An Observational Study of Score Study Practices Among Undergraduate Instrumental Music Education Majors

Abstract

The purpose of this study was to investigate undergraduate instrumental music education majors’ score study practices as they related to the effectiveness of their simulated conducting. Participants (N = 30) were video recorded in two sessions in which they completed a 20-min score study session and a simulated conducting performance. In the first score study session, all 30 conductors studied Mini-Suite for Band, Movement 1. In Session 2, participants studied Portrait of a Clown but this time either with a model recording (n = 15) or without one (n = 15). We computed the overall duration of participants’ score study behaviors for both pieces. Additional data included graduate students’ evaluations of participants’ post–score study conducting performances and an inventory of participants’ score study markings. We found a significant difference in the proportion of time spent in score studying activities between the model and no-model condition conductors, with more time spent in gesturing when studying along with a model. Evaluations of participants’ conducting revealed no differences between those conductors who used a model and those who did not while studying Portrait of a Clown. Our analysis of conductors’ score markings revealed a small number of notable differences between stronger/weaker conductors and between model/no-model conditions. Implications for undergraduate conductor preparation programs are discussed.

Keywords

conducting pedagogy conductor preparation preservice teacher preparation novice conductors score study

Score study is considered widely among conducting teachers as one of the most foundational elements of rehearsal and conducting preparation, the importance of which is second only to mastering basic conducting gestures (Deal et al., 1985). Conducting textbook authors, music education researchers, and expert conductors have discussed the significance of having full knowledge of an ensemble score in order to effectively rehearse (Battisti & Garofalo, 1990; Colwell & Hewitt, 2011; Feldman, Contzius, & Lutch, 2016; Kearns, 2011). Through the detailed process of score study, conductors acquire an internal sound image of the music, which ostensibly functions as a mental model for comparison during the ensemble rehearsal (Battisti & Garofalo, 1990). Feldman et al. (2016) suggest that analysis and internalization of the score are essential prior to making any interpretative decisions and that these processes can aid the conductor in detailing rehearsal problems before they occur.

Understanding the individual skills and techniques involved in the score study process is paramount in determining how to most effectively and efficiently instruct novice conductors. Using a metronome during study (Colwell & Hewitt, 2011), humming and/or singing melodic lines (Colwell & Hewitt, 2011; Feldman et al., 2016; Labuta, 2010), and marking gestural reminders in the score (Battisti & Garofalo, 1990; Jordan, 2008; Kearns, 2011) can be useful tools in preparing for rehearsal. Topic areas related to score study include theory and formal analysis, ear training and sight-singing, transposition and clefs, piano and keyboard skills, knowledge of secondary instruments, error detection, and score marking techniques (Battisti & Garofalo, 1990; Colwell & Hewitt, 2011; Crowe, 1996; Forsythe & Woods, 1983; Hochkeppel, 1993; Jordan, 2008; Kearns, 2011; Lane, 2006; Manfredo, 2008). Although these skills often are described in great detail in conducting textbooks and conducting and rehearsal techniques courses, novices may not transfer these processes to their own score studying activities (Lane, 2006). Because conductors often mark musical and gestural reminders into the score, an examination of novice conductors’ score marking practices may help pedagogues determine the most pressing areas of need regarding the teaching of score study strategies.

Numerous conducting texts and essays by expert conductors prescribe a specific order and procedure when implementing the aformentioned skills into score study. The Art of Conducting by Donald Hunsberger and Roy Ernst (1992)—one of the most frequently cited conducting texts used in undergraduate conducting curricula (Silvey, Springer, & Eubanks, 2016)—details a three-part process for score study: (1) conducting an overview of the score, including demographic, historic, and notational information; (2) analyzing structural features, including formal analysis of melodic, harmonic, rhythmic, and textural components and potential conducting issues; and (3) formulating an interpretation by making personal decisions about the music based on the analyses completed during the two previous stages. While other authors (e.g., Battisti & Garofalo, 1990; Green & Gibson, 2004; Labuta, 2010) suggest similar procedures, expert conductors also agree that there should be no single approach to studying a score (Colwell & Hewitt, 2011; Hunsberger & Ernst, 1992). Some pedagogues appear to concur, with Zirkman (1984) reporting that only 5 of 26 conducting teachers surveyed taught a specific method for teaching score study processes. Perhaps effective methods for score study are best developed individually by conductors when they are “based on [their own] personal capabilities” (Hunsberger & Ernst, 1992, p. 51).

The teaching of score study practices in undergraduate course work differs among university conducting faculty. Manfredo (2008) found that in advanced conducting courses, instructors “emphasized” or “highly emphasized” topics related to score study (e.g., transposition, clefs, analysis, types of scores, score marking), whereas in basic conducting courses, instructors reported “no or little emphasis” on these subjects (p. 51). In a study by Romines (2003), 70 undergraduate conducting instructors reported that curricular elements in their undergraduate conducting courses included score marking (87%), transposition (93%), and various clef studies (81%–85%). Despite the high frequency with which these elements of score study appear to be included in undergraduate conductor preparation curricula, learning how students might actually integrate these individual techniques into their own score study practices remains an area for further inquiry.

Researchers also have questioned how various score study strategies might impact conductors’ error detection skills. Conducting along with an aural model—in comparison to listening only—was found to significantly decrease participants’ abilities to detect tempo, balance, articulation, and intonation errors (Forsythe & Woods, 1983). However, when asked to mark these and other errors into the score, no significant difference in error detection was found between the two conditions. Crowe (1996) examined the effects of various score study styles on both the pitch and rhythm error detection abilities of beginning conductors. Results indicated that score study with a correct aural example was significantly more effective than score study with only a score. Conversely, Schlegel (2010) found no effect for score study method (visual only, visual with aural example, or free choice of method) or musical texture (homophonic or polyphonic) on music majors’ error detection of instrumental music. These diverse findings regarding the effects of score study methods, with or without an aural model, on beginning conductors’ error detection abilities suggest further examination may be warranted.

Although reports concerning expert conductors’ score study strategies are found in pedagogical and research literature (Battisti & Garafolo, 1990; Casey, 1993; Ellis, 1994; Wagar, 1991), few investigators have explored undergraduate music education majors’ score study processes. More focused, specific, and expressivity-oriented score study seems to be associated with musical training and experience among undergraduate music education students but not with musical achievement as determined by grade point averages and applied instructor ratings (Lane, 2006). In a survey of choral conducting students, Wine (1995) found that although graduate students tended to mark their scores less than did undergraduates, the particular types of self-reported score marking strategies were similar between groups. Neither Wine (1995) nor Lane (2006) attempted to associate score study procedures with conducting achievement. Researchers have attempted to identify the effects of score study strategies on novices’ nonverbal and verbal conducting behaviors through prescribing sets of specific score study strategies for use before error detection and correction tasks (Crowe, 1996; Hochkeppel, 1993; Hopkins, 1991) and prior to conducting or rehearsing an ensemble (Montemayor & Moss, 2009; Silvey, 2011a; Silvey & Montemayor, 2014). Determining how undergraduates study scores outside of required academic course work and exploring possible associations between discrete score study practices and simulated conducting performances could help conducting pedagogues and music teacher educators understand how novice conductors apply learned techniques to independently prepare themselves to conduct and rehearse ensembles. This additional knowledge could better inform how conducting faculty might optimally sequence and teach score study procedures at the university level.

The primary purpose of this study was to observe undergraduate instrumental music education majors’ score study processes as they related to the effectiveness of their simulated conducting. By examining these processes prior to leading a conducting performance, we sought to answer the following research questions: (1) What score study procedures do novices employ when independently studying a music score? (2) How long do novices spend in various score study strategies while studying a score, and is time spent in particular strategies related to aspects of conductor effectiveness? (3) What musical objectives do novices choose to focus on when studying a score (as seen in their score markings)? and (4) Are differences in these score study procedures evident between stronger versus weaker conductors, according to the effectiveness of their simulated conducting performances?

A secondary purpose of our study was to consider these questions with regard to whether or not the novices had access to a recorded model to support their score study. Effects of model recordings on various aspects of musical behavior such as student performance achievement (Henley, 2001; Hewitt, 2001; Morrison, 2002; Morrison, Montemayor, & Wiltshire, 2004) and undergraduates’ error detection and correction skills (Crowe, 1996; Grunow, 1980; Hopkins, 1991) are well documented. Effects of recordings on the score study process itself, however, seems to be a new area of inquiry. Anecdotal evidence from previous research studies (see Montemayor & Moss, 2009; Silvey & Montemayor, 2014) and our own experiences as teacher educators suggest that novice conductors prefer to have a model recording when possible, and it seems likely that the answers to our research questions (i.e., how novices generate an internal aural image from a conductor score) could look very different in either the presence or the absence of such a recording. Given that recordings (albeit of varying quality) of many selections from contemporary band repertoire are now more readily available than ever via commercial recordings and as YouTube videos (Whitaker, Orman, & Yarbrough, 2014), knowing how such recordings might affect novices’ score study processes and their subsequent conducting performance seems important for developing and refining score study instruction in university conducting preparation programs.

Method

Participants

Participants (N = 30) were a convenience sample of upper-level, undergraduate instrumental music education majors (juniors, n = 10; seniors, n = 20) enrolled at one of three large schools of music in the Midwest or Rocky Mountain regions of the United States, with 10 participants representing each institution. Their mean age was 22.0 years (SD = 0.78), with 20 males and 10 females represented. Twenty-nine of the participants were wind players, while one participant was a violinist with previous experience playing wind instruments. At the time of their participation, students had taken a basic conducting course at their institution and were either currently enrolled in or had completed at least one additional course in advanced conducting or rehearsal techniques. Prior to participant recruitment, we informally discussed the basic conducting/score reading, advanced conducting, and rehearsal techniques courses at our institutions with one another and agreed that our curricula were similar in scope and content (e.g., teaching of patterns/gesture, eye contact, facial expression, transpositions, score reading). A sample size of 30 participants was consistent with recent observational studies (Duke, Simmons, & Cash, 2009; Miksza, Prichard, & Sorbo, 2012). All participants read and signed Institutional Review Board consent forms prior to their participation.

Music Selection

We selected Mini-Suite for Concert Band (Movement 1, Birthday March) by Morton Gould and Portrait of a Clown by Frank Ticheli as the two scores that participants would study. Both pieces had been identified as Grade 2 (out of six) difficulty in the Teaching Music Through Performance in Band series (GIA Publications). Given the short duration of each piece (approximately 2 min) and that portions of both pieces are repeated frequently, we believed that participants would have enough time to thoroughly study both scores in their entirety. We then selected a 1-min portion of each work, representative of the character of the entire work, that featured (a) contrasting articulate and legato sections of music and (b) a consistent, quick tempo to be performed in the ensuing conducting portion of the procedure (mm. 1–42 of Mini-Suite for Concert Band, Birthday March and mm. 1–68 of Portrait of a Clown). (We did not disclose to participants that they would be conducting only a portion of the piece.) Prior to data collection, all participants confirmed that they had never studied, played, or conducted either of the compositions.

Score Study and Conducting Session Procedures

Participants signed up for individual 60-min sessions. During each session, participants were video recorded while completing two score study sessions (20 min each) and two conducting performances (approximately 1 min each). We instructed participants to bring their own conducting batons. Upon entering the room where the score study sessions took place, participants were directed to a table on which were placed the Mini-Suite for Concert Band score, a set of marking materials (including two sharpened lead pencils; one red and one black Papermate felt tip pen; Sharpie highlighters in yellow, green, pink, blue, and orange colors; and Crayola eraseable color pencils in the same colors as the highlighters), three blank sheets of white paper, and a Dr. Beat DB-88 metronome. A piano, adjacent to the table, was available for participants’ use.

Prior to beginning the first score study session, authors at each of the participating institutions read the following instructions to participants: “You will have 20 minutes to study the entire score with the intention of conducting the music at the end of that time. For your score study, feel free to use or not use any of the materials that have been provided.” A digital timer and the video camera were then both started, with this first score studying session ending after 20 min had elapsed. In an effort to provide an additional measure of ecological validity in this study, investigators at each site left the room during participants’ score study sessions.

Immediately following the 20-min score study period for Mini-Suite for Concert Band, Birthday March, participants completed their conducting task. Participants stood facing away from a dark blank wall, with a music stand before them and a digital video camera directly in front of them, approximately 10 ft (4.6 m) away. Participants were asked to conduct mm. 1 through 42 of the music they had just studied as if they were leading an ensemble performance of those measures. (The score indicated a moderate march tempo of around 104 beats per minute.)

After a 5-min break, participants returned to study Portrait of a Clown by Frank Ticheli. All conditions for the second score study session were identical to the first except that now a professional-level model recording (obtained from the Teaching Music Through Performance in Band series of recordings) was made available to half of the participants (n = 15, five at each institution; male, n = 10; female, n = 5). For participants who were assigned randomly to the model recording score study group, a laptop computer (which included a pair of high-quality stereo speakers connected through the audio port) that included an audio file of Portrait of a Clown was placed in the room for their use. Our instructions for these participants now included the additional statement “Feel free to listen to the recording as much as you wish as you study the score.” The 20-min study session then proceeded exactly as before, followed again by a similar conducting task, this time encompassing mm. 1 through 68 of Portrait of a Clown (tempo indication of ca. 160 beats per minute). All video recordings were downloaded onto computer hard drives for analysis.

Analysis

Score study procedures

We analyzed participants’ score studying behaviors in a manner similar to that done by Miksza et al. (2012) in their investigation of young musicians’ practicing behaviors. Although we could not find any previous research that described an observational scheme for analyzing the act of score study, we adopted reports of expert conductors’ score study practices (Ellis, 1994; Wagar, 1991) and advice found in basic conducting textbooks (Hunsberger & Ernst, 1992; Labuta, 2010) as the basis for documenting participants’ score study behaviors. In addition, we informally surveyed conductors at our respective institutions to ascertain their own observable and measurable score study processes. Selected score study practices from each source were compiled into one researcher-created master list that included (a) silent score study, as evidenced by looking at the printed score; (b) score marking with either pens, pencils, or highlighters; (c) piano playing; (d) singing; and (e) gesturing with or without a baton. The master list also included these same five behaviors done while using a metronome and done while playing a recorded model (in the model recording condition) so that in all, 15 distinct observable phenomena were encompassed. These lists appear as matrices in Tables 1 and 2.

Table 1.

Score Studying Behaviors Among Stronger and Weaker Conductors: Mini-Suite for Concert Band, Movement 1, Birthday March (Morton Gould).

	Matrix of Mean Times (N Participants Exhibiting Behaviors Listed)		20-Min Composite Temporal Profile (%)
	Silent	Using Metronome	20-Min Composite Temporal Profile (%)
Stronger conductors (n = 15)
Score study	5:21 (15)	1:05 (9)	6:00 (30)
Score marking	6:32 (15)	1:32 (4)	6:56 (35)
Gesturing	3:05 (13)	1:30 (9)	3:34 (18)
Piano playing	3:55 (12)	2:00 (1)	3:16 (16)
Singing	0:57 (3)	0:10 (3)	0:13 (1)
Weaker conductors (n = 15)
Score study	4:58 (15)	0:32 (8)	5:15 (26)
Score marking	7:20 (15)	3:40 (2)	7:49 (39)
Gesturing	3:05 (15)	2:50 (11)	5:10 (26)
Piano playing	2:09 (10)	0:02 (4)	1:27 (7)
Singing	0:50 (5)	0:13 (3)	0:19 (2)

Note. Durations within matrices (middle columns) are expressed in min:s and reflect means among only those participants who exhibited each particular behavior within a 20-min score study session. As such, these sum totals of durations within each matrix exceed 20 min. By contrast, durations and percentages of time in composite profiles (right column) are computed from among all 15 participants in each group, combining silent and with-metronome behaviors within each category, totaling 20 min (rounding errors notwithstanding).

Table 2.

Score Studying Behaviors Within Model Supported and No-Model Conditions: Portrait of a Clown (Frank Ticheli).

	Matrix of Mean Times (N Participants Exhibiting Behaviors Listed)			20-Min Composite Temporal Profile (%)
	Silent	Using Metronome	Using Model	20-Min Composite Temporal Profile (%)
Model provided (n = 15)
Score study	2:55 (15)	0:25 (4)	0:43 (2)	4:41 (23)
Score marking	6:32 (15)	0:31 (2)	0:28 (10)	6:55 (35)
Gesturing	2:32 (15)	1:23 (5)	4:56 (15)	7:55 (40)
Piano playing	1:20 (1)	—	—	0:05 (0)
Singing	0:34 (6)	0:43 (2)	0:18 (3)	0:23 (2)
No model provided (n = 15)
Score study	4:43 (15)	0:20 (10)	—	4:56 (25)
Score marking	5:51 (14)	3:12 (2)	—	5:54 (29)
Gesturing	3:50 (14)	3:08 (13)	—	6:17 (31)
Piano playing	3:23 (12)	0:43 (3)	—	2:51 (14)
Singing	0:05 (3)	0:07 (2)	—	0:02 (0)

Note. Durations within matrices (middle columns) are expressed in min:s and reflect means among only those participants who exhibited each particular behavior within a 20-min score study session. As such, these sum totals of durations within each matrix exceed 20 min. Dashes indicate no instances of indicated behaviors. By constrast, durations and percentages of time in composite profiles (right column) are computed from among all 15 participants in each group, combining silent, with-metronome, and with-model behaviors within each category, totaling 20 min (rounding errors notwithstanding). Percentages may not total to 100% due to rounding.

To faciliate the measurement of possible behaviors associated with score study that might be evident during the 20-min period, we imported all 60 score study videos (2 excerpts × 30 participants) into the Scribe 4.2 software application (Duke & Stammen, 2011). This program allowed us to track both the frequency and duration of designated score study behaviors. An observation template that included the selected score study practices from our master list was created for video evaluation. We then solicited two music education graduate students (one each from two of our institutions) who each had at least 5 years of public school teaching experience to establish reliability of the measurement criteria. Each reliability observer independently coded 12 (20%) of the 60 videos according to the 15 observable score study behaviors we had provided on our master list. The Scribe output provided for us the total duration of time spent in each score study behavior for each participant, summed across all instances of each behavior. To determine the level of agreement between our two observers, we calculated the difference between them (in seconds) for each of these summed durations, and we calculated the total amount of all discrepancies for each participant. The average per-participant total discrepancy was 1 min 57 s (18 s per observed behavior), or 10% of the total time spent in score study activities. In other words, our reliability observers agreed on the participants’ specific score study activities (per our categorizations) for 90% of the total score study time, with agreement on all individual participants’ score study videos at 80% or better. Deeming this level of agreement acceptable for our investigation, we then divided the remaining 48 videos between the two observers.

Score marking practices

We collected all conductor scores following each participant’s completion of study procedures (60 scores total). Our initial inventory of possible score markings was based on practices advocated in score study, conducting, and instrumental methods textbooks (e.g., Battisti & Garofalo, 1990; Feldman et al., 2016; Hunsberger & Ernst, 1992). We expanded and refined this list based on the participants’ markings that we found in the scores themselves (see Table 3). General categories of our analysis included the variety of marking utensils used, emphasizing or highlighting of particular score features, adding extra information, and use or nonuse of the separate pages of blank paper provided. For each participant, we checked whether or not each kind of score marking per our predetermined list appeared anywhere among their markings in the conductor scores, and we created a frequency list accordingly. To establish reliability, we began our analysis by having two authors independently analyze 12 conductor scores (20%) in common. Agreement was found to be .84 for all categories. We then divided the remaining 48 scores evenly between the same two authors to complete the analysis.

Table 3.

Frequency of Score Study Markings Among Participants (N = 30).

	Mini-Suite, Movement 1		Portrait of a Clown
	Stronger Conductors	Weaker Conductors	Model	No Model
Materials used
Two or fewer colors	1	0	0	3
Three or more colors	14	15	15	12
Highlighting extant score features^a
Dynamics	14	11	14	15
Articulations	8	7	7	5
Expressive instructions	0	0	9	9
Phrases (including breath marks)	0	0	1	3
Instrumentation	12	6	9	4
Marked primary melodic line	7	5	6	3
Marked melodic and other lines	4	9	8	4
Structure	11	14	7	6
Participant-provided information
Direction of musical line^b	6	1	2	3
Expressive words (1–2 instances)	2	4	3	3
Expressive words (3+ instances)	1	1	2	3
Words indicating texture, balance	1	2	1	1
Technical terms	1	1	0	0
Form or structure of music	2	1	2	5
Gestural/conducting indications^c	4	7	9	4
Used separate sheet of paper	0	3	0	2

Note. Adjacent rows of italicized text indicates mutually exclusive categories. For each category, a tally was counted if the feature was exhibited anywhere in the score. Each subgroup, n = 15.

“Highlighting” is broadly construed—could be circled, bracketed, rewritten, and so on.

This could include arrows, added dynamics, breath marks, and so on.

Could include items of potential difficulty for players in ensemble.

Conducting task performances

Video recordings of the 60 simulated conducting performances were presented for evaluation in four different random orders to four graduate students who were enrolled in music education or wind conducting programs at our institutions. Our evaluators also received conductor scores and CD recordings of both pieces and were asked to thoroughly familiarize themselves with each piece prior to completing the evaluation task. In order to discount any possible effects of ambient sounds on the evaluation of these simulated conducting performances, we instructed the evaluators to view these recordings with the volume silenced. On the evaluation sheet, we identified each recording as either Mini-Suite for Band or Portrait of a Clown. We asked evaluators to rate the conductors’ performances in three separate categories, each utilizing a 10-point Likert-type scale: (a) their perceived knowledge of the score, anchored by no knowledge (1) and very knowledgeable (10); (b) expressivity, anchored by not expressive (1) and very expressive (10); and (c) clarity of gesture, anchored by not clear (1) and very clear (10). These criteria and rating procedures were adapted from previous research studies that utilized undergraduate conductors as participants (Silvey, 2011a; Silvey & Baumgartner, 2016).

Results

Conducting Task Performances

Because we considered our three dependent variables to be measuring the same construct (i.e., conductor effectiveness), we averaged evaluators’ ratings of score knowledge, conducting expressivity, and conducting clarity to create an overall composite rating for each of the 60 conducting performances. Reliability among the four evaluators as measured by the intraclass correlation coefficient was acceptable at .75 (Cohen, 1988). Using this composite rating, we tested for possible significant differences among participants according to the institution they attended, finding none for either Mini-Suite for Band, F(2, 27) = 0.054, p = .948, or Portrait of a Clown, F(2, 27) = 0.203, p = .817. We then proceeded with subsequent analyses considering participants from all three sites together as a single group.

For Mini-Suite for Band, we chose to use the evaluations themselves as a grouping variable by dividing the 30 conductors’ ratings in half through the use of a median split. We used an independent samples t test to determine if any differences existed between the conducting performances of those participants who were grouped in either the top 15 or bottom 15 scores. A significant difference was found between the ratings of stronger conductors (M = 6.49, SD = .69) and weaker conductors (M = 4.85, SD = .67), t(28) = 6.614, p < .01. The effect size was large, d = 2.41 (Cohen, 1988). We used these groups in our subsequent analyses of score study behaviors and score marking practices.¹

Again, we used an independent samples t test to compare evaluators’ ratings of participants’ Portrait of a Clown conducting performances. In this analysis, however, we compared ratings of those participants who were assigned to either the model (n = 15) or no-model condition (n = 15).² There was no significant difference in conducting effectiveness between those conductors who did use a model recording during their score study (M = 5.72, SD = 0.83) versus those who did not (M = 5.11, SD = 0.90), t(28) = 1.913, p = .66.

Score Study Behaviors

From the Scribe output, we compiled data regarding the amount of time participants spent in various score study activities according to our list of 15 possible specific behaviors. In order to account for slight discrepancies among participants in their overall score study times, we calculated the sum of the durations of observed behaviors for each participant and then proportionally adjusted the amount of time found in discrete behaviors so as to reflect an overall score study session that was exactly 20 min in duration.³ We then counted the number of participants who exhibited each score study behavior, and from among them, we calculated the mean amount of time spent in each activity.

For the first score (Mini-Suite for Band, Birthday March by Morton Gould), we considered participants’ results according to their composite conducting scores per our median split of stronger conductors and weaker conductors (n = 15 for each). Data for their score studying behaviors are shown in Table 1. Stronger conductors and weaker conductors appeared similar in terms of their use of time during the score studying session for this piece. All participants in both groups engaged in silent score marking, averaging about 7 min in this activity, and in silent score study, to which about 5 min of their time was devoted. Nearly all participants spent time silently gesturing through the music (about 3 min). In addition, many used the metronome while gesturing. Most participants used the piano to support their study. Stronger conductors spent more time playing the piano than weaker conductors. Little time was spent singing.

To create a composite temporal profile measuring how participants within each group spent their score studying time, we computed the average durations in each activity among all participants, combining both silent and with-metronome behaviors. We also computed the proportions of time in each activity, expressed as a percentage. Results are shown in the right column of Table 1. A chi-square test for independence revealed no significant difference between groups in the distribution of time among the five activities, χ²(4, N = 30) = 5.58, p = .23.

We repeated this analysis for participants’ time spent studying Portrait of a Clown by Frank Ticheli. For this particular task, we compared the use of time among participants for whom we provided a model recording against those for whom we did not provide a model (n = 15 for each group). Results are shown in Table 2. The greatest amount of time (approximately 6 min for both groups) was spent in silent score marking. On average, participants in the model recording condition spent nearly 5 min gesturing along with the recording. Those in the no-model condition spent nearly 5 min engaged in silent score study. Piano playing was much more common among those in the no-model group, consuming approximately 3 min. Singing was brief and infrequent for everyone.

Again, we created temporal profiles for both groups, as seen in the right column of Table 2. Both groups spent about a quarter of their time in score study activities (i.e., apart from marking, gesturing, piano playing, or singing). Gesturing accounted for a greater proportion of time in the model recording group (40%) than in the no-model group (31%). Piano playing was nearly nonexistent in the model recording group but represented 14% of the overall time in the no-model group. The distribution of time among score studying activities was significantly different between model and no-model conditions, χ²(4, N = 30) = 15.8, p < .01.

To further explore possible relationships between time spent in discrete score study behaviors and particular aspects of participants’ simulated conducting performances, we performed bivariate correlation tests between actual (i.e., unadjusted) time spent in each of the five categories of studying behaviors (i.e., silent study, score marking, gesturing, piano playing, and singing, with durations summed across silent, with-metronome, and with-model conditions) and each of the component evaluator ratings of participants’ conducting (i.e., score knowledge, expressivity, and clarity) and with the composite conductor rating. To maximize statistical power and because studying conditions were identical between stronger and weaker conductor groups, we analyzed times and scores from Mini-Suite for Band as a single data set; for Portrait of a Clown, model and no-model conditions were analyzed separately. Results are reported in Table S1, available in the online version of the article. Most relationships were weak, and with one exception, none were statistically significant. For 12 of the 15 participants within the no-model group who played piano while studying Portait of a Clown, a modest, positive, significant relationship (r = .618, p = .032) was found between their piano playing time and subsequent evaluations of their conductor score knowledge.⁴

Score Marking Practices

Our analysis of participants’ score markings appears in Table 3. For Mini-Suite for Concert Band, nearly all participants used multiple score coloring utensils for marking the score. Dynamics was the most common musical feature identified in the scores. Most participants identified some component of the structure of the piece in their markings, such as meter, key, form, or tempo. In addition, a majority of participants identified melodic material in the scores. Slightly more participants whom we identified as weaker conductors also marked secondary lines. Twice as many stronger conductors (12) than weaker conductors (6) identified some aspect of instrumentation within the scores.

Participant-provided information (e.g., text regarding style, added dynamic or phrase markings) appeared much more infrequently among score markings. Six of the stronger conductors wrote some aspect of phrasing or the direction of the musical line into their scores, whereas only one of the weaker conductors did so. Few other differences between groups were apparent or notable.

Score markings for Portrait of a Clown were generally similar to those found in Mini-Suite for Concert Band. Twice as many participants who were provided a model to support their score study marked melodic lines in their scores or melodic and secondary lines (6 and 8, respectively) than did participants who were not provided with a model (3 and 4, respectively). Perhaps related to this phenomenon was the finding that gestural indications were more common in the model group (9) than in the no-model group (4), as was highlighting aspects related to instrumentation (again, 9 vs. 4). Other score markings were similar between groups.

Discussion

The purpose of this study was to investigate undergraduate instrumental music education majors’ score study practices as they related to the effectiveness of their simulated conducting. Regardless of whether conductors had been grouped as stronger or weaker as a result of their Mini-Suite for Band conducting evaluations, there was a great deal of similarity between these two groups in the amount of time spent in various score study strategies. Both groups spent approximately 60% of their 20 min either studying silently or marking their score and 20% of their time gesturing either with or without the aid of a metronome. Participants also marked the score frequently by using the pens, pencils, and highlighters that were provided for their use. This result is consonant with expert conductors’ and conducting pedagogues’ suggestions of providing markings when learning scores (Battisti & Garofalo, 1993; Colwell & Hewitt, 2011; Green & Gibson, 2004). Having a score marking system would seem beneficial not only for undergraduate conductors who are just learning how to conduct and rehearse but especially for secondary school instrumental music teachers who may not feel they have enough time to thoroughly study their music scores. Given that Zirkman (1984) found that many conducting teachers did not prescribe a specific method of score study in their undergraduate conducting classes, perhaps conducting teachers should consider a more formal process of teaching score study processes in the hopes of promoting a more efficient way of internalizing the music.

Overall, participants in both groups tended to mark or otherwise highlight the most salient features of the music, particularly dynamics and primary and secondary melodic lines. Relatively few participants added information of their own into the scores. This may suggest that novice conductors are most concerned with “getting through” the score—that is, knowing when conducting patterns ought to be larger or smaller in order to reflect the dynamics and being aware of which melodic lines to cue. Despite the 20 min they had to study a comparatively brief piece of music, few conductors added expressive or interpretive indications into their scores. Certainly, successfully navigating through a score is important; these results may serve to remind teacher educators that doing so is a novel task for new conductors and one that commands a considerable proportion of their attention. Collegiate music faculty may wish to help guide prospective ensemble teachers to be able to identify the expressive elements in their conductor scores as well.

It may be noteworthy that added markings regarding phrasing or the shape of the musical line appeared more frequently among the stronger conductors. Determining whether or not a causal relationship to this phenomenon exists, in either direction, remains an area for future inquiry. It is also interesting to note that several of the stronger conductors who had marked phrasing or the shape of the musical line did not add expressive markings to their scores. For them, the expressive aspects of the score may have already been apparent to them and did not need highlighting. This may represent the beginnings of a deep understanding of the subject matter, reflective of expert teachers, which might ultimately be seen in lesson plans and classroom instruction as well (Berliner, 1986; Borko & Livingston, 1989; Shulman, 1987).

The results of our observational data on Portrait of a Clown suggest that novice conductors’ score study procedures were influenced heavily by the use of a model recording. Within the model-supported condition (randomly assigned), all 15 conductors gestured along with the provided recording, which on average accounted for 40% of the total 20-min score study period. Furthermore, only 1 of the 15 conductors elected to use the piano when the model was made available, even though many of these same conductors used the piano in the Mini-Suite for Band score study session. We did note, however, that the percentage of total time spent by participants who gestured and played the piano in the no-model condition (44%) was similar to those participants in the model-supported condition who gestured along with the recording (40%). Because it would be difficult to gesture and play the piano simultaneously, we believe that both groups used the score study tools at their disposal (i.e., piano or recording) to most rapidly develop an aural image of the music they were studying.

Although many expert conductors advocate against the use of a model recording when first learning a score (Ellis, 1994; Toney, 2000), the use of the provided model recording was a prominent feature during these conductors’ score study sessions. There may be a need for conducting teachers to more explicitly present the strengths (e.g., accurate recordings, informed interpretations) and weaknesses (e.g., poor performances, adoption of a single interpretation) of using model recordings during the act of score study.

The model seemed to prompt among conductors twice as many markings related to identifying melodic and secondary lines and twice as many added indications regarding gestural cues compared to the no-model group. Viewed somewhat cynically, this may represent how a model functions as a shortcut for informing a novice conductor “how the piece goes.” Noting again, however, the higher proportion of time spent gesturing during the score study session, particularly gesturing along with the model, we are reminded that music listening prompts neurological responses related to movement (Chen, Penhune, & Zatorre, 2008; D’Ausilio, 2007; Lahav, Saltzman, & Schlaug, 2007) and that the use of musical models may yield at least a short-term performance advantage in subsequent motor behavior (Cash, Allen, Simmons, & Duke, 2014). For conductors, deliberately withholding or delaying opportunities for music listening may be counterproductive for some elements of musical performance in the near term, however well intended. In our study, model group participants’ conducting was rated higher than those from the no-model group but not significantly so. This may indicate the model group participants’ still-developing skill level in being able to translate the sounds they hear in their mind into gesture (Silvey & Montemayor, 2014). While it does provide an aural model of the music, some pedagogues suggest not listening to a recording during the initial stages of score study to “allow the musical mind to develop the structure, mood, phrasing, tempo, and the desired artistry” (Colwell & Hewitt, 2011, p. 342). Creating an aural image of the music purely from examination of the score appears to be paramount in such an approach. Feldman et al. (2016) advocate listening to a recording early on “to get a sense of the piece and its sound world” (p. 172), highlighting a stark contrast in the philosophical approach toward use of an aural model. At the least, our data indicated no particular deleterious effects of studying a score along with a recorded model, per the behaviors examined herein (notwithstanding goals such as exercising score reading abilities or developing a personal interpretation of the music). Further study on these matters might lead to insights regarding how recorded models might best be judiciously incorporated in the musical training of those new to ensemble conducting.

Because we divided those conductors who studied the Mini-Suite for Band score through the use of a median split, it is not surprising that we found a significant difference favoring the stronger conductors’ performances over the weaker conductors’ performances (M = 6.49, SD = .69; M = 4.85, SD = .67, respectively). Although both sets of conductors were observed having spent a similar amount of time in various score study activities (e.g., silent score study, score marking, gesturing), there was one notable difference between groups—stronger conductors spent a greater average amount of time playing piano than the weaker conductors (3 min, 16 s vs. 1 min, 27 s, respectively). Without any other external means of hearing the music, the stronger conductors appeared willing to play parts on the piano, a score study strategy that is suggested often by conducting pedagogues during the initial stages of learning a piece of music (Hunsberger & Ernst, 1992; Labuta, 2010). It is unclear if the stronger conductors were also stronger pianists; however, because all participants held junior or senior status, they previously had completed a four-semester sequence of class piano prior to participating in the study. Undergraduate conducting teachers may consider making students externalize the music they are preparing through singing, humming, or playing lines on their primary instrument in accordance with suggestions found in conducting textbooks (Colwell & Hewitt, 2011; Feldman et al., 2016; Labuta, 2000). Having novices demonstrate these musical ideas might help them internalize the music more quickly than just silently studying or marking the score. Future researchers should consider experiments that compare various external score study strategies on novices’ conducting and rehearsal techniques.

We acknowledge that a possible limitation of our study was asking participants to conduct the piece (in simulated fashion) at the end of the 20-min score study session, which may have conceivably altered the nature of their score study. However, we did leave the room during their score study sessions, and we selected excerpts that we believed were brief enough to be studied thoroughly in the alloted 20 min. One could reasonably assume that the goals of score study would (and perhaps should) change based on the level of musicianship of the ensemble members, the difficulty of the repertoire, and the temporal proximity of the performance. Although score study is considered an essential topic by conducting faculty and undergraduate conducting students (Manfredo, 2008; Silvey, 2011b; Silvey et al., 2016), further examination of conducting instructors’ and in-service teachers’ score study attitudes and practices would provide conductors of all experience levels with further insight on the particular short-term and long-term goals of score study and the underlying assumptions that guide these procedures.

The solitary and idiosyncratic nature of score study makes it difficult for conducting teachers to gain a full understanding of what undergraduates do when they study an ensemble score. In this investigation, we sought to illuminate what happens when novice conductors undertake the process of score study independently. We believe that our data give pedagogues and researchers helpful information about the types of score study strategies that are employed and preferred by undergraduate conductors. Even if some experts believe there is “no single ‘best’ procedure” for approaching score study (Colwell & Hewitt, 2011, p. 340), much can still be learned about the introduction and sequencing of score study activities in undergraduate conductor preparation programs.

Footnotes

Acknowledgements

We thank Will Ecker (University of Northern Colorado), Brad Regier (University of Oklahoma), and Aaron Wacker (University of Missouri) for their assistance in analyzing our conductors’ score study behaviors.

Declaration of Conflicting Interests

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

Funding

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

Notes

Author Biographies

Brian A. Silvey is an associate professor of music education and the interim director of bands at the University of Missouri. His research interests include conductor effectiveness and expressivity, instrumental music teacher preparation, and conductor pedagogy.

Mark Montemayor is a professor of music and the head of music education at the University of Northern Colorado. His research interests include teacher evaluation and the cognitive psychology of music instruction.

Christopher M. Baumgartner is an assistant professor of music education at the University of Oklahoma. His research interests include music student teaching, mentoring beginning music teachers, and instrumental music methods and conducting.

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