Visual processing is about how the brain perceives and processes the impressions of the eyes. Problems with processing visual impressions can also impact a variety of other skills.
“We’ve confirmed that visual processing may apply to dyslexia, but also to why some children have problems with mathematics and motor skills,” says Professor Hermundur Sigmundsson at the Norwegian University of Science and Technology’s (NTNU) Department of Psychology.
In addition, problems with visual processing may explain why some dyslexics respond more slowly when driving a car, at least as has been shown to be the case in a driving simulator.
Clear connection
A research group from NTNU compared two groups, described in a new article in Scandinavian Journal of Educational Research.
One group consisted of the top ten percent of performers on a test that is often used to determine whether an individual has dyslexia, and the other group consisted of the ten percent who struggled the most on the test.
In total, the researchers surveyed almost 200 people. They used two different computer programs to test the participants. One program checked how efficient the brain is at detecting movement or rapid changes in the surroundings, while the control task was to find a figure hidden in a pattern.
“We found a clear difference between the two groups with high or low literacy in their ability to perceive movement,” says Sigmundsson.
This strengthens previous findings that have pointed in the same direction. The researchers found no difference between the groups in their ability to solve the control task with figures that included shape and color.
Researchers at NTNU have previously linked dyscalculia, which is when a person has problems solving mathematical problems, to visual processing. The same connection applies to motor difficulties in children.
New app makes vision easier to investigate
Visual processing may well be an innate ability that can’t be improved by training that much, if at all. This can limit how good you can become at certain things, and you can only compensate with other skills and exercises to a certain point.
But a new app can at least make it easier to investigate the issue. It can help to determine if someone is struggling with visual processing associated with rapid changes in their surroundings.
In the work related to their most recent article, the research team used an app called Magno. NTNU researchers designed the app for Android. Professor John Krogstie, who heads the university’s Department of Computer Science (IDI) was also involved in the study.
Interdisciplinary
“At IDI we’ve had several tasks related to this problem, both in being able to conduct the test itself and how to manage the test results if a lot of people are going to take this kind of test,” says Krogstie.
In addition, problems with visual processing may explain why some dyslexics respond more slowly when driving a car, at least as has been shown to be the case in a driving simulator.
In addition to the computer technology challenges of creating such systems per se, the scope here is related to general solutions that contribute to learning using IT solutions, Krogstie says.
“By knowing more about the specific challenges a learner has, we can create customized solutions that take the challenges into account,” says Krogstie.
This project is linked to broader activity in the Learner Computer Interaction workshop at the department.
“This is an interdisciplinary activity that requires collaboration across academic fields. Having a good working relationship with other people, including people who work on the psychology of learning, is a natural fit. Working together on Magno helps us work better across academic subject areas. That’s useful in a lot of different ways,” says Krogstie.
While visual motor integration skills make a statistically significant contribution in some aspects of the regression model, the reduction in contribution reduces the predictive validity of visual motor integration skills.
Therefore, a visual motor integration skill measure will not sufficiently determine if a child has a reading disability
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It is estimated that students with specific learning disabilities are most often (80–90% of students) identified as having difficulty with reading.1,2,3
Thus, a clear understanding of the factors associated with the early development of reading problems has never been more important for parents, teachers, and health professionals working with elementary school-aged children.
The National Reading Panel4 reported the essential skills necessary for students to become proficient readers by the third grade.
The report identified five areas of reading: phonemic awareness, phonics, vocabulary, fluency, and comprehension. Absent from this list are any skills relating to the visual processing of text, or the visual-motor processes involved in reading. It is noteworthy that studies involving measures of visual-motor processes were not excluded at the outset.
Since the publication of the report of the National Reading Panel, Hammill5 reviewed three meta-analyses of reading to determine which abilities most highly related to reading achievement.
The ability measures from the meta-analyses were chunked into ten superordinate ability clusters that included reading, writing conventions, letters, written language, rapid naming, phonological awareness, IQ, memory, spoken language, and perceptual and motor (including visual motor skills).
The findings from these meta-analyses were consistent with the report of the National Reading Panel and other often cited syntheses of the research on the precursor skills necessary for the development of reading.
In this paper, we distinguish between reading, which is defined to be the process of extracting meaning from printed text, and the various skills that support reading. These supporting skills include phonological processes, the ability to decode words accurately and fluently, and knowledge of the meanings of words.
It is important to make the distinction between reading related skills and reading comprehension because reading comprehension is the end product of many component skills being carried out in concert with one another.
In prior work on the role of visual-motor skills in reading, studies have often failed to make this distinction. Some studies have focused exclusively on the component skills (e.g., decoding and fluency), whereas others have either ignored the component skills, or embedded them in general measures of reading.
These approaches either ignore the role of the component skills in reading comprehension, or fail to specify the correct role of the component skills in comprehension, both of which lead to specification errors in the statistical models and potentially biased estimation of the role of visual-motor skills in reading.
The present paper includes measures of reading comprehension as well as important reading related skills that play a role in the comprehension of text so as to obtain a clearer picture of the role of visual-motor skills in reading.
Research on visual-motor performance and reading ability has been present for over 50 years and has produced mixed results. For example, research comparing students with and without learning difficulties by Rosner et al.6 found a higher prevalence of visual-motor skill dysfunction among students with learning difficulties but the researchers did not specifically test any academic skills.
Goldstein et al.7 sought to predict reading, mathematics, and writing achievement using three different visual motor test scores. The sample population was comprised of individuals referred for evaluation of a learning disability.
The results indicated that while visual motor integration (VMI) was correlated with reading and other achievement scores, VMI was not independently related to reading over and above measure of intelligence. Kulp8 found a significant developmental trend of Berry VMI9 raw scores from kindergarten through second grade and that these scores were significantly related to teachers’ ratings of children’s reading ability,
Stanford Reading test scores in first graders, and Otis-Lennon School Ability Test (OLSAT) scores for second graders. The variables in the study measured general reading ability along with teacher ratings. Missing from the study were measures of phonological abilities, alphabetic knowledge, or general language abilities such as vocabulary or listening comprehension that served as predictors of reading along with the measure of VMI.
Also missing from the study as predictors of reading were any measures of decoding ability, indicating that the researchers were not operating from the most widely used theoretical model for reading, namely, the Simple View of Reading (SVR) of Gough and Tunmer.10 Feagans et al.11 used the Gibson Task to measure visual-motor skills, the Peabody Individualized Achievement Test, the Woodcock Johnson, and the Wechsler Intelligence Scales for Children–Revised to determine that students with low performance on the Gibson Task also had low performance on all other measures, especially reading.
In a more recent study by Sortor et al.,12 relations among Beery VMI, the Otis-Lennon School Ability Test, and the Stanford Achievement Test were examined and showed that visual-motor skills were significantly related to reading scores derived from the Stanford, a general reading ability test. Of the above mentioned studies8,11,12 none included measures of phonological abilities, alphabetic knowledge, decoding, or language skills as predictors of reading in their analysis examining the role of visual-motor skills.
This omission suggests that the researchers were not considering the role of visual-motor abilities within the context of a comprehensive model for the development of reading and reading-related skills, such as decoding and fluency.
In contrast, Margolese et al.13 studied the impact of visual motor skills within the context of other language-based predictors of reading, including phonological skills and language comprehension. Results indicated that the strongest predictor of early reading was phonological skills.
No effect of visual–motor skills was found when the phonological and language based measures were included as predictors. Busch14 found that the single best predictor of reading skills was the ability to recognize letters and sounds and the smallest contribution to the model was from VMI. This study was unlike other studies cited above in that phonological awareness was included as a predictor of reading.
However, at the same time, the researchers did not articulate a comprehensive model for the development of reading, leaving open the possibility that results might differ if relationships were examined within a comprehensive, theoretically-motivated model. For example, including decoding and fluency along with VMI in a model of reading comprehension considers only the direct effect of visual-motor skills on reading.
This direct effect may underestimate the role of visual-motor skill in reading if their influence on reading comprehension is fully mediated by word-level reading skills. Francis et al.15 found evidence that effects of visual motor skills on grade 5 reading were mediated by effects on grade 3 reading using latent variable models.
However, that study failed to differentiate among decoding and comprehension skills and did not measure phonological processes involved in the development of decoding skills, which may have positively biased estimates of the effects of visual-motor skills.
A major factor contributing to variability across many of the studies has been the failure of some studies to take into account known predictors of early reading skills, particularly predictors in the language domain.
Related to this criticism is the tendency for different studies to use different sets of measures, even if the same constructs, or domains of assessment have been included in different studies.
Another factor influencing prior research has been the intermittent inclusion of measures of cognitive ability. Kavale16found that there was a stronger relation for visual discrimination than visual-motor integration with reading, but Sortor et al.12argued that the results were due to the lack of control for IQ.
Additionally, Kavale16 suggested that although visual perception, a term that encompasses visual discrimination and visual motor integration skills, correlates to reading achievement, other factors such as other reading variables should be considered to explain variance in reading skills.
Finally, prior studies have varied in their focus on selected or unselected samples of students. Specifically, some studies have focused exclusively on students with disabilities, or students at-risk for the development of disabilities, while others have included relatively homogeneous samples of unselected students, such as participants who tended to be middle class and Caucasian,8,12 potentially limiting the generalizability of findings.
Variability across studies in the inclusion of constructs and in their measurement may reflect that researchers are operating from different theoretical models for the development of reading and do not agree on how best to measure all relevant constructs.
In part this heterogeneity in theoretical orientations is not unexpected when the research base spans many disciplines with different histories and differences in shared assumptions. Similarly, variability across studies in the populations of interest are not unexpected given the variety of basic and applied scientific fields with a substantive interest in the development of reading. Given the significant correlation between visual-motor skills and reading achievement,8,12 a more comprehensive evaluation of the role of visual-motor skills in the development of children’s reading seems warranted.
The goal of the present study was to investigate how visual-motor skills relate to reading achievement using a large and diverse sample of typically developing readers along with systematic measures of precursor and reading-related skills, word reading, vocabulary, and fluency, and norm-referenced achievement reading tests.
Precursor and reading-related skills in this study refer to letter sound knowledge, rapid naming of letters, phonological awareness, vocabulary, decoding skills, and word reading fluency.
