ORIGINAL PAPER
Effect of delayed mechanical feedback on long jump performance
1
Department of Physical Education and Sport Sciences, Al-Kitab University, Altun Kupri, Iraq
2
Faculty of Physical Education, Assiut University, Assiut, Egypt
Submission date: 2020-07-31
Acceptance date: 2021-04-08
Publication date: 2022-02-17
Hum Mov. 2022;23(4):140-147
KEYWORDS
TOPICS
ABSTRACT
Purpose:
The present study assesses the extent to which delayed mechanical feedback affects technical and numerical long jump performance.
Methods:
The participants were 45 first-grade students from the Department of Physical Education of Umm Al-Qura University. They were randomly divided into 3 equal groups. The first experimental group used delayed mechanical feedback, the second experimental group applied fast visual feedback, and the control group received oral explanation and guidance of a teacher. The delayed mechanical feedback condition lasted for 6 weeks. Each week included 2 units, each lasting for 90 minutes.
Results:
The educational programs had a significant main effect on technical and numerical long jump performance (p < 0.05), with a large effect size, as the percentage of improvement ranged 9.95–42.32%. Also, the differences across the 3 groups were statistically significant in terms of their technical and numerical performance (p < 0.05), favouring the mechanical feedback group, except for the difference between the fast visual feedback and the teacher guidance groups.
Conclusions:
The delayed mechanical feedback program had a more significant positive effect on technical and numerical long jump performance than the other 2 programs.
The present study assesses the extent to which delayed mechanical feedback affects technical and numerical long jump performance.
Methods:
The participants were 45 first-grade students from the Department of Physical Education of Umm Al-Qura University. They were randomly divided into 3 equal groups. The first experimental group used delayed mechanical feedback, the second experimental group applied fast visual feedback, and the control group received oral explanation and guidance of a teacher. The delayed mechanical feedback condition lasted for 6 weeks. Each week included 2 units, each lasting for 90 minutes.
Results:
The educational programs had a significant main effect on technical and numerical long jump performance (p < 0.05), with a large effect size, as the percentage of improvement ranged 9.95–42.32%. Also, the differences across the 3 groups were statistically significant in terms of their technical and numerical performance (p < 0.05), favouring the mechanical feedback group, except for the difference between the fast visual feedback and the teacher guidance groups.
Conclusions:
The delayed mechanical feedback program had a more significant positive effect on technical and numerical long jump performance than the other 2 programs.
REFERENCES (49)
1.
Kamnardsiri T, Janchai W, Khuwuthyakorn P, Suwansrikham P, Klaphajone J, Suriyachan P. Knowledge- based system framework for training long jump athletes using action recognition. J Adv Inf Technol. 2015;6(4):182–193; doi: 10.12720/jait.6.4.182-193.
2.
Fattah OA, Bataineh AS. Analysis of kinematics of the approach run in long jump event among Jordanian male team. Russ J Biomech. 2020;24(1):15–22; doi: 10.15593/RJBiomech/2020.1.02.
3.
Theodorou AS, Panoutsakopoulos V, Exell TA, Argeitaki P, Paradisis GP, Smirniotou A. Step characteristic interaction and asymmetry during the approach phase in long jump. J Sports Sci. 2017;35(4):346–354; doi: 10.1080/02640414.2016.1164884.
4.
Panteli FN, Theodorou A, Pilianidis T, Smirniotou A. Locomotor control in the long jump approach run in young novice athletes. J Sports Sci. 2014;32(2):149–156; doi: 10.1080/02640414.2013.810344.
5.
Graham-Smith P, Lees A. A three-dimensional kinematic analysis of the long jump take-off. J Sports Sci. 2005;23(9):891–903; doi: 10.1080/02640410400022169.
6.
Pan Z. Analysis of mechanical model on factors influencing the long jump result under the perfect condition. Res J Appl Sci Eng Technol. 2013;5(5):1589–1593; doi: 10.19026/rjaset.5.4909.
7.
Bartlett R. Introduction to sports biomechanics: analysing human movement patterns. Abingdon: Routledge; 2014.
8.
Bridgett LA, Linthorne NP. Changes in long jump takeoff technique with increasing run-up speed. J Sports Sci. 2006;24(8):889–897; doi: 10.1080/02640410500298040.
9.
Guiman MV. Theoretical and experimental aspects concerning the long jump trial. Bull Transilv Univ Bras I Eng Sci. 2015;8(57):17–24.
10.
Makaruk H, Starzak M, Sadowski J. Does step length adjustment determine take-off accuracy and approach run velocity in long and triple jumps? Hum Mov. 2015;16(3):124–129; doi: 10.1515/humo-2015-0038.
11.
Guiman MV. The take-off angle analysis in case of long jump trial. In: ICMS 2019 & CO MEC 2019. Brasov: Transilvania University of Brasov; 2019; 50–53.
12.
Bouchouras G, Moscha D, Papaiakovou G, Nikodelis T, Kollias I. Angular momentum and landing efficiency in the long jump. Eur J Sport Sci. 2009;9(1):53–59; doi: 10.1080/17461390802594243.
13.
Hraski M, Hraski Ž, Mrakovi S, Horvat V. Relation between anthropometric characteristics and kinematic parameters which influence standing long jump efficiency in boys and adolescents. Coll Antropol. 2015; 39(Suppl. 1):47–55.
14.
Fernandez-Santos JR, Gonzalez-Montesinos JL, Ruiz JR, Jiménez-Pavón D, Castro-Piñero J. Kinematic analysis of the standing long jump in children 6- to 12-yearsold. Meas Phys Educ Exerc Sci. 2018;22(1):70–78; doi: 10.1080/1091367X.2017.1383913.
15.
Pavlovic R, Bonacin D, Stankovic D. Differences in kinematic parameters of the long jump between male and female finalists of World Championships – Berlin 2009. Int J Sci Cult Sport. 2016;4(4):353–366; doi: 10.14486/IntJSCS528.
16.
Nolan L, Lees A. The influence of lower limb amputation level on the approach in the amputee long jump. J Sports Sci. 2007;25(4):393–401; doi: 10.1080/02640410600717931.
17.
Mishra MK, Rathore VS. Speed and agility as predictors of long jump performance of male athletes. Turk J Sport Exerc. 2016;18(2):27–33; doi: 10.15314/tjse.40102.
18.
Palao JM, Hastie PA, Guerrero Cruz P, Ortega E. The impact of video technology on student performance in physical education. Technol Pedagog Educ. 2015;24(1):51–63; doi: 10.1080/1475939X.2013.813404.
19.
O’Donoghue P. The use of feedback videos in sport. Int J Perform Anal Sport. 2006;6(2):1–14; doi: 10.1080/24748668.2006.11868368.
20.
Potdevin F, Vors O, Huchez A, Lamour M, Davids K, Schnitzler C. How can video feedback be used in physical education to support novice learning in gymnastics? Effects on motor learning, self-assessment and motivation. Phys Educ Sport Pedagog. 2018;23(6):559–574; doi: 10.1080/17408989.2018.1485138.
21.
Ningthoujam R. Construction and importance of video based analyses teaching in physical education by use of window live movie maker. Video J Educ Pedagog. 2016;1(1):4; doi: 10.1186/s40990-016-0003-2.
22.
Sethu S. Effect of technique training with and without visual feedback on high jump performance. Int J Emerg Technol Comput Appl Sci. 2014;10(4):314–318.
23.
Durai C. Effect of visual feedback on volleyball skills among physical education students. Int J Creat Res Thoughts. 2016;4(2):409–412.
24.
Anantharaj G, Durai C. Effect of skill training with and without video feedback on long jump performance. Int J Adv Res Innov Ideas Educ. 2018;4(1):552–556.
25.
Manikandan P. Impact of video modelling with video feedback on long jump skills. Res Rev Int J Multidiscip. 2019;4(4):497–499.
26.
Szczepan S, Zaton K, Borkowski J. The effects of concurrent visual feedback on the control of swimming intensities above the onset of blood lactate accumulation. Hum Mov. 2018;19(4):49–55; doi: 10.5114/hm.2018.77324.
27.
Aginsky KD, Noakes TD. Why it is difficult to detect an illegally bowled cricket delivery with either the naked eye or usual two-dimensional video analysis. Br J Sports Med. 2010;44(6):420–425; doi: 10.1136/bjsm.2008.047266.
28.
Magill R, Anderson D. Motor learning and control: concepts and applications, 11th ed. New York: McGraw Hill Education; 2017.
29.
Campos J, Gàmez J, Encarnación A, Gutiérrez-Dávila M, Rojas J, Wallace ES. Three-dimensional kinematics during the take-off phase in competitive long jumping. Int J Sports Sci Coach. 2013;8(2):395–406; doi: 10.1260/1747-9541.8.2.395.
30.
Akl A-R. Biomechanical study to assess the variations between male and female in long jump. Sport Sci Pract Asp. 2014;11(1):33–36.
31.
Guiman MV, Ioan B. A method for the analysis of the take-off and the flight start in the long jump. Palestrica Third Millenn Civiliz Sport. 2015;16(4):324–328.
32.
Cohen J. Statistical power analysis for the behavioral sciences, 2nd ed. New York: Routledge; 2013.
33.
Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for ttests and ANOVAs. Front Psychol. 2013;4:863; doi: 10.3389/fpsyg.2013.00863.
34.
Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006;1(1):50–57; doi: 10.1123/ijspp.1.1.50.
35.
Scott SH, Cluff T, Lowrey CR , Takei T. Feedback control during voluntary motor actions. Curr Opin Neurobiol. 2015;33:85–94; doi: 10.1016/j.conb.2015.03.006.
36.
Tidow G. On the reproducibility of acyclic velocity maxima as a function of resistance magnitude and infraserial pause duration [in German]. In: Krug J, Minow H-J (eds.), Sports performance and training [in German]. Leipzig: Academia; 1995; 275–283.
37.
McCosker C, Renshaw I, Greenwood D, Davids K, Gosden E. How performance analysis of elite long jumping can inform representative training design through identification of key constraints on competitive behaviours. Eur J Sport Sci. 2019;19(7):913–921; doi: 10.1080/17461391.2018.1564797.
38.
Muniz PE. Detection of launch frame in long jump videos using computer vision and discreet computation. Bachelor thesis. Cambridge: Massachusetts Institute of Technology; 2019.
39.
Bowtell MV, Tan H, Wilson AM. The consistency of maximum running speed measurements in humans using a feedback-controlled treadmill, and a comparison with maximum attainable speed during overground locomotion. J Biomech. 2009;42(15):2569–2574; doi: 10.1016/j.jbiomech.2009.07.024.
40.
Jennings CT , Reaburn P, Rynne SB. The effect of a self-modelling video intervention on motor skill acquisition and retention of a novice track cyclist’s standing start performance. Int J Sports Sci Coach. 2013;8(3):467–480; doi: 10.1260/1747-9541.8.3.467.
41.
Perreault ME, French KE. External-focus feedback benefits free-throw learning in children. Res Q Exerc Sport. 2015;86(4):422–427; doi: 10.1080/02701367.2015.1051613.
42.
Zatoń K, Cześniewicz I, Szczepan S. Effects of verbal feedback on movement efficiency during swimming ergometry. Pol J Sport Tourism. 2018;25(3):5–9; doi: 10.2478/pjst-2018-0013.
43.
Chatzopoulos D, Foka E, Doganis G, Lykesas G, Nikodelis T. Effects of analogy learning on locomotor skills and balance of preschool children. Early Child Dev Care. 2022;192(1):103–111; doi: 10.1080/03004430.2020.1739029.
44.
Sweigart CA, Collins LW, Evanovich LL, Cook SC. An evaluation of the evidence base for performance feedback to improve teacher praise using CEC’s quality indicators. Educ Treat Child. 2016;39(4):419–444; doi: 10.1353/etc.2016.0019.
45.
Glazier PS. Game, set and match? Substantive issues and future directions in performance analysis. Sports Med. 2010;40(8):625–634; doi: 10.2165/11534970-000000000-00000.
46.
Jeraj D, Veit J, Heinen T, Raab M. How do gymnastics coaches provide movement feedback in training? Int J Sports Sci Coach. 2015;10(6):1015–1024; doi: 10.1260/1747-9541.10.6.1015.
47.
Szerdiova L, Simsik D, Dolna Z. Standing long jump and study of movement dynamics using human motion analysis. In: 2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE; 2010; 263–266. Available from: http://ieeexplore.ieee.org/doc....
48.
Schmidt RA, Lee TD, Winstein CJ, Wulf G, Zelaznik HN. Motor control and learning: a behavioral emphasis, 6th ed. Champaign: Human Kinetics; 2018.
49.
Becerra Motta JA, Becker RR. The effectiveness of biomechanical stimulation (BMS) in conjunction with traditional methods of strength endurance development in swimming [in German]. Leistungssport. 2001;31(2):29–35.
Share
RELATED ARTICLE
| eISSN: | 1899-1955 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
