The Effects of Specific Practice Strategy Use on University String Players’ Performance

Abstract

The purpose of this study was to determine the effects of specific practice strategy use on university string players’ performance. Participants (N = 40) volunteered for the study and were string players enrolled in orchestra at a major research university. Within a pretest–posttest designed study, participants were assigned to one of four treatment groups using stratified randomization: free practice, playing slowly then gradually speeding up, repeating small sections, and playing the excerpt multiple times. In a recorded session, participants were given 1 min to review the study music and then were asked to sight-read the excerpt. Participants then practiced using their assigned strategy for 10 min, rested for 1 min, and performed the excerpt again. The researcher discovered that each practice strategy significantly improved university string players’ performance. No differences were found among practice strategies with regard to pitch, rhythm, expression, or overall scores. Results of an additional analysis indicated that the results may have been affected by performance level of the participants, the study music, and the time involved in the practice session.

Keywords

practice strategy strings university

“How do you get to Carnegie Hall? Practice, practice, practice.” Musicians everywhere have heard this saying and know there is much truth to it; they instinctively know that practicing leads to progress. But how to practice and what to practice are much harder questions to answer. Ivan Galamian, a renowned violin teacher, wrote, “One of the most important things that a teacher ought to teach his students is the technique of good practice” (Galamian, 1964, p. 93). Within the last 100 years, researchers have started to investigate what constitutes “good practice.” They have observed musicians of all ages practice and have tested to see which strategies work best. Through these studies, researchers have developed theories about how performers develop expertise through practice (Ericsson, Krampe, & Tesch-Romer, 1993), what constitutes effective practice (Jørgensen, 2004; Lehmann & Ericsson, 1997), and how learners go about the process of practicing (Hallam, 1997b).

Descriptive Studies of Practice

Researchers have used a variety of descriptive techniques to discover that young musicians tend to use a limited range of strategies in their practice, with repetition being the most common (Austin & Berg, 2006; Leon-Guerrero, 2008; Lisboa, 2008; McPherson & Renwick, 2001; Pitts, Davidson, & McPherson, 2000; Rohwer & Polk, 2006). Researchers also have learned that young students who use analytical strategies, such as practicing in sections, using slower tempos, or keeping practice diaries, improve performance (McPherson, 2005; McPherson & Renwick, 2001; Miksza, 2007; Rohwer & Polk, 2006). Despite the call from many researchers for educators to teach their students more efficient practice strategies, evidence suggests that younger students do not always incorporate learned strategies into their own practice (Austin & Berg, 2006; Leon-Guerrero, 2008; Lisboa, 2008; Rohwer & Polk, 2006).

In an effort to determine if practice changes as performance level changes, researchers also have compared practice habits of musicians of different ages and abilities. Results from these studies revealed that students with lower performance levels tended to use a limited number of practice strategies (Hallam, 1997a; Jardaneh, 2007). As students’ performance level improves, however, their practice begins to include higher-level strategies, such as goal setting, segmentation, and understanding instructions (Hallam, 1997a, 1998, 2001; Sloboda, Davidson, Howe, & Moore, 1996; Williamon & Valentine, 2000). Results concerning the time required for a person to improve performance level have been mixed. Researchers have shown that the amount of time a musician spends in deliberate practice is predictive of performance when measured over a long period (Ericsson et al., 1993; Hallam, 1998; Sloboda et al., 1996). Other researchers, however, have shown that the amount of time spent practicing was not predictive of performance when measured over the period of a single performance (Williamon & Valentine, 2000). Time spent practicing is an important factor in the development of musical skills but clearly is not the only factor (Hallam, 1998, 2001).

Other researchers have observed how advanced and expert musicians use their practice time. These researchers have shown that advanced and expert musicians are able to recognize errors quickly and accurately, and correct them using a variety of practice strategies (Barry, 2007; Chaffin & Imreh, 2001; Chaffin, Lisboa, Logan, & Begosh, 2010; Duke, Simmons, & Cash, 2009; Geiersbach, 2000; Nielsen, 1999a, 1999b, 2004). Advanced and expert musicians are also more metacognitive about their practice, thus allowing them to recall learned strategies and control and regulate those strategies during practice (Geiersbach, 2000; Nielsen, 1999a, 1999b, 2004). During practice, the focus of advanced musicians changes over time as they work from the initial learning of a piece through performance (Chaffin et al., 2010; Chaffin & Imreh, 2001; Nielsen, 1999a), and this focus is guided by a musical goal, or mental image, present from the earliest practice sessions (Chaffin et al., 2010; Chaffin & Imreh, 2001). The advanced and expert musicians in these studies, however, were not a homogenous group; they showed considerable differences in their strategies (Barry, 2007; Duke et al., 2009; Geiersbach, 2000) and in their focus during practice (Chaffin et al., 2010; Chaffin & Imreh, 2001). Results from these studies indicate that the practice strategies musicians elect to use during practice have an effect on the efficiency of their practice (Geiersbach, 2000) and their ultimate performance (Duke et al., 2009).

When considering descriptive studies across all skill levels, patterns begin to emerge regarding the development of musicians over time. Musicians at the beginner and intermediate levels tend to use a limited range of strategies in their practice, do not use many planning strategies, have not yet developed the ability to choose and regulate their practice strategies, and lack the ability to create a mental image of the music they are trying to create (Austin & Berg, 2006; Hallam, 1997a, 2001; Jardaneh, 2007; Leon-Guerrero, 2008; Lisboa, 2008; McPherson & Renwick, 2001; Pitts et al., 2000; Rohwer & Polk, 2006). As musicians develop, they begin to use a wider variety of practice strategies, plan their practice, and develop metastrategies to assist them in their practice (Hallam, 1997a, 1998, 2001; Miksza, 2007; Rohwer & Polk, 2006; Sloboda et al., 1996; Williamon & Valentine, 2000). By the time musicians reach advanced and expert levels of performance, they have highly developed practice skills and are able to regulate practice strategies to address problems (Barry, 2007; Chaffin et al., 2010; Chaffin & Imreh, 2001; Duke et al., 2009; Geiersbach, 2000; Nielsen, 1999a, 1999b, 2004). Advanced and expert musicians also appear to have a mental image of the music from the beginning of their practice, which regulates their practice from the earliest sessions through performance (Chaffin et al., 2010; Chaffin & Imreh, 2001; Nielsen, 1999a, 1999b, 2004). Less clear is which practice strategies are most effective at improving performance. Because musicians’ practice strategies change as they develop, there is also a question of which practice strategies are most appropriate for which level of performer.

Experimental Studies of Practice

Researchers have begun to answer these questions through experimental studies of various practice strategies used by young musicians. The results from these studies are mixed. Young students were able to learn how to diagnose problems and develop strategies to fix those problems and were able to use these strategies consistently (Bauer, 2008; Braun, 2007), but it is unclear if those strategies help students perform better than students who do not use those strategies (Cecconi-Roberts, 2001; Hewitt, 2002). Using a model during practice appears to be a very effective strategy used to improve young musicians’ performance (Henley, 2001; Hewitt, 2001). Also of interest, free practice seems to be as effective as any targeted practice strategies tested by researchers (Cecconi-Roberts, 2001). Clearly, more study is needed to determine the most appropriate practice strategies for young musicians.

Only one researcher has compared musicians of various performing levels in an effort to determine how practice strategies change as performance level changes. Donald (1997) demonstrated that regardless of performance level, practicing using varied tempos was an effective strategy for improving musicians’ performance. Also, even when targeted practice strategies do not result in marked improvement in performance, musicians, when left to their own devices, will create strategies to improve their own performance regardless of their performance level (Kostka, 2000).

There are few studies that have investigated the specific practice strategies most effective at improving advanced musicians’ performance. Rosenthal, Wilson, Evans, and Greenwalt (1988) found free practice may be as effective as any targeted strategy and that modeling helped to a certain degree. Coffman (1990), however, found very few differences between practice strategies when participants were asked to use them for a limited amount of time.

When considering all levels of musicians, surprisingly few of the practice strategies tested have been shown to improve performance significantly. Strategies such as silent practice, singing, silently studying the music, error detection, and self-evaluation were not shown to be consistently effective practice strategies (Coffman, 1990; Cecconi-Roberts, 2001; Hewitt, 2001, 2002; Kostka, 2000; Rosenthal et al., 1988). Practicing using varied tempos appeared to be an effective strategy; musicians who used some sort of slow practice showed improvement in their performance or at least felt it improved their performance (Braun, 2007; Cecconi-Roberts, 2001). Listening to models also was an effective practice strategy (Henley, 2001; Hewitt, 2001; Rosenthal et al., 1988). Some researchers have used free practice as a control in their studies (Cecconi-Roberts, 2001; Kostka, 2000; Rosenthal et al., 1988) and discovered that when musicians were left to choose their own practice strategies, they performed as well as those using targeted strategies.

Purpose

Previous research has not determined which specific practice strategies are most effective at improving student performance. In an attempt to answer a small part of this larger question, the purpose of the current research was to determine the effects of specific practice strategy use on university string players’ performance.

Method

Participants

Participants were string players enrolled in orchestra at a major research university in the southern United States. This university did not have a school of music, and therefore, the orchestra was composed of nonmusic majors. The researcher set 40 participants as the target goal for the study and took volunteers until the population reached this number. Participants completed a demographic questionnaire that gathered information including participants’ age, gender, classification in school, and instrument played. Of the 40 participants in the study, 19 were female (48%) and 21 were male (53%). Participants were between 17 and 23 years of age (M = 19.70, SD = 1.34). Six participants were seniors (15%), 8 were juniors (20%), 7 were sophomores (18%), 13 were freshman (33%), and 6 did not indicate their classification (15%).

I also sought to discover background information, including how long participants had played their instruments, if participants had ever taken private lessons, and, if so, how long participants had studied. Twenty participants played violin (50%), 3 played viola (8%), 14 played cello (35%), and 3 played bass (8%). Participants had played their instruments between 4 and 15 years (M = 9.06, SD = 1.88); 36 (90%) had taken private lessons at some point in their musical learning, while 4 (10%) had not. The participants who had taken lessons reported studying privately between 2 to 12 years (M = 5.96, SD = 2.82).

On the questionnaire, participants were asked to indicated how often they practiced, how long those practice sessions lasted, and which strategy of the three test strategies most applied to their own practice. Reponses indicated that 15 (38%) practiced daily, 14 (35%) practiced weekly, 9 (23%) practiced monthly, and 2 (5%) never practiced. Six (15%) participants indicated that their practice sessions were less than 30 min, 24 (60%) practiced between 30 and 60 min, and 10 (25%) practiced between 60 and 90 min. Participants were asked which strategy they used most often in their own performance from among the three practice strategies to be tested: play slowly then gradually speed up, repeat small sections, and play the excerpt multiple times. Thirteen (33%) participants reported most often using the strategy of playing slowly then gradually speeding up, 22 (55%) most often used the strategy of repeating small sections, 3 (8%) most often used the strategy of playing the excerpt multiple times, and 2 (5%) indicated that they most often used both the strategies of playing slowly then gradually speeding up and of repeating small sections.

Materials

The study music was taken from Sinfonia No. 2 in D major by Mendelssohn, which I chose because the university orchestra was going to perform this work as part of its first concert. This music selection allowed the participants to sight-read music they would actually be performing. For the purposes of this study, I selected to use the exposition of the first movement. The excerpt was in common time at a fast tempo, quarter note = 138 beats per minute (bpm), and was 33 measures long. The excerpt began in the key of D major and modulated to the key of A major. Each excerpt was divided into five separate phrases, and the phrases were numbered as such for the purposes of this research.

Instrumentalists in the study practiced different music, which corresponded to their particular instrumental part for the piece. The violin excerpt was composed primarily of faster notes (eighth and sixteenth notes), included chromatic passages and accidentals, and required violinists to shift into higher positions. The viola excerpt was similar but had fewer passages of fast notes and did not require the players to shift position. The cellists and bassists used the same music for their excerpt, as was common in orchestral literature of the time. The cello and bass excerpts had even fewer fast notes but still contained accidentals and chromatic passages. For cellists, the excerpt could be played primarily in first position with the exception of three notes, which required the players to shift into second position. For bassists, the excerpt required more shifts in order to manage the higher notes and chromatic passages.

The scoring instrument was based on the procedures of the Farnum String Scale (Farnum, 1969). The Farnum String Scale was developed from the Watkins-Farnum Performance Scale, a sight-reading scale for woodwind, brass, and percussion players. This scale, along with its judging procedures, has been found to be reliable (r = .97) and correlated to teachers’ rankings of musicians’ sight-reading scores (r = .75) (Stivers, 1972). In keeping with the Farnum String Scale’s judging procedures, judges in the current study scored participants’ performances by subtracting points when participants made pitch, rhythm, or expression errors (33 points each). Mistakes were counted per measure for each of the musical categories for a possible 99-point total.

During the treatment portion of the experiment, the proctor gave performance and practice tempos using a McAdams Model 20 metronome. Time was kept using a Sportline Model 226 stopwatch. All treatment sessions were digitally recorded and edited using a Sony IC Recorder and were transferred to Apple iTunes, where they were coded for later scoring. Codes were randomly assigned, stratified by instrument, by using an online random number generator ( http://www.random.org). Pretest and posttest performances were then transferred to a CD-R for playback. Playback equipment consisted of a Panasonic SA-PT950 DVD/CD player with Panasonic SA-PT950-AC speakers.

Procedure

Students who were registered for orchestra received information about the study through e-mail 4 weeks before classes began. Once they arrived on campus, students came to the orchestra room to complete a required audition for the class. While there, potential participants were given an information sheet describing the study in detail and were given the opportunity to volunteer. Once the student had agreed to participate, he or she was taken into the testing room, where the proctor explained the general procedures of the test. Participants were then given an opportunity to look at the excerpt and were asked if they had played or were familiar with the study’s music. If a participant answered yes to either question, then that volunteer was excused. Two volunteers were excused from the study because they had prior experience with the music.

The remaining participants who were not familiar with the music were given the performance tempo, 138 bpm, and were asked to study the music for 1 min without playing or fingering. The metronome was turned off during the 1-min study period. After 1 min, the proctor started the recorder, announced the participant’s test code, and gave the performance tempo again. Once the proctor turned off the metronome, the participant sight-read the exercise, which served as the pretest. Leaving the recorder on, the proctor then instructed the participant to practice the excerpt for 10 min using one of the following, randomly assigned, practice strategies:

Free practice: Participants used any strategy they felt was best to learn the excerpt.

Play slowly then gradually speed up: Participants were given a starting tempo of 78 bpm and were asked to play through the entire excerpt at that tempo, after which a tempo of 88 bpm was given and the participant was asked to play through the excerpt again. This procedure occurred eight times, each time increasing in tempo (i.e., 98, 108, 118, 128, 132, 138) until the participant reached the target tempo of 138 beats per minute.

Repeat small sections: The participant was given the performance tempo of 138 bpm and was asked to practice only the first section of the excerpt for 2 min at tempo, after which the participant practiced the second section for 2 min. This procedure continued for each of the five sections of the excerpt.

Play the excerpt multiple times: The participant was given the performance tempo of 138 bpm and was asked to play through the entire excerpt as many times as possible at tempo during the 10 min of practice.

After the treatment, participants were given 1 min of rest, in which the proctor turned the study music over on the stand and asked the participant to sit quietly. After the rest, the proctor turned the music back over and gave the performance tempo of 138 bpm again. Once the proctor turned the metronome off, participants performed the music one last time, which served as the posttest. At the conclusion of the test, the proctor asked participants to complete the short questionnaire.

After all treatment sessions were completed, participants’ pretest and posttest performances were edited for scoring. Three judges, with 18 to 31 years of string playing experience (M = 26.00, SD = 7.00) and 6 to 17 years of teaching experience (M = 13.33, SD = 6.35), were recruited for scoring. All 80 performances, which included a pretest and a posttest for each participant, were played back in an order that was stratified randomly by instrument for judging.

Results

Interjudge reliability, calculated using the Pearson r correlation with the Fisher z transformation, was acceptable (r = .87). Pretest and posttest mean scores were used to compute a two-way analysis of variance (ANOVA) with repeated measures for test and strategy using participants’ overall scores. A significant main effect by test was found, F(1, 36) = 44.59, p < .01, η² = .55. As shown in Table 1, total overall scores for participants’ pretests were lower than total overall scores for participants’ posttests, indicating that participants significantly improved their overall performances between pretest and posttest. Results also indicated no significant main effect by strategy, F(3, 36) = .69, p = .57, and no significant interaction between test and strategy with regard to overall scores, F(3, 36) = .37, p = .78. Participants improved their overall performance significantly regardless of practice strategy used.

Table 1.

Means and Standard Deviations of Participants’ Overall, Pitch, Rhythm, and Expression Scores by Strategy.

	Overall Scores		Pitch Scores		Rhythm Scores		Expression Scores
Strategy	M	SD	M	SD	M	SD	M	SD
Pretest
1	75.57	11.01	23.93	3.82	21.13	6.39	30.50	1.72
2	74.37	12.79	24.20	5.62	20.93	5.30	29.23	29.23
3	73.23	12.13	22.23	4.99	20.83	5.95	30.17	2.39
4	67.07	12.10	21.40	5.02	17.10	6.06	28.57	2.55
Total	72.56	12.02	22.94	4.86	20.00	5.95	29.62	2.52
Posttest
1	82.83	11.27	26.87	4.20	24.97	7.15	31.00	1.54
2	81.63	13.34	25.73	4.61	25.54	7.32	30.37	2.54
3	80.20	14.66	25.17	6.19	23.97	7.14	31.07	2.08
4	77.07	12.05	24.00	4.59	23.70	6.91	29.37	2.33
Total	80.43	12.58	25.44	4.87	24.54	6.89	30.45	2.18

Note: Strategy 1 = free practice, Strategy 2 = playing slowly then gradually speeding up, Strategy 3 = repeating small sections, Strategy 4 = playing the excerpt multiple times.

A three-way ANOVA with repeated measures was calculated using pretest-posttest, musical category score, and strategy. A significant main effect was found for test, F(1, 36) = 44.60, p < .00, η² = .55. Participants’ mean scores improved between pretest and posttest with regard to total pitch, rhythm, and expression scores (see Table 1), indicating participants significantly improved all aspects of their performance between tests. A significant main effect also was found for score, F(2, 36) = 83.82, p < .00, η² = .69, which indicated participants had differences between their pitch, rhythm, and expression scores. No significant main effect was found for strategy, F(3, 36) = .69, p = .57, and no significant interactions were found between score and strategy, F(6, 72) = .40, p = .87; between test and strategy, F(3, 36) = .36, p = .78; or among score, test, and strategy, F(6, 72) = .96, p = .46. This indicated that participants improved their performance in each musical category between pretest and posttest regardless of which strategy they used.

The ANOVA did reveal a significant interaction between score and test, F(2, 72) = 12.75, p < .00, η² = .25. Participants’ expression scores were higher than their pitch scores, which were higher than their rhythm scores, on both pretest and posttest. However, participants improved their rhythm scores most, followed by their pitch scores and then their expression scores (see Table 1).

Additional Analysis

In close examination of the data, it appeared to me that a difference between instruments may have existed. Although comparing instruments was not explicitly a purpose of this study, I decided to investigate this further and computed a two-way ANOVA with repeated measures to compare instruments and test scores. Results confirmed the significant main effect by test, F(1, 36) = 47.99, p < .01, η² = .51, and an additional significant main effect by instrument, F(3, 36) = 3.25, p < .05, η² = .21, was discovered. There was also a significant interaction by test and instrument, F(3, 36) = 3.54, p < .05, η² = .11. Mean scores revealed that the cellists had higher total pretest scores than all other instrument groups and higher total posttest scores than the violinists and bassists, although after treatment, scores tended to cluster together (see Table 2, available online at http://jrme.sagepub.com/supplemental). Specifically, the violists and bassists seemed to improve more than violinists and cellists. Examination of the total gain scores by instrument confirmed that violists and bassists improved the most, followed by violinists and then cellists.

Discussion

In this study, I found that all practice strategies tested resulted in significantly improved performance of university string players in the initial stages of learning a specific piece of music. Strategies resulted in no differences with regard to participants’ pitch, rhythm, or expression performances. This result is important as it adds to the limited data describing how specific practice strategies affect advanced (college nonmusic major) musicians’ performance. To date, there have been few experimental investigations of specific strategy use on the performance of older musicians, and some of these studies are more than 20 years old (Coffman, 1990; Donald, 1997; Rosenthal et al., 1988). Of these studies, two have used pianists (Coffman, 1990; Donald, 1997) and one has used woodwind and brass players as participants (Rosenthal et al., 1988), but none have employed string players.

The current study’s findings are surprising because observational studies have shown that musicians who used more analytical practice strategies improved more than musicians who did not use analytical strategies (Duke et al., 2009; McPherson, 2005; Miksza, 2007; Rower & Polk, 2006). In the current study, the strategies that reflected the analytical strategies identified by previous researchers were play slowly then gradually speed up and repeat small sections. The strategy that most reflects nonanalytical practice was playing the excerpt multiple times. Because of the results of these previous studies, I expected to find differences among the strategies tested, but results revealed none.

Free practice was intended to serve as a control in this study as in previous studies (Cecconi-Roberts, 2001; Kostka, 2000; Rosenthal et al., 1988). This was chosen as a control to determine if guided practice strategies were better than individually developed strategies at improving the performance of advanced musicians. The results of the current study indicated that free practice was as effective as any of the strategies tested. A possible reason for this result was that participants’ free practice may have included elements of the other strategies investigated and/or included other strategies that worked as well as the strategies tested. I did not analyze which strategies participants used during free practice, but future researchers may wish to examine advanced students’ free practice more closely to determine if these students use analytical strategies.

Another possible reason for the outcome could have been a Hawthorne effect. The participants in this study all knew their practice habits were being studied. This simple fact could have encouraged participants to focus and work harder during this study than they might normally do in a regular practice setting. Future researchers should consider this possibility and design studies in an effort to mitigate this possibility.

Experience and Performance Level

Several factors may have contributed to the results indicating that all strategies tested resulted in significantly improved performances. One factor may have been the experience of the participants. Musicians with more experience may be able to better control their practice and thus improve their performance (Hallam, 1997a) than those with less experience. In the current study, the advanced musicians had little difficulty completing the practice tasks assigned to them. These students were able to slow their tempos, speed up their tempos, or maintain their tempos as required by the strategy assigned. The advanced musicians seemed to have control over their own practice and technique, and this control may have aided their ability to significantly improve their performance during this study.

Research has shown that through experience, advanced musicians build steadily upon their general musical knowledge, thus helping both their practice and performance (Hallam, 1997a). The participants in the current study possessed years of study and exposure to music that have increased their base of musical knowledge. This general musical knowledge likely has included music reading, finger dexterity, scale practice, and aural expectations based on previous experience playing solo and orchestral music. Using their musical knowledge and previous experiences, the advanced musicians in this study may have been able to better negotiate the intricacies of learning the excerpt.

The general musical knowledge of the advanced musicians in the current study also likely included specific knowledge of practice strategies. In addition to their years of experience, most participants (90%) had taken private lessons. Working with experienced teachers, these participants likely were exposed to multiple practice strategies, including the ones tested. Participants probably honed their practice skills during their practice sessions, which, for most participants, occurred daily or weekly for 30 to 60 min. During these practice sessions, participants may have developed affinities for one strategy or another, as expressed in their responses to the questionnaire item about the three strategies used in this research. Participants’ previous knowledge and use of practice strategies and their own personal preferences may have helped or hindered performance in the current study, especially to the extent that the assigned strategy did or did not match their own preferences.

Performance level may also have played a role in the outcome of this study. As revealed in previous studies, practice tends to change as a person’s performance level increases (Hallam, 1997a, 1998, 2001; Miksza, 2007; Rohwer & Polk, 2006; Sloboda et al., 1996; Williamon & Valentine, 2000). In the current study, the general trend for all strategy and instrument groups was to improve between pretest and posttest. The one exception to this trend that I noticed upon close examination of the data was that the cellists who had been randomly assigned to the group that played the excerpt multiple times did not improve from pretest to posttest. These three cellists had the lowest pretest scores of all cellists in any of the groups, and this may reflect a low technical skill level. In contrast, violinists in the same strategy group had higher pretest scores, likely reflecting higher technical skill, and their scores improved. Perhaps, as suggested by previous research (Hallam, 1997a, 2001), because of their lower skill level, the cellists were not capable of improving their performance on their own. Future researchers should test both the analytical strategies used, such as playing slowly and repeating smaller sections, as well as a nonanalytical strategy, such as repeating the whole excerpt, with musicians of differing ability and experience levels.

Influence of Repertoire

Results showed significantly improved performance regardless of assigned practice strategy. However, there was evidence that the repertoire may have contributed to anomalies between instrument groups. The excerpt used in this study was the same length and tempo for all instruments, but the musical characteristics of the parts were different, as described previously. Differences found among the instruments may actually reflect differences in the difficulty of the excerpts.

The choice of music also may have influenced the significant differences found between the pitch, rhythm, and expression scores. Expression scores were the highest, followed by pitch scores and then rhythm scores. Conversely, rhythm scores showed the most gain between tests, followed by pitch scores and then expression scores. Because the music used in this study was of a fast and technical nature, musicians had relatively few opportunities for expressive music making, and thus few opportunities to make mistakes, and little opportunity to improve the expressiveness of the performance. The possibility exists that the strategies tested in the current study would have produced different outcomes in overall effectiveness or in specific music categories had the music excerpts been different.

Practice Time

Researchers seem to have two views on the importance of time with regard to music practice. One view holds that the amount of accumulated deliberate practice is the most important determinate of the level of musical performance (Ericsson et al., 1993; Sloboda et al., 1996). The other view supports the idea that time spent practicing is less important than the efficiency and effectiveness of practice (Duke et al., 2009; Williamon & Valentine, 2000). The current study indicated that when participants were given equal time in the initial stage of learning, all practice strategies tested resulted in significantly improved musical performance. This outcome may have been different had participants been given more or less than 10 min to practice.

For the purposes of this study, I had selected 10 min for participants to practice. There were two reasons for selecting this amount of time. The first was practical considerations of the music chosen. The excerpt was 33 measures long with a tempo of 138 bpm, meaning one complete performance would take just under 1 min if the given tempo was held throughout. By providing 10 min, participants had the opportunity to practice the music 8 to 10 times during the practice session. I believed this was adequate time to allow for improvement, which was found to be true. The second reason for selecting 10 min was because the results of previous studies using a shorter practice period demonstrated few if any significant differences between strategies (Cecconi-Roberts, 2001; Coffman, 1990; Henley, 2001). I elected to use a slightly longer time period with the expectation of finding differences between strategies. The results of the current study echo those of previous studies, which have found few significant differences between practice strategies in the earliest stages of learning a piece of music.

Results indicated that the 10-min practice session was adequate to result in significantly improved performance. Previous research, however, has demonstrated that differences among practice strategies may emerge over a longer period of time (Miksza, 2007). This research supports the view that variables other than time spent are important factors contributing to the performance of musicians (Duke et al., 2009; Williamon & Valentine, 2000). Perhaps the use of a longitudinal design that provides more time for practice would result in differences between practice strategies.

Implications for Teachers

The finding that free practice was as successful as targeted practice strategies for advanced musicians in the initial stage of learning new music implies that advanced musicians can be left to their own devices to practice, with a reasonable expectation that they will improve as much as if they were using one of the other targeted strategies, at least in the first 10 min of learning a piece of music. Using this finding can be especially helpful for teachers in a full ensemble rehearsal. For example, if an orchestra is in the initial learning stages of a piece of music, and the teacher comes to a place in the music where the students are having difficulty, the general reaction would be to stop and use targeted practice strategies to fix problems in individual instrument sections, thus leaving much of the group not practicing. Instead, the teacher could simply allow the group to spend a few minutes to practice freely, and reasonably expect the same performance outcome. The advantage then is that all students will spend time practicing instead of just the selected instrumental sections. If the performance requires additional improvement, then previous research suggests that the students may benefit from instruction on how to use analytical strategies, such as slow practice or playing smaller sections of music.

Suggestions for Future Researchers

In the current study, results indicated there were differences among performers as a result of instruments played. The likely causes were the choice of study music and different numbers of instruments represented in the experimental groups. Previous researchers (Hallam, 1997b) have theorized that the characteristics of the instruments may interact with practice strategies and music to produce different performance outcomes. Future researchers should equate study music and sample size for instruments in an effort to discover if the effectiveness of a particular strategy is related to which instrument a musician plays.

Future researchers also may consider using a scoring instrument that is more sensitive than the Farnum String Scale (Farnum, 1969), which scores only one expression, pitch, and rhythm error per measure. For example, if a participant made three rhythm mistakes in a measure during the pretest and then made only one mistake in the same measure during the posttest, the rhythm score for that measure would be the same in both cases and not indicative of the improvement. Thus, this scoring process may not have been sensitive enough to be able to show improvement that actually was taking place. A suggestion for future researchers is to make the Farnum String Scale more sensitive by scoring errors by beat rather than measure.

One explanation for the results of this study could have been that advanced musicians have the ability to create an accurate aural image quickly. Previous researchers have shown that advanced and expert musicians are able to create an aural image that guides them through practice and performance (Chaffin et al., 2010; Chaffin & Imreh, 2001; Ericsson et al., 1993; Hallam, 2001), while beginner and intermediate musicians may not be able to create an accurate aural image on their own (Hallam, 2001; Lisboa, 2008). Future researchers should study performers’ abilities to create an aural image and how this image affects their practice and performance.

In this study, college-aged nonmusic majors served as the participants, which is a somewhat unusual population for practice studies. Future researchers should consider additional analysis of this important group. High school music students who choose to continue performing often choose to continue music as an enrichment to their university experience. This is a large and important population that may require university instructors to use strategies different from those used with music majors to be effective.

Conclusion

The purpose of this study was to determine the effects of specific practice strategy use on university string players’ performance. Results indicated that in the first stages of learning a specific piece of music, all strategies tested were effective, resulting in significantly improved performances. Each contribution to knowledge about how practice strategies may improve musical performance has the potential to help students of all levels become better musicians, thereby enriching their lives with the joy of performing music well.

Footnotes

Author’s Note

This article is based on the author’s doctoral dissertation, “The Effects of Specific Practice Strategy Use on University String Players’ Performance,” completed at the University of Houston in 2010.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Author Biography

Paul L. Sikes is an associate director of bands and orchestra at Texas A&M University, College Station. His research interests include the use of effective practice strategies at all levels of performance and the general creativity of musicians.

References

Austin

J. R.

Berg

M. H.

(2006). Exploring music practice among sixth-grade band and orchestra students. Psychology of Music, 34, 535–558. doi:10.1177/0305735606067170

Barry

N. H.

(2007). A qualitative study of applied music lessons and subsequent student practice sessions. Contributions to Music Education, 34, 51–65. doi:10.1177/8755123310361768

Bauer

W. I.

(2008). Metacognition and middle school band students. Journal of Band Research, 43, 50–63. Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/1100000?accountid=7082

Braun

A. M.

(2007). Effects of differentiated-tempo aural models on middle school orchestra students’ attitudes and motivation toward practicing. Dissertation Abstracts International–A, 68. (ProQuest ID 1296104261) Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/908270427?accountid=7082

Cecconi-Roberts

L. A.

(2001). Effects of practice strategies on improvement of performance of intermediate woodwind instrumentalists. Dissertation Abstracts International–A, 24, 1356. (ProQuest ID 728891471) Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/908109044?accountid=7082

Chaffin

Imreh

(2001). A comparison of practice and self-report as sources of information about the goals of expert practice. Psychology of Music, 29, 39–69. doi:10.1177/0305735601291004

Chaffin

Lisboa

Logan

Begosh

K. T.

(2010). Preparing for memorized cello performance: The role of performance cues. Psychology of Music, 38, 3–30. doi:10.1177/0305735608100377

Coffman

D. D.

(1990). Effects of mental practice, physical practice, and knowledge of results on piano performance. Journal of Research in Music Education, 38, 187–196. doi:10.2307/3345182

Donald

L. S.

(1997). The organization of rehearsal tempos and efficiency of motor skill acquisition in piano performance. Dissertation Abstracts International–A, 59, 116. (ProQuest ID 736881241) Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/907628123?accountid=7082

10.

Duke

R. A.

Simmons

A. L.

Cash

C. D.

(2009). It’s not how much; it’s how: Characteristics of practice behavior and retention of performance skills. Journal of Research in Music Education, 56, 310–321. doi:10.1177/0022429408328851

11.

Ericsson

K. A.

Krampe

R. T.

Tesch-Romer

(1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406. doi:10.1037/0033-295X.100.3.363

12.

Farnum

S. E.

(1969). Farnum string scale: A performance scale for all string instruments. Milwaukee, WI: Hal Leonard.

13.

Galamian

(1964). Principles of violin playing and teaching. London, England: Faber & Faber.

14.

Geiersbach

F. J.

(2000). Musical thinking in instrumental practice: An investigation of practice strategies used by experienced musicians. Dissertation Abstracts International–A, 61, 2230. (ProQuest ID 732091991) Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/908067878?accountid=7082

15.

Hallam

(1997a). Approaches to instrumental music practice of experts and novices: Implications for education. In Jørgensen

Lehman

A. C.

(Eds.), Does practice make perfect? Current theory and research on instrumental music practice (pp. 179–231). Oslo, Norway: Norges musikkhøgskole.

16.

Hallam

(1997b). What do we know about practicing? Towards a model synthesizing the research literature. In Jørgensen

Lehman

A. C.

(Eds.), Does practice make perfect? Current theory and research on instrumental music practice (pp. 179–231). Oslo, Norway: Norges musikkhøgskole.

17.

Hallam

(1998). The predictors of achievement and dropout in instrumental tuition. Psychology of Music, 26, 116–132. doi:10.1177/0305735698262002

18.

Hallam

(2001). The development of expertise in young musicians: Strategy use, knowledge acquisition and individual diversity. Music Education Research, 3, 7–23. doi:10.1080/14613800020029914

19.

Henley

P. T.

(2001). Effects of modeling and tempo patterns as practice techniques on the performance of high school instrumentalists. Journal of Research in Music Education, 49, 169–180. doi:10.2307/3345868

20.

Hewitt

M. P.

(2001). The effects of modeling, self-evaluation, and self-listening on junior high instrumentalists’ music performance and practice attitude. Journal of Research in Music Education, 49, 307–322. doi:10.2307/3345614

21.

Hewitt

M. P.

(2002). Self-evaluation tendencies of junior high instrumentalists. Journal of Research in Music Education, 50, 215–226. doi:10.2307/3345799

22.

Jardaneh

(2007). Exploring young piano students’ perceptions of effective practice strategies (Unpublished master’s thesis). University of Ottawa, Ottawa, Canada. Retrieved from http://www.piano.uottawa.ca/wp-content/themes/pianolab/Publications/Motivation/Motivation%20and%20Practice%20Strategies/Exploring%20young%20piano%20students%20perceptions.pdf

23.

Jørgensen

(2004). Strategies for individual practice. In Williamon

(Ed.), Musical excellence: Strategies and techniques to enhance performance (pp. 85–103). New York, NY: Oxford University Press.

24.

Kostka

M. J.

(2000). The effects of error-detection practice on keyboard sight-reading achievement of undergraduate music majors. Journal of Research in Music Education, 48, 114–122. doi:10.2307/3345570

25.

Lehmann

A. C.

Ericsson

K. A.

(1997). Research on expert performance and deliberate practice: Implications for the education of amateur musicians and music students. Psychomusicology, 16, 40–58. Retrieved from http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/907652154?accountid=7082

26.

Leon-Guerrero

(2008). Self-regulation strategies used by student musicians during music practice. Music Education Research, 10, 91–106. doi:10.1080/14613800701871439

27.

Lisboa

(2008). Action and thought in cello playing: An investigation of children’s practice and performance. International Journal of Music Education, 26, 243–267. doi:10.1177/0255761408092526

28.

McPherson

G. E.

(2005). From child to musician: skill development during the beginning stages of learning an instrument. Psychology of Music, 33, 5–35. doi:10.1177/0305735605048012

29.

McPherson

G. E.

Renwick

J. M.

(2001). A longitudinal study of self-regulation in children’s musical practice. Music Education Research, 3, 169–186. doi:10.1080/14613800120089232

30.

Miksza

(2007). Effective practice: An investigation of observed practice behaviors, self-reported practice habits, and the performance achievement of high school wind players. Journal of Research in Music Education, 55, 359–375. doi:10.1177/0022429408317513

31.

Nielsen

(1999a). Learning strategies in instrumental music practice. British Journal of Music Education, 16, 275–291. Retrieved from http://journals.cambridge.org/abstract_S0265051799000364

32.

Nielsen

(1999b). Regulation of learning strategies during practice: A case study of a single church organ student preparing a particular work for a concert performance. Psychology of Music, 27, 218–229. doi:10.1177/0305735699272015

33.

Nielsen

(2004). Strategies and self-efficacy beliefs in instrumental and vocal individual practice: A study of students in higher music education. Psychology of Music, 32, 418–431. doi:10.1177/0305735604046099

34.

Pitts

Davidson

McPherson

G. E.

(2000). Developing effective practice strategies: Case studies of three young instrumentalists. Music Education Research, 2, 45–56. doi:10.1080/14613800050004422

35.

Rohwer

Polk

(2006). Practice behaviors of eighth-grade instrumental musicians. Journal of Research in Music Education, 54, 350–362. doi:10.1177/002242940605400407

36.

Rosenthal

R. K.

Wilson

Evans

Greenwalt

(1988). Effects of different practice conditions on advanced instrumentalists’ performance accuracy. Journal of Research in Music Education, 36, 250–257. doi:10.2307/3344877

37.

Sloboda

J. A.

Davidson

J. W.

Howe

M. J. A.

Moore

D. G.

(1996). The role of practice in the development of performing musicians. British Journal of Psychology, 87, 287–309. doi:10.1111/j.2044-8295.1996.tb02591.x

38.

Stivers

J. D.

(1972). A reliability and validity study of the Watkins-Farnum Performance Scale. Dissertation Abstracts International–A, 34, 815. (ProQuest ID 759656991)

39.

Williamon

Valentine

(2000). Quantity and quality of musical practice as predictors of performance quality. British Journal of Psychology, 91, 353–376. doi:10.1348/000712600161871

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