Interaction Between Visual and Spatial Working Memory Skills for Academic

One of the applied learning skills is academic skills, which are considered critical for scoring good grades in school. These skills are necessary for tackling the process of organizing learned information& retaining them. WM can be categorized as auditory working memory (AWM) and visuospatial working memory (VSWM). AWM underpins the capacity to retrieve information and manipulate them as required. The VSWM is a temporary visual store including dimensions such as color and shape (Logie, 1995)

The Evidence of previous studies has shown that VSWM is associated with retaining location information (pattern recognition) and object information (i.e., colors, shapes). The visual working memory (VWM) and spatial working memory (SWM) have distinct information processing as visual memory is responsible for retaining information regarding shapes and colors, whereas spatial memory is responsible for retaining information about locations and movement. This distinction is not always distinguished as visual memory involves spatial information and vice versa. In practice, the two systems work together in some capacity but different tasks have been developed to highlight the unique abilities involved in either visual or spatial memory. Carlesimo et al., 2001studied a brain-damaged person and reported that brain damage can impair object memory or spatial memory without impairing the type of memory. Petit et al., 1998 suggested that memory tasks activate different neural substrates than spatial memory tasks. Klauer& Zhao, 2004 reported that there is less interference between object memory task and or spatial memory task. These studies suggest a dissociation between VMW and SWM.

Researchers have identified few models to explain the process of storing the information. The object-based model predicts that SWM does not play a necessary role in retaining information about how individual features were organized as objects in VWM. In contrast, other researchers argue that VWM stores feature values from different feature dimensions in separate feature-specific memory stores, and requires SWM and attention to keep those features organized as integrated object representations in memory (Wheeler &Treisman, 2002). It seems intuitively reasonable to expect that successful mathematics learning would require students to make efficient use of their working memory. It is perhaps not surprising for example, that the phonological loop is implicated in more tasks that involve strategy use based on counting down strategies for subtraction problems (Imbo and Vandierendonck, 2007) than in tasks that require single-digit multiplication recall from long-term memory (De Rammelaere et al., 2001). The central executive, on the other hand, usually has a greater role to play in the ‘carry operation’ in addition and multiplication than the phonological loop (Imbo et al., 2007). A comprehensive review of the research relating to mathematics and working memory, Raghubar, Barnes, and Hecht (2010) agree, but with some caveats. They note the complexity of this relationship and the likelihood that for any individual it will depend on a wide range of factors that influence how the individual interacts with the mathematics information (either the teaching information or the information specifying a problem or task). These include personal factors such as their age and skill level, mathematics content factors, and characteristics of the learning–teaching contexts such as the level of mastery being targeted (beginning, generalizing, or automatizing), the language of instruction, and the formats in which the mathematics information presented. They note the need for a sufficiently comprehensive model of mathematical processing, particularly about skill acquisition, that can handle current findings on working memory as well as provide the basis from which to guide discoveries and inform practice. Children with math difficulties differ from their peers without difficulties in the aspect of their working memory processes; in verbal working memory, in static and/or dynamic visual–spatial memory processing, in numerical working memory, and backward digit span tasks. Given a lack of consistency across studies about how to measure the components of verbal and visual-spatial working memory, you can see various trends across the age span of school, for example,

1. executive and visual–spatial memory processes are used more during learning new mathematical skills/concepts and the phonological loop processes after a skill has been learned.
2. longitudinal studies suggest that some executive processes may be more generic in terms of supporting learning, while others, such as visual-spatial working memory may be more specific to early mathematical learning and verbal processes become more prominent at older ages
3. different aspects of working memory mediate different aspects of mathematical performance for dyscalculic children.
4. working memory is linked with other factors in mathematics learning such as students’ ability to use and focus their ‘learning attention’. Dyslexic students frequently have difficulty investing attention in what they are learning (Fletcher, 2005; Zentall, 2007). They also have difficulty automatizing what they are learning so that, on later occasions, the knowledge makes a lower demand on thinking space. An understanding of which aspects of working memory are deficient in children with math difficulties is obscured by a lack of precision in knowing the particular strategies and processes that the child brings to bear on working memory tasks (possibly as a function of age and language) and a theory that links these working memory processes to particular aspects of mathematical learning and performance.

Specific Learning Disorder (SLD) is a generic term used to describe a heterogeneous condition, as it is a single overall diagnosis, incorporating deficits that impact academic achievement. Rather than limiting learning disorders to diagnoses particular to reading, mathematics, and written expression, the DSM criteria describe the shortcomings in general academic skills and provide a detailed specification for the areas of reading, mathematics, and written expression(Diagnostic and Statistical Manual of Mental Disorders, DSM-5 2015). Several researchers have investigated that the individual with SLD encounter severe learning problems and have difficulty in scholastic achievements due to working memory deficits specifically in visual and spatial memory (Mammarella, Daniela Lucangeli, and Cesare Cornoldi, 2010).

The individual with SLD has difficulty in coordinating with visual, auditory, and sensory inputs and decode instructions by analyzing these repeatedly. Though several studies have proved the influence of VW deficits in academic performance among children with SLD, the interaction between Visuospatial working memory has not been evaluated so far in the Indian scenario. The present study is a preliminary attempt to shed light on these issues by characterizing the conditions in which VWM and SWM interact and assessing their effect on academic performance.

Aim

The current study aimed to determine the (a) visuospatial working memory deficits in individuals with SLD and (b) to assess the interaction between VWM and SWM and its influence on academic performance in children with specific learning disorders.

Method

Participants: The study involved 40 participants and they were in the age range of 9years – 12 years. The participants were categorized into 2 groups. Group 1 consisted of 20 participants (9 Females and 11 Male) who were diagnosed as individuals with specific learning disorders (SLD) by a qualified speech-language pathologist. The test battery administered were Early Reading Skills (ERS), Linguistic Profile Test - K (LPT - K), Test for Pragmatics Skills (TPS), Test for Auditory Comprehension of Language (TACL), and Test for Examining Expressive Morphology (TEEM) and SLD assessment protocol. Group 2 consisted of 20 typically developing children (9 Female and 11 Male) who were in the age range of 9 years -12 years. All the participants were screened for the presence of neurological, audiological, visual, and psychological deficits. Only the participants who passed the screening tests were included in the study.

Design: A dual-task paradigm was used to measure the visual and spatial working memory. This method was previously been adapted by researchers to measure the storage capacity of working memory for objects, locations, and observed movements, (Jiang et al., 2000; Luck & Vogel,1997; Wood,2007). The study consisted of 4 tasks, Task 1 (T1) is a pattern recognition task in which the individuals had to view the stimulus and mark the location array consisting of varying numbers of locations along the spatial grid within the time lock presentation. Task 2(T2) is a color recognition task, where the participants were instructed to view the color and mark the corresponding color. Task3 (T3) is a shape pattern recognition task, here the individual had to plot across the spatial grid within time lock. Task4 (T4) is a color shape recognition task; here the individuals remembered shape and color within the given time. The stimulus consisted of 4 tasks and 26 stimuli, which were prepared with increasing complexity using DmDx software with a time-lapse of 1500msec between each picture. The study involved 4 experiments to assess the interaction between visual and spatial tasks and to associate with academic performance.

Procedure: Each trial began with a 500 misrepresentation; Task 1 was a pattern recognition task, which had eight different matrices with varying complexity that were presented to the participants. Each matrix was composed of blue dots with different patterns. Each participant was presented with one matrix at a time for a duration of less than 500msec. The participants were instructed to remember the pattern and shade the color to the given empty matrix. Initially, the participants were presented with a 2 x 2 matrix pattern followed by which 3x3, 4x4, and 5x5 respectively.

Task 2 is a shape pattern recognition task, in this task the participants were presented with a series of 5 images. One image has 1 shape and one blank and the complexity of the task was the same for the 1st and5th image. Each subject was presented with a blank sheet without a geometric shape. The participants were instructed to remember the position and shape of the geometric pattern that was shown and draw the shape to the given sheet in the same pattern, which was shown.

Task 3 was the color recognition task. In this task, the children were presented with a series of 9 images, in different matrices with varying complexity. One matrix with a minimum of 2-4 colored squares was presented at a time. Where the complexity increased from 1st to6th image, which had one square blank following to, those next 3 images had all the 4 colored blocks. Each subject was presented with a sheet of squares without color. The participants were instructed to remember the position and color of squares presented and colors the shape to the given sheet in the same pattern. Initially, the participants were presented with 2 squares in which one was colored and another empty, pattern followed by which 3 squares with 2 squares colored and 1 uncolored and 4 squares with all colored respectively.

Task 4 was the color shape pattern recognition task. In this task, the participants were presented with a series of 5 images. Where each image has 3 geometric shapes with 2 colored and another uncolored, each subject was presented with a blank sheet. The participants were instructed to remember the colored geometric shape pattern with the position and draw them in the sheet given as shown in the image.

The academic performance record was collected from the teachers and documented. The data obtained were analyzed and was subjected to statistical analysis using SPSSS software version 17.