Motor skills must be taught in order to be performed proficiently (Logan, Robinson, Wilson, & Lucas, 2012). The speed-accuracy trade-off is the relationship between how fast a movement is completed and the accuracy of the movement. Hsieh, Pacheco and Newell (2016) discuss that when completing a movement task quickly and increasing movement speed there is greater chance of making more mistakes and being less accurate. Freestone, Ferdinands and Rooney (2015) conducted an experiment to test the speed-accuracy trade-off with nine elite junior baseball players with the average age being 19.
6 years. The study asked for the baseball players to throw 10 fastballs at 80% and 100% speed at a 7cm target standing 20 m away.
The findings found that at maximum speed there was a higher average error of 67.7% therefore, the study examines the speed-accuracy trade-off. Moreover, Mulligan and Hodges (2013) discuss how the exposure to visual patterns allow for the motor system to automatically anticipate future outcomes. However, there has not been a study where the visual and motor influences are controlled.
Mulligan and Hodges (2013) did an experiment with forty males between the ages of 19 and 31 who were all righthanded. These 40 males were spilt into four groups; full vision, no vision, observer and a control group. The experiment found that full vision and the no vision group improved but accuracy significantly increased with the full vision group. Therefore, the purpose of this experiment is to highlight how the speed-accuracy trade-off is affected in the throwing whilst exploring how vision affects our speed and accuracy in the overarm throw.
Ten participants (5 females and 5 males) aged from 7-52 volunteered to participate in this study. All participants were informed that their results will be used for a scientific report assessment.
The equipment used in this experiment included 8 Wilson tennis balls, a 35 cm x 35cm square crate, a blindfold and a stopwatch. The data was written into Windows Microsoft office 365 and figures and tables were made in Windows Microsoft Excel 365.
The experiment procedure used in this study is similar to other speed-accuracy trade-off experiments (Freestone, Ferdinands & Rooney, 2015; Molina & Stodden, 2018). The experiment required the subjects to stand on a line 10m away with 8 Wilson tennis balls facing a 35cm x 35cm square crate that was used as the target. Subjects were told that the experiment would be split into three trials each trial focusing on a specific element of the speed-accuracy trade-off. Trial one focused on the speed of the ball: the subject was asked to throw the eight tennis balls at the target as fast as they could whilst being timed and recorded. The second trial placed emphasis on the accuracy of the experiment. The subjects followed the same procedure but instead were asked to focus on the accuracy of their shots instead of speed. For the final trial they were told to repeat the experiment but blindfolded to highlight how lack of visual cues affect the speed-accuracy trade-off.
The results of speed, accuracy and impaired vision rounds of the experiment. The results of this experiment showed that as accuracy increased, the subjects ability to perform the task quickly decreased. This is evident when Subject 5 hit the target 6 times with a time of 47 seconds in comparison to Table 1 where the same subject hit the target once within 12 seconds. The average hits found in Trial 2 was 3.9 hits. Furthermore, when speed was emphasised, accuracy was decreased as can be seen in Table 1 with Subject 1s results. The results showed that accuracy was zero in Trial 1 when speed was the focus of the overarm throw experiment; this task was completed in 8 seconds. Speed was increased within each trial when accuracy demands were foremost. In Trial 1 the quickest time was 8 seconds in comparison to Trial 2 at 47 seconds which clearly indicates how speed is increased when accuracy is emphasised. In the speed demanded task the study found that the average speed in Trial 1 was 14.5 seconds while in Trial 2 it was 26.3 seconds therefore, the experiment claims that it follows the speed-accuracy trade-off theory. The experiment also showed how accuracy significantly decreased when vision was obstructed. Accuracy decreased from the most accurate score which was 6 to zero when the subjects were blindfolded in Trial 3.
Speed-accuracy trade-off is described as a linear relationship between speed of a movement and the accuracy of the movement (Molina & Stodden, 2018). According to Molina and Stodden (2018) multi-joint movements such as throwing do not support this theory. This is evident in both Figure 1 and Figure 2 which confirm that a linear relationship in this experiment does not exist when speed or accuracy is emphasised. An example of this is shown in Figure 2 where in Trial 1 the highest score for accuracy was 4 hits, but in Trial 2 the highest score for accuracy was 6. Similar results were found in Freestone et al. (2015). Their experiment used nine junior elite baseball athletes to throw 10 fastballs at 80% and 100% of maximum speed. The findings indicated that optimal accuracy occurred at 70-75% maximum of speed and that anything above 75% resulted in a decrease in accuracy. Freestone et al.s (2015) experiment indicated that the highest average error was found in the 100% of maximum speed with an average error of 67.7%. This is evident in Table 1 where accuracy was limited but the task was completed faster.
Similarly, Molina and Stodden (2018) did an experiment with 45 children (21 girls) aged between 9-11 years old. They were required to throw 5 overarm throws at their max speed in five blocks of eight trials (40 trials in total). As in the experiment reported in this study, the children were asked to throw as hard as they could at a 20cm x 20 cm target from 3.05m away. Molina and Stodden (2018) found that when unskilled in the task, the subjects showed less variability across the different target speeds of 45%, 65%, 85% and 100%. Figure 1 highlights how speed demanded tasks in Trial 1 showed similar scores of accuracies while Trial 2 indicates that speed decreases when accuracy is demanded in a task.
Moreover, Mulligan and Hodges (2013) conducted an experiment to explore how the use of visual patterns allows for our motor systems to prepare for action anticipation. Their experiment had 40 male subjects throwing a dart at 3 specific points on one target. Mulligan and Hodges (2013) split the subjects into four groups; No vision of the action, Full vision, Observer, and a control group. The group who did the task with no vision only received feedback on the final position of the darts; the observer group were to only watch the task being performed; the control group received no pre-test practice, and the group with full vision were able to use motor practice to develop their motor skills through vision. Mulligan and Hodges (2013) highlight that no studies have been done where vision and motor influences have been controlled, and hypothesised that if motor experience by itself is responsible for improvement, there should be no difference between the no vision and the full vision group pre to post practice performance. Their findings concluded that accuracy scores increased when more vision was available and found that the group who learnt with no vision had a slower learning rate at the beginning, but by the end, they performed similarly to the group with full vision. Similarly, this is seen in Figure 2 in Trial 3 where when the task was performed without vision, accuracy decreased in comparison to Trial 2. The majority of the subjects were unable to hit the target without any vision. This comparison is made clear with Subject 10 when comparing their Trial 2 accuracy which was 6 to their Trial 3 accuracy which was zero. Therefore, these findings highlight how vision patterns affect the humans motor systems to predict future outcomes and how it aligns with the speed accuracy trade-off.
The results from this experiment are consistent with other speed-accuracy trade-off experiments showing that as speed is emphasised, accuracy will decrease and vice versa. However, Molina and Stodden (2018) indicate that the speed-accuracy trade-off is described as a linear relationship but, both speed and accuracy tasks in this experiment showed they did not have a linear relationship. Therefore, the results of the study described in this report support Molina and Stoddens (2018) claim that multi-joint movements such as throwing do not follow the speed accuracy trade-off model. Furthermore, the study confirms that many variables such as vision can affect accuracy and speed when completing a task.