Updated on 09 Jul. 2008

 

 

 

Keynote abstracts
Optimal range of variation in hockey technique training
Beckmann, H.1), 2), Winkel. C.1), & Schöllhorn, W.I.2)
1) Westfalische Wilhelms-University Muenster, Germany
2) Johannes Gutenberg-University Mainz, Germany		  
Different approaches in technique training are deduced from motor learning theories with a background from either motor or action approaches. According to Schöllhorn et al. (2006, 2007) these motor learning theories could be summarized to the theory of differencial learning (Schöllhorn, 1999) using the parameter “variation range” or even “noise”. The theory of differencial learning also forecasts that there is a correlation between variation range/ level of noise and learning performance in the form of an inverted-u-shaped-curve (cf. Gebkenjans et al., 2007). The aim of this study was a comparison between treatments of different variation ranges in technique training for the push and the flick in indoor hockey (cf. IFH, 2008) to proof this idea of an optimal variation range. Table 1 gives a survey of the different treatments. According to Schöllhorn et al. (2006, 2007) the treatments are arranged top down in order of increasing variation range.

Table 1. Survey of treatments used in this study.
Annotations: With “none” is intended, that in this cases the variations in target or movement result only indirect from variations of the other parameter.

Methods
In the pre-test we tested 43 experienced hockey players: The task was to execute ten pushes and ten flicks with a standard hockey stick (cf. FIH, 2008). Subjects had to aim on two targets in a hockey goal (3m x 2m), that was painted on a wooden wall (5m x 3m). The targets were marked in the bottom right corner (push) and in the top left corner (flick) of the goal. After the pre-test the subjects were randomly distributed (cf. Table 1) and started with a six week treatment, with two training sessions per week with twenty trials each in the push and in the flick. After three weeks of training the test was repeated (intermediate test) and after the sixth week the treatment interval was closed by a post- and a transfer-test. Two and four weeks after the post-test the subjects executed a retention-test. In all tests, except the transfer-test, subjects shot ten pushes (bottom right) and ten flicks (top left) under blocked conditions. In the transfer-test they shot ten pushes (bottom left) and ten flicks (top right) in a new direction. The dependent variable “target precision” was parameterized by the mean absolute value of the distance between target and strike and it was measurement by an optic measuring system. As Table 1 shows, the independent variable “treatment” has five levels (cf. column “group”). Therefore we use an ANOVA with repeated measurements on the factor time for analyzing the data.		   Results

Figure 3. Results for the push (left diagram) and the flick (right diagram).

The results show an increasing target precision for the most groups in the push (except DL 2) and for all groups in the flick (cf. Figure 3). Furthermore the results of the ANOVA show statistical differences for the push between DL 1 and CG (p = 0.045*), CI and DL 1 (p = 0.008***) as well as DL 3 and CI (p = 0.068trend). There are no statistical differences for the flick between the groups.

Discussion
The results for the push affirm the proposal by Schöllhorn et al. (2006, 2007), that there is an optimal trend between size of movement variations during acquisition and learning progress per time. For the push the optimum seem to be at a variation range represented by group DL 1, which may indicate that for a target precision task variations in the target (CI, DL 1) or combined variations in movements and the target (DL 3) are more effective than variations in the area of movements only (DL 2). Moreover the results of the transfer- and the retention-test point out, that differencial learning including variations in the target enables hockey players to adapt to new situations and to stabilize the target precision performance over time. This might be relevant for game situations and for economical restructuring of training processes. However the results for the flick point out that the optimum variation range might depend on the movement pattern and the individuality of the athlete and cannot defined a priori or individual-spanning.

Key References
FIH, The International Hockey Federation (Ed.) (2006). Rules of indoor hockey [Electronic resource]. Download at http://www.fihockey.org/vsite/vfile/page/fileurl/0,11040,1181-178867-196085-113017-0-file,00.pdf; on 2008-06-10, 16:37 CET.
Gebkenjans, F., Beckmann, H., & Schöllhorn, W. I. (2007). Does low and high contextual interference lead to different levels of noise? [Abstract]. In P. Beek & R. van den Langenberg (Eds.), 3rd European Workshop on Movement Sciences. Book of Abstract (pp. 153-154). Köln: Sportverlag Strauß.
Schöllhorn, W. I., Janssen, D., Michelbrink, M. & Davids, K. (2007). Fluctuations in classical learning theories provide evidence for an underlying priciple. In P. Beek & R. van de Langenberg (Eds.), 3rd European Workshop on Movement Science. Book of Abstracts (pp. 54-55). Cologne, Germany: Sportverlag Strauß.
Schöllhorn, W. I., Michelbrink, M., Beckmann, H., Trockel, M., Sechelmann, M., & Davids, K. (2006). Does noise provide a basis for the unification of motor learning theories? International Journal of Sport Psychology, 37 (3/ 4), 34-42.
Schöllhorn, W. I. (1999). Individualität - ein vernachlässigter Parameter? [Individuality – a neglected parameter?] Leistungssport, 29, (2), 7-11.

Annotations
This study was supported by the Federal Institute for Sport Science, Germany (file reference: IIA1-070618/06). Furthermore the authors like to thank F. Rost for supporting the data acquisition and data analysis.

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