Résumé
Bien que la recherche en éducation ait démontré que l’enseignement explicite des stratégies constitue une approche pédagogique efficace, nous ne possédons encore que très peu de connaissances au sujet des stratégies qu’emploient les étudiants en musique pour apprendre le solfège, des facteurs contribuant à leur utilisation et du rôle qu’elles jouent dans la réussite des étudiants. Cet article se penche sur ces questions. Deux cent soixante-douze (n = 272) étudiants en musique de niveau collégial inscrits à des cours de formation auditive jazz et classique ont été recrutés pour cette étude. Durant deux semestres, les participants ont été invités à répondre à trois questionnaires visant à mesurer leur utilisation des stratégies et à documenter leurs expériences musicales. Les données ont été mise en relation avec les résultats obtenus dans les cours de solfège. Des analyses factorielles ont d’abord révélé la présence de onze types de stratégies, regroupées en quatre catégories : les mécanismes de lecture (décodage des hauteurs, aides extérieures, modèles schématiques, analyse musicale); la lecture à vue chantée (préparation, performance); la pratique personnelle (gestion des répétitions, intériorisation, techniques de répétition); le soutien à l’apprentissage (métacognition, socio-affectivité). Les analyses ont ensuite montré que l’utilisation des stratégies était liée à plusieurs caractéristiques individuelles : le genre, les habiletés scolaires, l’oreille absolue, les expériences musicales informelles, les expériences musicales collectives, l’instrument principal, les connaissances en théorie musicale ainsi que la connaissance de la notation musicale. Les analyses multivariées ont finalement montré que les stratégies employées contribuaient significativement, mais faiblement, à la prédiction des résultats en solfège. Les stratégies de performance, relatives à la situation de lecture à vue chantée, était directement associé à la réussite en solfège, tandis que toutes les autres jouaient un rôle de médiation entre les facteurs individuels et les résultats en solfège.
Abstract
While the benefits of integrating explicit teaching of strategies has been highlighted in the literature for many educational contexts, we know very little about the strategies employed by college music students in the context of sight-singing acquisition, the factors contributing to their use, and their relationships with sight-singing outcomes. This paper addresses these issues. A total of 272 music students attending classic and jazz aural skills classes completed a music background questionnaire and a strategy inventory over two semesters. The collected data were analyzed in relation to their sight-singing grades. Factor analysis revealed eleven components grouped in four major themes: 1) reading mechanisms (pitch decoding, external support, common melodic patterns, music analysis), 2) sight-singing (preparation, performance), 3) personal practice (practice management, internalization, rehearsal techniques), and 4) learning support (socio-affective, metacognition). The findings show that strategy use is related to several individual characteristics: gender, academic achievement, absolute pitch, informal music experiences, collective music experiences, piano playing, knowledge in music theory, and notation knowledge. Multivariate analysis indicated that spontaneous strategy use offers a small but significant contribution to the overall prediction of sight-singing grades. Strategies relative to sight-singing performance were directly related to sight-singing grades, while other strategies only mediated the relationships between individual characteristics and sight-singing grades. Keywords: strategies, sight-singing, aural skills, success factors, music education
Introduction
This research aims to investigate the relationships between the use of spontaneous sight-singing strategies, individual characteristics, and sight-singing grades in aural skills classes among college- level music students. While the benefits of integrating explicit teaching of strategies has been highlighted in the literature for many educational contexts, we know very little about the strategies employed by college music students in the context of sight-singing acquisition, the factors contributing to their use, and their relationships with sight-singing outcomes. This paper addresses these issues.
Predictors of sight-singing performance
For several decades, most research on sight-singing has tried to determine the best predictors of performance, and several factors have been identified. In a series of publications in the early 1990s, Harrison and his colleagues showed that sight-singing performance was predicted mainly by music ability, academic ability, and music experience (Harrison et al., 1994). In our ongoing project (unpublished manuscript), we have deepened this knowledge with new data on the nature of the experiences related to aural skills performance. Using regression analysis with a large set of predictors, we found that collective music experiences (i.e. orchestra, choir, theory), informal musical experiences (i.e., playing-by-ear, improvisation, music listening), and piano playing were significantly associated with higher performance in aural skills. We also observed that aural skills were related to absolute pitch, notation knowledge, and music theory achievement. But this picture might not be complete. In the light of many findings in educational research, learning strategies could be an additional key to understanding sight-singing achievement and, in the long term, for improving the quality of learning in aural skills classes.
Learning strategies
Since the mid-70s, learning strategies have been the main focus of a great deal of educational research. A common belief was that identification of the most “desirable” strategies and schemas from expert learners could lead to optimal teaching and learning. Strategies spontaneously used by learners have been described and theorized in various ways (Kouba, 1989; O’Malley, Chamot, Stewner-Manzanares, Kupper & Russo, 1985; Paris et al., 1983; Weinstein & Mayer, 1986). Although there has been no consensus on a single taxonomy of strategies, distinctions are often made between three broad categories: cognitive strategies, metacognitive strategies, and socio-
affective strategies (Ardasheva et al., 2017). Strategies spontaneously used by students have been found to be associated with several demographic and psychological traits, for example, age, sex, cognitive style, motivation, autonomy, epistemological belief, and awareness of one’s mental operations (Montague & Boss, 1990; Oxford & Nyikos, 1989; Ryan, 1984). Differences between high- and low-achieving learners have been found in their spontaneous use of strategy in areas such as reading comprehension, math, and second-language learning (Anderson, 1991; Golinkoff, 1975; Pockey & Blumenfeld, 1990; Zimmerman & Martinez-Pons, 1990). Research in this field has led to a very effective teaching approach: explicit strategies instruction. Hundreds of experimental studies have demonstrated the positive effects on learning outcomes (e.g., Ardasheva et al., 2017; Berkeley & Lason, 2018; Chiu, 1998; Dennis, Sharp, Chovanes, Thomas, Burns, Custer & Park, 2016; Donker, de Boer, Kostons, Dignath van Ewijk, & van der Werf, 2014; Dignath & Bütter, 2008; Dignath, Bütter, & Langfeldt, 2008; Hattie, Biggs & Purdie, 1996; Mancho, 2018; Plonsy, 2011; Swanson et al., 2013).
Sight-singing strategies
In music education research, learning strategies have become increasingly interesting to researchers (Bogunović, 2018; Buonviri, 2019; Després, Burnard, Dubé & Stévance, 2017; Hallam et al., 2019; Mawang, Kigen & Mutweleli, 2018; Woody, 2019), but few papers have been published on sight-singing at the college level. The rare publications mostly describe and categorize the strategy used without relating it to individual characteristics or proficiency level (Carlson, 2016; Fournier et al., 2019; Thompson, 2003; 2004). Most of the strategies are summarized in a framework by Fournier et al. (2019). Their proposal, which includes 72 domain- specific strategies, encapsulates four major practical themes: 1) reading mechanisms (pitch decoding, pattern building, validation), 2) sight-singing (preparation and performance), 3) reading skills acquisition (musical vocabulary enrichment, symbolic associations, internalization, rehearsal techniques), and 4) learning support (self-regulation, attention, time management, motivation, stress). Although this categorization has clear implications for aural skills pedagogy, it relies chiefly on qualitative analysis and has not yet been validated empirically with a larger population.
We have found only one paper in which relationships between strategy use and individual characteristics are investigated at the college level. Vujović and Bogunović (2012) reported significant differences in strategy use according to sex, music specialization, expertise in music
theory, and self-assessment of sight-singing proficiency. The relationships described by Vujović and Bogunović (2012) are relevant, but they are far from providing a complete picture. The strategies were studied without using adequate strategy inventory, and most of the predictors of sight-singing success were omitted. Furthermore, the authors did not have an adequate measurement of sight-singing performance and, therefore, could not investigate the relationships between the strategy used and sight-singing achievement.
Study aims
Our review of the literature indicates that there is a huge gap between current knowledge in educational research and what needs to be understood to implement explicit sight-singing strategy instruction. The research reported here aims to extend current knowledge by using the framework devised by Fournier et al. (2019) to study more systematically the relationships between strategy use, individual characteristics, and learning outcomes in aural skills classes. The research questions are:
1. To what extent do the empirical data support Fournier et al.’s (2019) framework? 2. What relationships are there between strategy use and the predictors of sight-singing? 3. How is strategy use related to sight-singing performance?
Method
ParticipantsData were collected from college-level music students attending jazz or classical aural skills classes at the time of the study. A total of 272 participants took part. The majority were enrolled in a two-year program (64.7%), while the rest were in a three-year program. At the time of the study, 45.9% of the respondents were in their first year, 44.4% were in their second year, and 9.7% were in their third year. Just over half of the participants were in a jazz profile (57.7%). Their ages ranged from 16 to 35 (M = 18.57, SD ≤ 2.27), and there were slightly more men than women (57%). All instrumentalist and vocal groups were fairly represented: guitar/bass (21%); piano/keyboard (16.9%); voice (16.2%); woodwinds (14.0%), brass (11.8%), drum/percussion (10.3%), and strings (9.9%). Each aural skills course was offered for different levels. One hundred and thirty-nine (139) were in low-level aural skills classes (51.1%), 92 in intermediate classes (33.8%), and 41 were in advanced classes (15.0%).
Data source
School records
Demographic information as well as data relative to academic and music achievement were collected through school records (sex, year, jazz/classical profile, high school GPA, music theory placement test, sight-singing grades).
Music experience questionnaire
A self-report questionnaire was used to collect data related to music experiences. Questions were grouped by major age periods (0-5 years; 6-11 years; 12-17 years; more than 17 years) and asked participants information about their collective music experiences (number of years of experience in orchestra, number of years of choral experience, number of years of music theory classes, number of years of aural skills classes), informal music experiences (listening to music, attending concerts, singing with family, playing by ear, improvising, composing, learning an instrument by themselves, playing in a band), music reading expertise, and whether they had absolute pitch. The questionnaire was completed in class during the first weeks of the fall semester.
Strategies inventory
To measure the strategies used by the students, we developed a five-point Likert scale questionnaire based on the 72 strategies from Fournier et al.’s (2019) framework. An initial version of the items was drafted and piloted with eight music students whom we asked to assess the clarity of the items, their relevance and completeness, and the time required to answer the questions. We did the same exercise with two aural skills teachers. From the feedback they provided, we added 11 additional items and made some required wording changes. Participants were asked to fill out the strategy inventory in the middle of the fall semester and then again in the middle of the winter semester.
Sight-singing achievement
To measure sight-singing achievement, we used the sight-singing grades from fall and winter aural skills college records.
Measures
Before performing the main analyses, we examined all the variables from the school records, the music experience questionnaire, and the strategy inventories to verify the accuracy of the
transcribed data, the missing values, and the fit between the distributions and the assumptions of the multivariate analyses (Tabachnick & Fidell, 2013). The distributions of some variables in the music experiences questionnaire were severely skewed and were recoded into dichotomous or ordinal variables (three categories) for subsequent analysis. Table 8 shows the descriptive statistics for the variables derived from the school records and the music experiences questionnaire. Cronbach alphas are provided for computed variables and scales. Academic achievement is a composite score of the high school GPA and national exams (α = .94). Informal musical experiences are an additive score of nine items assessed at 5, 11 and 16 years of age (α = 85). Music reading proficiency is an additive score from five-point scales at 5, 11 and 16 years of age (α = .66).
Missing values for variables in strategy inventories 1 and 2 were within an acceptable range (between 0 and 1.9% of non-response) and were replaced using regression estimations (Tabachnick & Fidell, 2013). Five cases had missing values on more than two variables and were deleted. Many of the 83 variables in the strategy inventories were not distributed normally. Strategies with higher means were negatively skewed, while strategies with the lowest means were positively skewed. The 83 items included in the strategy inventories were subjected to exploratory factor analyses, and then 11 scales were computed according to the main strategic dimensions that emerged. Factor analyses are part of the main analysis and further details will be provided in the next section.
Results
Factor analyses
In order to test the empirical validity of the framework, we performed exploratory factor analysis. Since the items covered a wide range of strategies related to sight-singing, we ran separate factor analyses for each main theoretical category: music reading mechanisms (23 items), sight-singing strategies (24 items), personal practice (20 items), and learning support (16 items). Given the high number of variables, we pooled the data from inventories 1 and 2 to raise statistical power. Before making this decision, we ensured that the factor analyses from both inventories yielded similar results (Tabachnick & Fidell, 2013). Using IBM SPSS REGRESSION and the Mahalanobis distance at p < 0.001 as a criterion, ten multivariate outliers were identified and deleted. After deletion, the reduced data set included 436 non-outlying cases. The Kayser-Meyer-
Table 8. Descriptive statistics Variables M (SD) n (%) General information Age 18.48 (2.15) Gender (males) 141 (57%) Profile (jazz) 145 (58%) Year First 114 (46%) Second 109 (44%) Third 24 (10%) Major instrument Guitar/bass 52 (21%) Piano / clavier 41 (17%) Voice 36 (15%) Woodwinds 36 (15%) Brass 31 (13%) Drum/percussions 26 (11%) Strings 25 (10%) Absolute pitch 18 (7%) Music experiences
Piano / clavier (≥ 1000 hours) 41 (16.6%)
Collective experiences < 1 year 61 (25%) 2–13.99 years 120 (49%) ≥ 14 years 66 (27%) Informal experiences (α = 85) 2.9 (0.7) Music listening (1-5) 4.3 (0.7) Family support (1-5) 3.8 (0.9) Concert attending (1-5) 3.1 (1.0) Learning by oneself (1-5) 2.9 (1.0) Playing by ear (1-5) 2.7 (1.1)
Sing with family (1-5) 2.7 (1.3)
Play in a band (1-5) 2.7 (1.2)
Improvising (1-5) 2.3 (0.9)
Composing (1-5) 1.8 (0.8)
Music achievement
Music reading proficiency (α = .67) 8.1 (2.4)
At 5 years old (1-5) 1.3 (0.7)
At 11 years old (1-5) 2.9 (1.3)
At placement test (1-5) 4.0 (1.1)
Theory placement test (1-4) 2.4 (0.9)
Academic achievement
Academic achievement (α =.94) 81.3 (5.9)
General point average (0-100) 82.6 (5.3)
Table 9. Factor structure of reading mechanisms strategies
Items Factors Cronbach alphas
1 2 3 4 Fall Winter Music analysis Concept-sound associations (50) .67 Harmonic progressions (15) .64 Music analysis (49) .55 Modulations (13) .40 Intervals (2) .39 Embellishing notes (17) .38 .31 Arpeggios (12) .36 .654 .745
Common melodic patterns
Melodic motives (20) .73
Repeated motives and sequences (14) .62
Rhythmic patterns (21) .59
Common melodic patterns (16) .46 .48
Scale patterns (19) .42
.732 .717
Pitch decoding
Previously sung notes (3) .59
Absolute pitch (7) -.46 -.32 Leap filling (4) .43 Reference notes (5) .38 Combine strategies (25) .31 .37 .574 .478 External support
Following other signers (40) .84
Adjusting with others (41) .60
Play on instrument (25) -.31 .40
.616 .656 Eigenvalues 4.24 2.25 1.85 1.39
Note: Factor loadings of the following items were below .30 and are not shown in the table: scale degrees (1), instrument imagery (8),
Table 10. Factor structure of sight-singing strategies
Items Factors Cronbach alphas
1 2 Fall Winter
Sight-singing performance
General music direction (27) .72
Music flow anticipation (37) .54
Being aware of expressive music elements (36) .52
Melodic contour (22) .51
Musical phrases (18) .48
Instinct (43) .47
Imagine the sound (42) .41
Similarities with familiar melodies (28) .31
.720 .715
Sight-singing preparation
Music score markings (62) .52
Analyze basic parameters (31) .50
Set up basic parameters (29) .48
Scan music score (30) .46
Sing repeatedly (57) .41
Work on trouble spots (32) .38
Break down complex task (61) .37
Look ahead (35) .32 .37
Choose proper vocal register (34) .35
Sing out loud (33) .32
.625 .706
Eigenvalues 3.54 2.44
Note: Factor loadings of the following items were below .30 and are not shown in the table: move forward (39), embody the pulse
Table 11. Factor structure of personnal practice strategies Items Factors Cronbach alphas 1 2 3 Fall Winter Practice management Schedule practices (67) .72 Structure practices (70) .71
Set clear goals (68) .67
Pursue goals (69) .66
Working hard (77) .54
Being prepared for exams (75) .53
Use every spare time to practice (71) .31
.779 .806
Internalization
Singing sequences without reference to notation (47) .55
Using gestures to embody expression (54) .50
Memorizing common music patterns (46) .50
Attentiveness to emotions evoked by music (52) .44
Whistling silently (56) .38
Singing quietly (55) .36
Recognize music concepts in music I listen to (45) .32
Play harmony with keyboard (44) .31
.620 .674
Rehearsal techniques
Complexify exercises (58) .96
Create variations in repetitions (59) .56
.735 .725
Eigenvalues 4.03 2.32 1.37
Note: Factor loadings of the following items were below .30 and are not shown in the table: sing in mind (53), use solmization system
Table 12. Factor structure of learning support strategies
Items Factors Cronbach alphas
1 2 Fall Winter
Affective strategies
Enjoy group singing (79) .76
Be comfortable with your voice (82) .55
Seek music satisfaction (78) .54
Remember past success (83) .50
Remember the value of sight-singing (80) .43
Positive self-talk (74) .42
Practice with a partner (81) .36
.719 .724
Metacognition
Awareness of the skills required (65) .66
Awareness of strengths and weakness (63) .62
Mistake analysis (64) .59
Strategies' awareness (66) .44
Mistakes detection (24) .35
Stay focus (72) .34
Trouble spots identification (60) .32
.674 .640
Eigenvalues 3.62 1.82
Note: Factor loadings of the following items were below .30 and are not shown in the table: imagine you are someone else (73) and
Table 13. Relationships between strategy use and individual characteristics
Reading mechanisms Sight-Singing
Music
analysis Common patterns decoding Pitch External support Preparation Performance Control
Year (sophomore) (Fisher’s F) 1.401 1.871 .706 4.133* .176 3.703*
Jazz profile (Fisher’s F) 4.267* .283 .514 1.652 1.260 2.235
Fall (Fisher’s F) 3.075 .675 .255 .002 .429 .038
General characteristics
Absolute pitch (Fisher’s F) 3.919* 1.903 110.388*** 33.712*** 1.752 1.121
Male (Fisher’s F) 1.405 2.163 3.724 1.093 31.315*** .145 Music experiences Piano (Fisher’s F) 9.204*** 8.428** 1.406 4.006* .556 5.716* Collective (Pearson’s r) .01 -.04 -.01 -.17** .07 .10 Informal (Pearson’s r) .06 .06 -.09 -.17** .11 .27*** School achievement Academic (Pearson’s r) .18** .06 .10 .02 .10 -.04 Theory (Pearson’s r) .18** .16* -.08 -.19** -.08 .05 Notation knowledge (Pearson’s r) .10 .03 -.15* -.26*** .13* .10
Personal practice Learning support
Practice management Internalization Rehearsal techniques Socio- affective Meta- cognitive Control
Year (sophomore) (Fisher’s F) 1.856 1.963 7.143** 1.368 .801
Jazz profile (Fisher’s F) 8.839** 24.828*** 4.973* 4.457* .319
Fall (Fisher’s F) .381 .023 4.792* .333 .621
General characteristics
Absolute pitch (Fisher’s F) 2.911 .953 .106 .090 9.903**
Male (Fisher’s F) 12.260** .876 .093 6.591* 6.417* Music experiences Piano (Fisher’s F) .971 4.966* 4.586* 5.651* 7.289** Collective (Pearson’s r) .01 .10 .14* .07 .11 Informal (Pearson’s r) .10 .22** .22** .26*** .23*** School achievement Academic (Pearson’s r) .07 -.02 -.15* .01 .13 Theory (Pearson’s r) -.02 .00 .16* -.07 .07 Notation knowledge (Pearson’s r) -.05 -.05 .13* -.01 .18**
Olkin value of the four main categories were between .750 and .771, exceeding the recommended value of .6 (Tabachnick & Fidell, 2013). Given the lack of empirical research in sight-singing strategies, we opted for principal axis factoring, which is the most appropriate extraction technique to study underlying structures and to take into account measurement errors (Tabachnick & Fidell, 2013). To guide our decision about the number of factors, we inspected the scree plots using the Cattell criteria and ran parallel analyses (O’Connor, 2000). A final decision was made that took into account the number of variables with high loadings and the interpretability of the factors. Orthogonal and oblique rotations were computed and compared. Since they led to similar solutions, we retained the orthogonal solution (Varimax) for ease of description.
Tables 9 through 12 show the factor structures of the four main groupings and the Cronbach alphas for the fall and winter strategy inventories. A total of eleven factors were extracted. Four factors relating to reading mechanisms were extracted, and they explained 42 % of the variance: music analysis (18%), common melodic patterns (10%), pitch decoding (8%), external support (6%). Two factors relating to sight-singing were extracted, and they explained 25% of the variance: sight-singing performance (15%) and sight-singing preparation (10%). Three factors relating to
personal practice were extracted, and they explained 39 % of the variance: practice management
(20%), internalization (12%), rehearsal techniques (7%). Two factors related to learning support were extracted, and they explained 34% of the variance: affective (23%) and metacognition (11%). Fourteen items had factor loadings below .30 and were discarded.
The Cronbach alphas, calculated for each scale (fall/winter), were as follows: music analysis ( α = .65/.75), common melodic patterns (α = .73/.72), pitch decoding (α = .57/.48), external support (α = .62/.66), sight-singing performance (α = .72/.72), sight-singing preparation (α = .63/.71), practice management (α = .78/.81), internalization (α = .62/.67), rehearsal techniques (" =.74/.73), socio-affective (α = .72/.72), metacognition (α = .67/.64). The factor analyses indicated that the empirical data was partly compatible with the pedagogical model developed by Fournier et al. (2019) and led to the following modifications.
Reading mechanisms
In the initial framework, three types of strategies were part of the reading mechanisms (pitch decoding, common melodic patterns, and validation). The findings reported here indicate that
strategies used to find the pitches (scale degrees, intervals, instrument imagery) were not related to other pitch decoding strategies. Here, pitch decoding strategies are simple “tricks” used to remember or to “compute” tone heights, such as “noticing previously sung notes” and “filling leaps with scales”. In the original framework, “pattern-building” strategies designated both small patterns and large musical structures. The factor analysis here shows a clear distinction between “common melodic patterns” and more theoretically-driven concepts. Finally, there was no