Intellectual performance improving integrated physical training algorithm for academic physical education

O.A. Safonova1
Dr.Hab., Professor R.M. Kadyrov1
PhD, Professor K.N. Dementiev1
1St. Petersburg State University of Architecture and Civil Engineering, St. Petersburg

Keywords: intellectual performance, physical performance, physical education service, training effect.

Background. Our analyses of the relevant theoretical and practical literature, own research findings and health statistics show that many university students and graduates have poor knowledge and skills in the health protection domain and, therefore, are often unhealthy and physically unfit in many aspects including those that are critical for professional service [3, 4]. This situation may be due to the fact that the valid academic physical education and sports and Elective physical education and sports curriculum are seldom if ever customized to the intensity of modern academic studies [6].

The academic intellectual performance is expected to meet the examination-related requirements with a special priority to the thinking rate, memorizing capacity and high overall performance rate [1, 7]. Therefore, the academic physical education and sports service shall be designed so as to improve the intellectual and physical performance for success. A high attention shall be paid, however, to the huge academic data flows every year and especially in the examination periods that may result in overstresses and hence, inhibit the students’ mental and physical progress and undermine their adaptability to stressors [2, 5, 7, 8].

Objective of the study was to offer an intellectual and physical performance building integrated physical education algorithm.

Methods and structure of the study. The study was designed to test a set of physical exercises of potential multisided benefits. The training algorithm implied the following 4 modules. Module 1 geared to build up the overall endurance by the 30-40-min cross-country races with the heart rate of 130-140 beats/ min; and interval trainings that combine the 3-min walking and 20-min racing intervals with the HR of 130-140 beats/ min. Module 2 designed to train speed by the interval sprint trainings including three 30/ 60/ 100/ 200m intervals with 1-min rest breaks and with the HR of 140-160 beats / min. Module 3 intended to develop strength by the 15-30kg weights applying exercises (squats, deadlifts, bench press, dumbbells/ barbell practices); own weight applying exercises (prone push-ups, walking thrusts, pull-ups for men and semi-hanging pull-ups for women, recumbent-to-sit exercises, Burpees of 5 series of 5 exercises with 12 reps each. And Module 4 geared to build up coordination qualities by practices with apparatuses (stuffed balls, gymnastic sticks) and on a gymnastic bench (jumps-over, twist jumps-over, twist jumps-onto etc.), with 5 reps each.

The academic physical education classes included one 90-min session a week. Module 1 was tested outdoors in September-October and April-May. Modules 2-4 were tested indoors in November to April on an alternative basis (one module per session). The training algorithm was tested in the academic year 2018-19 on a first-year sample, with the sample (n=64) split up into Experimental and Reference Groups (EG, RG) of 32 people each. The intellectual performance was rated by the Landolt Rings Correction Probe and the standard academic progress rates (average points per exam); and the physical performance was rated by the Harvard Step Test, with the both tests run prior to the first semester and after the second semester.

Results and discussion. The pre- versus post-experimental test found that the EG made the academic progress of 1.1 points versus only 0.1 points in the RG; the Correction Test found the EG and RG making progress of plus 120 and 11 characters, respectively; the error rate in the EG and RG was tested to fall by 5 and 1 characters, respectively; and the data flow processing speed was tested to grow in the EG and RG by 1.20 and 0.10 bits/ s, respectively: see Table hereunder. This means that the experimental intellectual and physical performance building integrated physical education algorithm was highly beneficial for the attention control and performance improvement purposes.

Table 1. pre- versus post-experimental intellectual performance test rates of the sample

Tests and test rates

EG (n=32)

M±m

RG (n=32)

M±m

р

Academic progress

Average points

Pre

3,6±0,6

3,9±0,6

≥0,05

Post

4,7±0,7

4,0±0,4

≤0,05

Landolt Rings

Characters checked

Pre

980±58

970±58

≥0,05

Post

1110±37

981±58

≤0,05

Errors

Pre

36,3±8,64

34,3±8,64

≥0,05

Post

31,03±8,9

35±8,9

≤0,05

Data processing rate, bits/s

Pre

1,25±0,06

1,25±0,06

≥0,05

Post

2,07±0,13

1,3±0,06

≤0,05

Harvard step test

Points

Pre

56±1,2

56±1,2

≥0,05

Post

65±2,1

58±1,1

≤0,05

 

The post-experimental EG and RG physical performance was tested to average 65±2.1 points (above average) and 58±1.1 points (below average), respectively.

Conclusion. The experimental data and analyses verified the need in habitual academic physical education and sports practices as a universal stress tolerance building and stamina improvement mechanism particularly beneficial in the examination periods. The new integrated physical training algorithm was tested beneficial as verified by the EG versus RG progress in the intellectual performance and physical performance tests and academic progress data and, hence, may be recommended for application in the academic physical education and sports curricula.

References

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  2. Grigoriev V.I., Dementiev K.N., Pristav O.V., Mironova O.V. Design capabilities of academic physical culture in new conditions. Teoriya i praktika fiz. kultury, 2015, no. 10, pp. 94-96.
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  7. Safonova O.A., Germanova A.A. Influence of physical education on mental performance of civil engineering students. Kultura fizicheskaya i zdorovye, VSPU. 2017. no. 3(63). pp.  100-101.
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Corresponding author: safonov812@yandex.ru

Abstract

Our analyses of the relevant theoretical and practical literature, own research findings and health statistics show that many university students and graduates have poor knowledge and skills in the health protection domain and, therefore, are often unhealthy and physically unfit in many aspects including those that are critical for professional service. This situation may be due to the fact that the valid academic physical education and sports and Elective v curricula are seldom if ever customized to the intensity of modern academic studies. Objective of the study was to an intellectual and physical performance building integrated physical education algorithm for the academic physical education service. The integrated physical training algorithm includes the following four modules: (1) overall endurance training module; (2) speed training module; (3) strength training module; and (4) coordination training module.

Benefits of the new integrated physical training algorithm were tested by an education experiment in 2018-19. Sampled for the experiment were the 1-year students (n-64) split up into Experimental and Reference Groups of 32 people each. Intellectual progress of the sample was tested by the Landolt Rings probe and the standard academic progress rates (average points) per examination session. The physical fitness of the sample was tested in the experiment by the Harvard Step Test (HST) rates. The new integrated physical training algorithm was tested beneficial as verified by the EG versus RG progress in the intellectual performance and physical performance test rates and, hence, may be recommended for application in the academic physical education and sports curricula.