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Consequently, there has been enthusiastic interest in understanding and identifying the neural pathways that seem to control both music perception and spatial-temporal ability. Spatial-temporal ability refers to recognizing the relations between objects and mentally transforming them through space and over time without a physical representation. Researchers propose that exposure to music and experience with music strengthens those neural connections. Such a relationship has implications for the role of music in such traditionally nonmusical fields as mathematics, architecture, engineering, and chess, in which spatial-temporal reasoning plays a large part because it incorporates many mathematical and scientific concepts, such as proportions and geometry.
Interest in the phenomenon labeled \"The Mozart Effect\" has broadened programs in music education. Classical music has been advocated for use in business and daycare centers; in Georgia, classical CDs were given to new mothers as they left the hospital. An additional study by Rauscher further explored the findings of the original experiment by using preschoolers, all of normal intelligence, with no prior music or computer training. This study examined the long-term effects of music training, by following the preschoolers for two years. Experimenters divided the preschoolers into four groups: keyboard and group singing lessons, singing lessons, computer lessons, or no lessons at all. On an Object Assembly task, testing spatial-temporal ability, the subjects who received the keyboard and group singing lessons performed significantly better than the remaining three groups (Rauscher, 1997). These results have been more practically applied in further experiments that have shown that school math scores improve over years with musical games, constant singing exercises, and piano lessons. Researchers point out that by visualizing the keyboard as a representation of a number line in terms of pitch children can learn to better develop mental skills for math: \"If you develop some kind of mental skill involved in one area of learning, and if you need that skill in some other area of learning, the brain can at least sometimes make learning easier through transfer\" (Viadero, 1998).
The current experiment had a simple design: one factor with three levels, the three listening conditions. Additionally, data were collected on years of musical training, and approximate amount of time taken to complete the test. This study was modeled after the original, in an attempt to replicate its results of improved spatial-temporal ability in the classical listening condition. An additional music listening condition was added to address the issues raised by the original regarding the effects of a less complex, more repetitive music. An example of this genre of music is techno or house music, with a heavy, monotonous beat, and a short melody repeated continuously throughout the song. On the other hand, classical music is musically complex, incorporating changing and intricate melodies which build and develop throughout the piece, different kinds of orchestral instruments, and complicated harmonic blending and rhythms. The sonata in the first experiment, Mozart`s sonata for two pianos in D major, K488, is a piece played by just two pianos, as compared to the more complicated symphony which uses the full orchestra, which can include up to twenty-four different instruments. To test if the effects on spatial-temporal reasoning generalize beyond the specific piece of classical music in the original experiment and classical music in general, there were, along with the silent listening condition, two music listening conditions: a classical symphony, Berlioz`s Symphonie Fantastique, differing from the first experiment`s and a techno mix.
Do musical ability and spatial-temporal ability, once thought to be separate, really have a common origin in the brain? What implications does this have for the links among ability and performance in the mind and its organization? These questions are far beyond the scope of this experiment, yet are important to keep in mind while exploring this elusive and intriguing relationship.
Twelve Georgetown University students, recruited by and friends of the experimenter, participated in this study. There were three groups of four participants each. Approximately equal numbers of men and women were tested. Each participant was randomly assigned to one of three listening conditions through random block assignment to control for individual differences.
A consent form was used to inform subjects. They were told the purpose of the study and also told to keep in mind that the spatial-temporal reasoning test was difficult. It also informed them that names would not be placed on their tests, that the results were solely for research purposes, and that they could terminate their participation at any time.
All subjects listened to the songs on the same computer, set to the same volume at each trial. The classical listening condition song was Hector Berlioz`s \"Un Bal, Movement 2 of Symphonie Fantastique\" and the techno listening condition song was the extended mix of ATB`s \"My Dream.\" Both songs lasted about 6 minutes, and the subjects in the third listening condition were exposed to the same duration of silence.
The test consisted of 10 questions, in which subjects had to pick one out of five possible answers. The questions were presented as sequences of images, in which the subject had to pick the image that would come next, requiring him or her to move the image around in his or her mind. At the top of the test, subjects were asked to identify their testing group (A, B, or C) and also asked \"How many of years of formal music training/lessons have you had?\" to provide additional data.
After completing the consent form, participants chose one slip of paper out of an envelope. A, B, or C was written on the slips, representing the three levels of the listening condition factor: A represented \"Un Bal,\" the classical music; B represented \"My Dream,\" the techno music; and C represented the silence listening condition. After a slip was chosen, it was discarded to ensure random block assignment. Because this experiment is between-subjects, random block assignment served to protect against the confound of individual differences. Also serving to guard against individual differences, the subjects, all being Georgetown undergraduates, were matched by age and general intelligence.
Subjects were instructed to listen to their randomly assigned song or to silence, to relax and close their eyes so that no distracting visual stimuli might confound the results. As stated above, the songs and silence lasted for about 6 minutes. Then subjects were given the tests and instructed to do their best. Subjects were given an unlimited amount of time to complete the test.
A frequency distribution for the scores of the Classical Group, the Techno Group, and the Silence Group shows that the majority of higher scores were attained by the Silence Group, not the Classical Group as predicted. The majority of lower scores were attained by the Techno Group, with the Classical Group falling somewhere in the middle.
The mean scores of the three conditions are: 42.5 for the Classical Group, 37.5 for the Techno Group, and 57.5 for the Silence Group. The Silence Group yields the highest scores on this test and the Techno Group the lowest with the Classical Group again in the middle.
Associating years of music training and test scores reveals a slightly negative correlation coefficient, r=-.160, suggesting practically no relationship. However, a correlation between the time taken to complete the test and test scores reveals an r of .559, suggesting a relatively strong relationship. This indicates that the subjects who took longer on the test performed better.
A one-way ANOVA reveals that these results are not significant, F(2,9) = 1.61, p>.05. The actual p value is .2525. These results have led to an acceptance of the null hypothesis, that there would be no significant difference among scores from the three listening conditions. There is no effect of listening condition on the dependent measure, the spatial-temporal reasoning test.
Those subjects exposed to silence before the test performed best. This could be explained by a lack of distractions, i.e. the music, that allowed them to focus later on the task at hand. The next best mean of scores was obtained by those subjects in the classical music condition and the lowest scores were obtained by the techno music condition. The statistics, such as the frequency distributions and means, do reveal that subjects perform most poorly after being exposed to the techno music condition, as implied by the original experimenters. Their suggestion was to have further experiments explore the effects of less complex, more repetitive music. It was predicted that techno music would interfere with spatial-temporal ability, which is supported by these results. However, the fact that this mean of scores had the greatest variability, showing that individual scores varied highly from the mean, implies that this claim is not very reliable.
To understand this experiment and its lack of a significant effect, several problems should be taken into consideration. A careful look at the differences between this current experiment and the original could shed light on the current experiment`s failure to replicate. The original experiment`s ANOVA revealed F(2, 35) = 7.08, p = .002, a highly significant result. Perhaps this spatial-temporal ability test (which differed from the original experiment`s use of tests from the Stanford-Binet Intelligence Scale) is not a valid measure of subjects` actual spatial-temporal reasoning skills. If so, then its results would not indicate enhanced performance by the classical music condition group. In the original, thirty-six college students participated, as compared to the twelve in this experiment. Perhaps this sampling number was too small to display an effect. Additionally, individual differences most certainly are a factor, although precautions such as random assignment and matching were used to minimize their confounding influence. The original experiment was a within-subjects study. However, due to the limitation of the test`s length, if this study was within-subjects and therefore, counterbalanced, there was the risk of ending up with a brief and inadequate measure.
Furthermore, by viewing Figure 4 and considering that r is .559, indicating a strong positive relationship, the correlation between time taken to complete test and test scores is most definitely relevant to the failure to replicate. However, there is no mention of time taken to complete the tests in the original. Unlimited time, thought to relieve stress on the subjects` part and to ensure completion of the test, was a confounding variable. Each subject took a different amount of time to complete the test, and this interfered with results. In future studies, time as a confounding variable should somehow be eliminated, while, at the same time, alleviation of stress and completion is assured.
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