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Psychology and Psychotechnics
Reference:

Search for psychophysiological predictors of success in school

Druzhinin Oleg Aleksandrovich

ORCID: 0000-0003-3365-4302

Entrepreneur

443110, Russia, Samara region, Samara, Novo-Sadovaya str., 19, sq. 119

oleg.a.druzhinin@gmail.com
Other publications by this author
 

 

DOI:

10.7256/2454-0722.2023.3.43891

EDN:

WVJFUM

Received:

24-08-2023


Published:

03-09-2023


Abstract: The paper presents the results of an experimental study aimed at identifying psychophysiological predictors of learning success among students of grades 1-11 of secondary schools. The study involved 611 children and adolescents aged 7 to 18 years. The results of sensorimotor tests of varying complexity were analyzed, assessing the reaction time to auditory and visual stimuli. The results of the parents' questionnaire were also taken into account. It is shown that only complex sensorimotor tests, during which the child must respond to targeted combinations of visual stimuli, ignoring all other stimuli, have predictive significance that allows predicting the success of a child in learning.   Previously, the same results were obtained by us for elementary school students. The present study allowed us to establish that complex sensorimotor tests predict success in learning throughout the entire period of schooling from grades 1 to 11. Children who showed high results in complex sensorimotor tests significantly study better, and their parents believe that school grades correspond to the abilities of children. It was also found that girls study better, and the use of gadgets for more than one hour a day has a negative impact on the success of children in learning.


Keywords:

sensorimotor tests, reaction time, children, learning success, sensorimotor integration, cognitive abilities, executive functions, sensorimotor reactions, visual-motor reaction, abilities

This article is automatically translated.

 

Introduction. The tradition of measuring various parameters of a person's reaction time to evaluate intellectual indicators is based on the theoretical ideas of several researchers. This tradition is the result of ideas about sensorimotor integration as the basis of cognitive abilities [3], as well as G. Eysenck's views on the nature of intelligence, in which the speed of information transmission in the nervous system is described as the biological basis of intelligence [1]. Currently, the study of human speed characteristics is actively continuing in a variety of tasks [16,17,18,21].

 The most developed areas are those related to the success of athletes in various sports [5,8,14].

Reaction time in elderly people is also being studied, as it is related to their safety [12,15].

 There are fewer papers evaluating the relationship of reaction time with academic performance. As a rule, studies were conducted on small samples [9,22].

It is shown that the reaction time in sensorimotor tests is associated with the level of formation of executive functions [13,19,20].

 

Previously, we used the assessment of various parameters of simple and complex sensorimotor reactions to predict the success of a child's education in primary school [6,7,10]. We have shown a high prognostic significance of the parameters of a complex visual-motor reaction for the assumption of what the average annual assessment the child will have at the end of the year.

At the same time, it was shown that, starting from the 4th grade, the educational motivation of schoolchildren changes significantly, which could change the prognostic significance of the parameters previously studied by us. That is why the purpose of this work was to identify psychophysiological predictors of success in learning throughout school from grades 1 to 11.

 

Materials and methods

 

The study was conducted in two schools in St. Petersburg - No. 225 and 235 in 2022. Students took part in the study with the written consent of their parents. The purpose of the study and the procedure for conducting it were explained to parents at the meeting. Sensorimotor tests were conducted in the morning.

A total of 611 children aged 7 to 18 years participated in the study. The age and gender composition of the sample is shown in Figure 1.

 

 

Fig. 1. Distribution of subjects by gender and age. Columns with horizontal stripes are girls, with vertical stripes are boys. Age – full years.

 

 

 

The study was conducted on a device for psychophysiological testing UPFT-1/30-"PSYCHOPHYSIOLOGIST" (scientific, production and design firm "Medikom", Russia) with a block of psychomotor tests. The diagnostic complex included 7 tests. Examination of 1 child took about 15 minutes.

1.         Simple visual-motor reaction (PMR): the child was asked to press the button as soon as possible if the green LED on the instrument panel lit up.

2.         Simple auditory motor reaction (PSMR) - the subject was asked to press a button on the instrument panel as soon as possible if a sound sounded.

3. Complex visual-motor reaction (SPMR) – a two–color indicator - red or green LEDs - was used as a stimulus. The subject had to react to one of the signals, while ignoring the second.

4. Complex visual-motor reaction to a light combination (SPMR-SC) – the subject reacted by pressing buttons only to a certain combination of colored LEDs, ignoring other combinations.

5. Reaction to a moving object (RDO). A moving object is an arrow rotating around a circle.  inside the circle there are 12 LEDs that light up randomly one by one.  It is necessary to press the button so that the arrow stops as close as possible to the burning LED.

6. Dynamic sensorimotor test (DST) – light stimuli are presented with increasing speed if the reactions of the subject in the form of pressing a button are correct. The more correct reactions, the faster the stimuli are presented.

7. Tapping test (TT) – the subject is asked to tap the tapping pad as quickly as possible. The test was performed separately for the right and left hands.

            The parents of the students filled out Google questionnaires consisting of 23 questions. The questionnaires allowed us to take into account the peculiarities of children's lifestyle, for example, the time spent daily with gadgets, the independence of the child when performing lessons, etc., as well as the opinion of parents about the compliance of school grades with the abilities of the child.

Indicators reflecting various aspects of the success of the tests were automatically saved in the device's card file and then uploaded to the SPSS-21 table for subsequent mathematical analysis along with the results of the parents' questionnaire.  The results of sensorimotor tests and the results of parents' questionnaires were compared with the annual grades of children in all subjects.

 

Results and their discussion

 

First, a factor analysis was carried out in order to describe the possible relationships of the studied parameters. The result of the factor analysis is presented in Tables 1 and 2.

From Table 1, it can be seen that factor analysis can be used for data processing, since the measure of the adequacy of the Kaiser-Mayr-Olkin sample is 0.716 (a CMOS value greater than 0.5 is sufficient for application), the percentage of the explained variance was 0.66 %

 

Table 1. KMO and Bartlett criterion

A measure of the adequacy of the Kaiser-Mayer-Olkin sample (KMO).

0,716,716

Bartlett 's sphericity criterion

Approximate Chi-square

335,578

St.

55        55

Significance

0,001

 

Table 2. Rotated matrix of components

 

Table

Component

 

1

2

3

 

Tepping_SU_PR

0,867

-0,159

0,093

Tepping_SU_LR

0,862

-0,259

0,063

DST_BALL

0,846

0,316

-0,252

DST_CHPR

0,844

0,371

-0,222

Age

0,807

-0,053

-0,290

SZMR_ER_3

0,076

-0,747

-0,126

SZMRSK_CHPR

0,366

0,590

-0,079

Marks at school (academic performance) match the abilities

-0,362

0,502

0,298

Uses gadgets for entertainment for less than an hour a day

-0,191

-0,036

0,691

Paul

-0,010

-0,098

-0,659

Average score for the last year

-0,058

,530

0,623

The method of factor allocation: the method of principal components.

 Rotation method: varimax with Kaiser normalization.

 

a. The rotation converged in 6 iterations.

 

               

 

The first factor (35.3% of the explained variance) includes the relationship of age with the parameters of the tapping test and the parameter DST_BALL (dynamic sensorimotor test, number of points), DST_CHPR (dynamic sensorimotor test, number of correct reactions). The older the child, the higher the tapping test scores (the sum of the strokes) were with both the right and left hand, and the speed tasks aimed at decision-making are performed more efficiently. This result can be explained by the fact that the reaction rate in sensorimotor tests is associated with the degree of myelination of the brain's pathways, therefore, with age, as children complete myelination, this speed increases.

The second factor (16.2% of the explained variance) connects the parents' idea that school grades correspond to their child's abilities with the parameters of a complex visual motor reaction (the number of errors in it) – the SPMR – ER - 3 indicator: the fewer errors, the more likely parents are to evaluate the child's grades as corresponding to his abilities. Children with high scores in complex sensorimotor tests are more likely to receive higher grades at school, parents are satisfied with their success and consider such grades deserved, corresponding to the abilities of the child.

The third factor (14.7% of the explained variance) connects the objectively obtained estimates of the child with the time spent with the gadget and the sex of the child. Data analysis showed that girls study significantly better. This result may be due to the fact that the functional maturation of the brain of girls occurs faster than that of boys.  It was also found that the less time a child spends with gadgets, the higher his grades. This is an important result that shows that the success of a child in learning depends not only on his innate abilities, but also on the conditions that parents create. It is parents who can regulate the amount of time a child spends with gadgets. The abuse of electronic entertainment automatically leads to a decrease in the child's motor activity, which in turn can reduce his performance and success in learning.  Apparently, the optimal time that a student can spend with a gadget is less than an hour a day.

Then a regression analysis was carried out, the results of which are presented in Table 3.

 

 

 

 Table 3

Summary for the modelb

Model

R

R-square

Adjusted R-square

Standard estimation error

Durbin-Watson

1

,381a

,146

,130