarded as a form of testing. Considerable research has documented positive effects of testing on learning. Presumably taking a test requires retrieving and sometimes integrating the learned material and those processes can augment learning without additional teaching or study e.
What is visual thinking and visual learning?
Hausmann and Vanlehn addressed the possibility that generating explanations is beneficial because learners merely spend more time with the content material than learners who are not required to generate an explanation.
In their study, they compared the effects of using instructions to self-explain with instructions to merely paraphrase physics electrodynamics material.
Thus, we expect benefits from creating either kind of explanation but for the reasons outlined previously, we expect larger benefits from creating visual explanations. Present experiments This study set out to answer a number of related questions about the role of learner-generated explanations in learning and understanding of invisible processes.
We anticipate that learning will be greater with the creation of visual explanations, as they encourage completeness and the integration of structure and function. We predict that including greater counts of information, particularly invisible and functional information, will positively correlate with higher post-test scores.
We predict that high spatial ability participants will include more information in their explanations, and will score higher on post-tests.
Although the pump itself is not invisible, the components crucial to its function, notably the inlet and outlet valves, and the movement of air, are located inside the pump. It was predicted that visual explanations would include more information than verbal explanations, particularly structural information, since their construction encourages completeness and the production of a whole mechanical system. It was also predicted that functional information would be biased towards a verbal format, since much of the function of the pump is hidden and difficult to express in pictures.
Finally, it was predicted that high spatial ability participants would be able to produce more complete explanations and would thus also demonstrate better performance on the post-test.
Explanations were coded for structural and functional content, essential features, invisible features, arrows, and multiple steps. Method Participants Participants were 59 female seventh and eighth grade students, aged 12—14 years, enrolled in an independent school in New York City. The sample consisted of three class sections of seventh grade students and three class sections of eighth grade students. Both seventh and eighth grade classes were integrated science earth, life, and physical sciences and students were not grouped according to ability in any section.
We hypothesize that integrated hints also will support robust learning.
Both of these manipulations, elaborated explanations and integrated hints, support coordination through self-explanation of visual and verbal information.
Providing these multiple representations during learning likely affects path choice. For example, when students are required to explain the application of geometry principles using diagrams, there will be only small differences in estimated effort of shallow and deep strategies since shallow strategies are unlikely to achieve the correct answer. Further, we anticipate that elaborated explanations and integrated hints also produce path effects: Specifically, scaffolds or materials that support sense making with visual and verbal information should promote integration.
Link to Powerpoint slides Butcher, K. Paper submitted to Cognitive Science Conference. Training in self-explanation and self-regulation strategies: Investigating the effects of knowledge acquisition activities on problem solving.
A Mind Mapping Approach To Your Sketchnotes - Verbal To Visual
How students study and use examples in learning to solve problems. Cognitive Science, 13, Eliciting self-explanations improves understanding. Cognitive Science, 18, Abstract planning and perceptual chunks: Elements of expertise in geometry. Cognitive Science, 14, Effects of solving related proofs on memory and transfer in geometry problem solving. Journal of Experimental Psychology: