Susan Davis
Psychology of Music
Group Project: Music Learning
“According to new biological theory, music learning is a process by which mental representations (genuine musical conceptions) are developed and gradually altered, differentiated, extended, and refined” (Gruhn, 2006, p. 17). Although many people believe that performing music is reserved for the gifted and talented, research has shown that music learning is available to all people. Lehmann, Sloboda, and Woody (2007) express that most people, with few exceptions, are capable of achieving musical competency at a professional level, although the actuality of this happening is dependent upon external variables that include “motivation, opportunity, and resource” (p. 26). Considering that music learning is attainable for the general population, it is imperative that music educators understand how to effectively cultivate musical experiences in their students. This paper will therefore examine Swanwick and Tillman’s theory (1986) intended to shed light on the developmental aspect of musical learning, as well as explore whether critical periods exist in the brain for music learning, and finally touch on recent developments in neurodidactics and their implications for music education.
Several people have tried over the years to develop a theory for chronological stages of musical development, comparable to the psychological theories of Piaget, Vygotsky or Erikson. One such theory that has received attention is that proposed by Keith Swanwick and June Tillman (1986): “the spiral of musical development” (p. 331). Their spiral model emerged from a study evaluating children’s musical compositions. Children ranging in age from 3 to 11 years old were given the opportunity to make music with a variety of available instruments, including their voices. The children had time to formulate a “composition” and repeat it. These pieces were recorded, amounting to 745 compositions from 48 children over four years. A tape was compiled of the “second versions” of students’ compositions in randomized age order. Three independent judges were then brought in to estimate the children’s ages based on the recorded musical evidence. Of the three judges, two were both musicians and teachers while one was a teacher with no musical experience. The judge without musical experience had great difficulty recognizing age-appropriate musical behaviors, while the two other judges exhibited a high statistical correlation to the actual ages of the students assessed. Swanwick and Tillman investigated this relationship, as well as the judges’ comments about how they determined the age assessment. They found “observable differences between the musical compositions of these children, linked with age” (Swanwick, 1988), leading them to formalize their model of musical development. Many of the terms Swanwick uses to clarify the stages of development are derived from Piaget’s work about children at play (e.g. “mastery” and “imitation”). This model also appears to be influenced by the work of Helmut Moog, Robert Bunting and Malcolm Ross (Swanwick, 1988).
Swanwick and Tillman’s spiral of musical development (see Appendix A) consists of eight developmental modes spread throughout four levels of development. At the basic “mastery” level (0-4 years), children first experience the “sensory” mode. This is characterized by sound exploration, attraction to timbre and dynamic levels, as well as unpredictable music making. As time goes on, children enter the “manipulative” mode where they begin to demonstrate understanding of instrument techniques, a regular pulse, repetition, and increasing control of materials. The second developmental level is “imitation” (4-9 years) and it begins with the “personal” mode. For children in this mode, personal expressiveness is central, with hints of basic phrases and generally spontaneous musical ideas. The transition to the “vernacular” mode is signified by melodic and rhythmic patterns emerging in the form of shorter pieces, often exhibiting 2, 4, or 8-bar phrases. At the “imaginative play” level (10-15 years), later renamed “constructional play” by Swanwick (Runfola & Swanwick, 2002), children first enter the “speculative” mode. This mode exemplifies experimentation as children explore contrasting ideas and musical surprises, although they are not always controlled. In the “idiomatic” mode children continue to develop the surprises into more identifiable musical styles and authenticity becomes very important as children aim to imitate “grown up” music making. “Meta-cognition” (15+ years) is the final level, initiating the “symbolic” mode. Swanwick and Tillman did not actually work with children from this category, however they speculated about the qualities of this level based on the writings of Bunting and Bruner (Swanwick, 1988). At this level, young adults reflect on musical experience and exhibit a growing personal identification with certain pieces and musicians. This culminates in the “systematic” mode that combines intense feeling with ability to speak about music in an academically structured way. Student musical experience may be informed by research, music theory, and technology as students compose, discuss and reflect on their work. It is important to note that Swanwick considers the levels to be circular and cumulative, as well as somewhat flexible regarding age (Swanwick, 1988). A child with a stimulating musical home environment may move through the levels more quickly, whereas a child with no musical encouragement may never even achieve the higher levels. In this way the spiral of musical development differs from certain psychological developments that occur without extrinsic stimulation.
While Swanwick and Tillman’s spiral of musical development is compelling for music educators and has yet to be supplanted by a more thorough model, it is essentially based on one longitudinal study executed in the 1980’s (with a few replicated studies later, Runfola et al. 2002). Innumerable developments in technology and measurement capabilities have arisen in the past twenty years that might shed some light on actual brain development in children related to music learning. Some have explored the possibility of “critical periods” for musical skill acquisition.
A critical period is an “age window” of opportunity for development of a specific behavior or ability that is more significant than at other times of encounter (Trainor, 2005). The research example most often referenced to demonstrate critical periods is Hubel and Wiesel’s study of 23 newborn kittens. One eye of the newborn kittens was covered so that they adapted to using the other. After a few months the covered eye was opened, however the kittens were not able to regain full vision in that eye (Flor & Hodges, 2006). This would seem to indicate that the brain dealing with optical data changed to accommodate the stimulus early in the kitten’s life, but after the “critical period” the brain could no longer adapt. Analysis of critical (or sensitive) periods for music is more complicated because of its multifaceted nature and the various general and music learning systems involved. To date there is no empirical substantiation for concrete critical periods in music learning. However, Trainor (2005) has asserted that there may be evidence that early musical experience has a different effect from similar experiences later in life.
Trainor cites the work of Amunts, Schlaug, Jaencke, Steinmetz, Schleicher, Dabringhaus, and Zilles as delivering the strongest support for a critical period in childhood. Their studies showed that “the size of an area of motor cortex (intrasulcal length of the posterior bank of the precentral gyrus) in a group of keyboard players was correlated with the age of onset of musical lessons” (Trainor, 2005, p. 266). Flor and Hodges (2006) have cited Gordon’s studies of musical aptitude as demonstrating potential for critical periods. Gordon discovered children’s musical aptitude scores do not appear to change significantly after 9 years of age. Trainor also mentions Takeuchi and Hulse’s work that found absolute pitch exhibited in adulthood to be strongly linked with music lessons prior to 6 years of age. This appears to correspond with Crozier’s findings that absolute pitch training is more successful with children under 6 years old (Trainor, 2005) as well as the work of Russo, Windell, and Cuddy (2003) that found 5-6 year olds more receptive to absolute pitch training than both 3-4 year olds and adults. In addition, Trainor refers to the work of several researchers that have found sensitivity to harmonic structure apparent at later ages, specifically after 8 years and up to 10 or 12 years of age (e.g. Costa-Giomi, 2003; Cuddy & Badertscher, 1987; Krumhansl & Keil, 1982; Speer & Meeks, 1985 as cited in Trainor). Trainor does express that although there seems to be support for certain critical or sensitive periods early in life, neuroplasticity in the brain continues well into adulthood indicating “there are multiple pathways to achieving musical expertise” (Trainor, 2005, p. 274).
The current technological revolution in neuroscience has the potential to answer questions about critical periods in music learning and give direction to music education curricula in the 21st century. The ability to look at brain activity - the prospect of understanding what happens in the brain during music learning - has opened up a whole new world of possibilities. Most recently, the discipline of neuropedagogy (or neurodidactics in European terms) has emerged seeking to establish brain-based learning strategies. The goal of neurodidactics (attributed to Gerhard Preiss) is to discover what teachers need to know about the electro-chemical and hormonal processes in the brain that reinforce synaptic strength and foster long-term representation, in order to better educate students (Gruhn, 2004; Gruhn & Rauscher, 2007). While multiple recent studies have elucidated brain activity as it relates to music learning, we still are not in a place to profess causal connections between musical phenomena and neural activity. With that in mind, I will explain a few current compelling studies and their results.
Harvard Project Zero is presently involved in a longitudinal study comparing the brains of children taking piano lessons with children not engaged in music learning. Ellen Winner comments on the experience in the movie, Class Act:
We decided to look at children just as they were beginning to study a musical instrument and to follow them over time; look at their brains through MRI (magnetic resonance imaging); look at their brains before they’ve had any training and then at yearly intervals and to compare these children to a group of children not getting music lessons. We did find that after one year the children in the music group had more grey matter brain volume than children in the control group. (Sackner, 2007)
These findings are synergistic with the results of Fujioka, Ross, Kakigi, Pantev, and Trainor (2006). Fujioka et al. studied “auditory evoked responses to a violin tone and a noise-burst stimulus…[in] 4- to 6-year old children in four repeated measurements over a 1-year period using magnetoencephalography (MEG)” (p. 2593). Half of the children studied participated in Suzuki violin lessons while half of the children received no music lessons. Music lessons were found to result in brain developmental changes over time in response to the musical stimuli.
Altenmüller, Gruhn, Parlitz, and Liebert (2000) studied the effect of different learning modalities on students’ ability “to distinguish between correct and incorrect (balanced and unbalanced) phrases (i.e., the so-called musical periods that consist of corresponding parts, antecedent and consequent)” (Altenmüller & Gruhn, 2002, p. 73). Students were either trained in a “procedural” manner, where they participated in musical tasks through singing, playing, improvising, and performing musical works; trained in a “declarative” manner, where they were taught verbal concepts through direct instruction, the use of visual aids and some musical examples (with no performing); or treated as a non-trained musical “control group.” Students who learned declaratively showed increased activity in left hemisphere regions that may indicate analytical reasoning and step-by-step processing. Gruhn has referred to this as more localized learning. By contrast, students who learned procedurally exhibited a wider distribution of cortical activation patterns, as well as increased activation in the right hemisphere. This may indicate a more global way of processing information with visuo-spatial associations (Altenmüller and Gruhn, 2002; Altenmüller et al., 2000). Testing was initiated again one year later, without further training, and the procedural group still exhibited an increase in achievement that Gruhn attributes to subjects developing “categories that enabled them to continue in a process of self-directed learning” (Gruhn, 2004, p. 4).
With the increased desire to demonstrate the power and necessity of music to school and arts administrators, politicians and the greater community, brain-based music studies have been exalted as a panacea for weak advocacy arguments. However, the complexity of this research and our inability to make clear causal claims triggers some to warn against “false hopes that neuronal and educational processes are strongly and evidently linked” (Stern as cited in Gruhn & Rauscher, 2007). In spite of Stern’s warnings, Gruhn (2004) has made several suggestions about music learning and music education that are difficult to dispute based on the neurobiological data available in the field so far: (1) Students need time to develop mental representations; (2) Students need many opportunities to embody experience, building efficient neural networks; (3) Students need context, not content, to create meaning; (4) Students need to be taught topics when the brain is best prepared (“sensitive”) to process the input; (5) Students need to experience positive feelings (“flow” according to Csikszentmihalyi) through their learning process; and (6) Students should be taught music in a procedural way to best develop mental representations. While there are still many questions that remain unanswered about music learning, and there are many other studies the confines of this paper cannot address regarding neuroscience and music, I hope that the scope of topics engaged here offer some insight into a currently thriving and compelling field of inquiry.
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Appendix A: The spiral of musical development (Swanwick & Tillman, 1986)