Psychology of Music
© The Author(s) 2017
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learning microanalysis to
study musicians’ practice
Gary E. McPherson1, Margaret S. Osborne1,
Paul Evans2 and Peter Miksza3
This article describes the development of a music practice microanalysis protocol that is based on the
three-phase model of self-regulated learning (i.e., Forethought, Performance, and Self-Reflection). Up
until now, most studies on music practice have tended to focus on behavioural aspects. The expanded
view presented here outlines a technique for mapping the types of behaviours (actions), cognition
(thoughts), and affect (feelings) that can help focus musicians’ practice. To explain the technique, we
describe the practice of two first year Bachelor of Music students studying at a prominent university
music school who are compared at three time points across one semester as they prepare an étude for
a performance exam. These case studies demonstrate two broadly contrasting self-regulated learning
profiles of how microanalysis can be used to cue students to think about what they are doing and
then reflect critically on the strategies they can use to improve their playing. As a technique,
microanalysis can inform educational interventions aimed at breaking the cycle of habits that typify
musical practice by encouraging musicians to become more behaviourally, metacognitively, and
motivationally involved in their own learning.
Microanalysis, self-regulated learning, musical development, practice, music learning, metacognition,
The profession of music is replete with well-worn quotes highlighting practice as an essential
ingredient for musical success. We have all heard the adage that “practice makes perfect” and
the expression “the quickest way to Carnegie Hall is to practice, practice, practice. . .” In our
1University of Melbourne, Australia
2University of New South Wales, Australia
3Indiana University, USA
Gary E. McPherson, Melbourne Conservatorium of Music, University of Melbourne, Melbourne, Victoria 3010,
731614POM0010.1177/0305735617731614Psychology of MusicMcPherson et al.
2 Psychology of Music 00(0)
view however, understanding how musicians reach the highest levels of musical achievement
involves understanding how they think about the task, themselves, and their performance, as
well as the amount of time they spend practising.
One of the challenges of teaching music performance is how to encourage developing musi-
cians to develop into autonomous learners (Hoyle & Dent, in press; McPherson & Zimmerman,
2011). To achieve this goal, musicians need to learn how to balance the effortful components
of practice with the broader self-regulatory skills required for them to systematically organise
their own thoughts, feelings, and actions as they seek their goals (Usher & Schunk, in press).
Learners possess the capacity to plan, set goals, and imagine future success, and this shapes
how they will subsequently behave as they pursue increasingly advanced levels of performance.
Accordingly, people can also self-react as they strive to achieve their goals, by recognising where
they are going wrong and adjusting tactics to achieve their goals. Due to the capacity for reflec-
tive self-consciousness, learners can examine their own actions, thoughts, and feelings before,
during, and after their attempts at learning something new or something that was already
learnt (Usher & Schunk, in press). Consequently, successful learners are those who have learnt
to harness these attributes and regulate their own learning.
While previous attempts to research practice efficiency have largely concentrated on behav-
ioural aspects (e.g., Chaffin, Imreh, & Crawford, 2002; Gruson, 1988; Jørgensen, 2002;
Lehmann & Ericsson, 1998), the expanded view we present here outlines a technique that
focuses on the types of behaviours (actions), cognition (thoughts), and affect (feelings) that
encourage musicians to become metacognitively, motivationally, and behaviourally active par-
ticipants in their own learning (McPherson & Zimmerman, 2011).
In this article, we describe a microanalysis protocol that can be used to cue students to
describe their actions and then reflect critically on the strategies they choose to improve their
playing in-situ. The protocol is based on an extensive body of literature across the past two dec-
ades in education, medicine, science, athletics, developmental psychology, and counselling
domains (Cleary, Callan, & Zimmerman, 2012; Cleary & Zimmerman, 2001) that draws on the
three phases of self-regulated learning: Forethought, Performance, and Self-Reflection. In the
sections that follow, we outline the self-regulated learning process and describe how microa-
nalysis techniques have been used in other domains to better understand learning.
Grounded in social-cognitive theory, self-regulated learning (SRL) emphasises the role of social
sources to reciprocally enhance or adversely impact how students perceive their help seeking
capabilities over time (Bandura, 1997). An important assumption of social-cognitive theory is
that people need to proactively control and manage the triadic reciprocal relationships between
person, behaviour, and environment through self-observation, self-judgement, and self-reac-
tion (Bandura & Schunk, 1981). Zimmerman (2011) and Zimmerman and Campillo (2003)
expanded the social-cognitive framework to include self-generated thoughts, feelings, and
behaviours that are planned and cyclically adapted based on performance feedback in order to
attain self-set goals (see Figure 1). A key principle is the cyclical nature of the dynamic pro-
cesses of forethought, performance, and self-reflection, which over multiple iterations of a task
provides a continuous line of goal directed, strategically defined, and emotionally satisfying
In the Forethought Phase, self-regulated musicians analyse the task they are about to com-
plete and draw on a range of self-motivational beliefs that will form the basis of their approaches
to rehearsing or performing music. In the Performance Phase, musicians would apply various
McPherson et al. 3
self-control and self-observational skills that aid focused attention and willpower on the music
that is being performed. In the Self-Reflective Phase, an assessment of how well the performance
went occurs when self-judgements and self-reactions are formed that then impact on the plan-
ning for further refinement in subsequent musical practice and performance.
Assessing self-regulated learning
Self-report questionnaires of SRL are the most widely used measures by researchers and educa-
tional practitioners (Cleary et al., 2012; Wolters & Won, in press). Such measures typically
define SRL as an aptitude (a relatively enduring attribute of a person which predicts future
behaviour) using self-report ratings of frequency of behaviour: never /always / most of the time /
typical of me (Winne & Perry, 2000). Research using this methodology to study self-regulated
practice behaviours in highly skilled musicians has shown that advanced musicians rely heav-
ily on self-regulatory skills when practising their instrument (Araújo, 2015). Unfortunately,
this methodology has insufficient corroboration with actual traces of individuals’ thoughts
and behaviours, being typically retrospective and decontextualised (Cleary et al., 2012).
Furthermore, most self-report questionnaires are not intended to assess SRL as a whole, but
rather, particular aspects of the SRL process, calling into question the validity of the conclu-
sions of many SRL studies (Wolters & Won, in press). Reliance on traditional survey measures
is therefore limited as an assessment tool for the contextualised and dynamic processes of the
three-phase model of SRL. Microanalytic techniques can provide a more valid and reliable
Figure 1. Phases and sub-processes of self-regulated learning. Reproduced with permission from
“Motivating Self-Regulated Problem Solvers” by B. J. Zimmerman and M. Campillo in The nature of problem
solving (p. 239), by J. E. Davidson & R. J. Sternberg (Eds.), 2003, New York, NY: Cambridge University
Press. Copyright 2003 by Cambridge University Press.
4 Psychology of Music 00(0)
assessment of SRL by documenting the contextually-bound behavioural, cognitive, and affec-
tive processes involved during real time music learning.
Microanalysis is an ecologically-sensitive SRL assessment technique which targets reciprocal tri-
adic interactions between person (namely, cognition, affect, behaviour) and environment factor s
in specific situations (Cleary & Callan, in press). A key feature of this technique is that it assesses
“authentic moment-to-moment behavioural interactions” which “minimise the response biases
and errors associated with retrospective self-reports about behaviour or interactions” (Cleary
etal., 2012, p. 4). Learning events are conceptualised as a temporal entity with a clear begin-
ning, middle, and end (i.e., an event), which is reflective of students’ efforts to self-regulate their
learning (Zimmerman, 2000). In this manner, the event is demarcated by a prior event and sub-
sequent event, capturing the sequential dependency of responses, and enabling causal infer-
ences about student’s self-regulatory changes in the practice context to be determined.
Importantly, true microanalytic protocols apply specifically to the practice session in which stu-
dents are about to engage, and not to longer-term performance goals (Cleary etal., 2012).
Microanalysis is now used across multiple educational settings (Cleary & Callan, in press). For
example, in an assessment of medical students’ clinical reasoning skills, undergraduates were
given a microanalytic assessment including open-ended questions targeting forethought and
performance phase sub-processes and requiring verbal responses, while reading a clinical case
and formulating the most probable diagnosis (Artino etal., 2014). Results indicated that most
students in the formative stages of learning diagnostic reasoning skills were aware of at least one
reasoning strategy. Notably, only about one-third of students set goals or developed plans that
incorporated strategies, and those who did achieved better course grade outcomes. This under-
scores the potential importance of forethought regulatory processes to facilitate student educa-
tional achievements (Artino et al., 2014). This methodology also enabled an assessment of
robust declines in students’ self-efficacy beliefs and regulatory processes following negative feed-
back about their performance on the diagnostic reasoning task (Cleary, Dong, & Artino, 2015).
The differential and construct validity of microanalytic protocols has been established
through research in science education (DiBenedetto & Zimmerman, 2010) and novice, non-
expert, and expert athletes (Cleary & Zimmerman, 2001; Kitsantas & Zimmerman, 2002).
These studies show that high achievers tend to exhibit more strategic thinking and regulation
as they perform specific tasks than do low achievers. Microanalysis has also shown that high
performing individuals tend to set more specific goals, approach tasks more strategically, and
make strategic attributions and adaptations following failure or poor performance on a task
(Cleary etal., 2012).
Self-regulated learning and microanalysis in music
Within music, studies on practice are still relatively scarce compared to other academic subjects
and sports. Much of this literature focuses on the behaviours of musicians and the efficacy of
differing techniques that are employed during practice sessions (Jørgensen & Hallam, 2016;
Lehmann & Jørgensen, 2012). Examples include studies that observe and then record the accu-
racy of skilled motor control learning through to studies that examine musicians’ ability to
document and reflect on individual practice sessions through questionnaires, interviews, and
learning journals of practice over time. Consequently, most findings on music practice are
derived from studies that have concentrated on what happens during practice, musicians’
McPherson et al. 5
reflections about their own practice, or the quality and quantity of practice and how this might
relate to differing levels of expertise (Miksza, 2011).
Researchers have adapted the social-cognitive perspective on musical skill development to
examine six psychological dimensions of SRL in music (McPherson & Zimmerman, 2011). Using
this framework, researchers have examined SRL in beginning, intermediate, and advanced stu-
dents (McPherson, Davidson, & Faulkner, 2012; McPherson, Miksza, & Evans, in press; McPherson
& Renwick, 2011; McPherson & Zimmerman, 2011; Miksza, 2015; Miksza, McPherson, Herceg,
& Meider, in press). A natural outgrowth of this work is to investigate SRL in music practice as a
cyclical process according to the three phases of SRL. Preliminary music evidence provides strong
support for this approach. For example, Miksza and Tan (2015) found that music students who
perceive themselves to be more self-regulated and efficient in their practice also tend to display
more determination to accomplish short- and long-term goals, experience flow while practising,
and exhibit thoughtfulness, metacognition, and self-awareness while practising. Furthermore,
augmenting traditional practice strategies (such as slowing and repetition) with SRL music prac-
tice instruction (such as goal-selection, planning, self-evaluation, and rest/reflection) signifi-
cantly improves performance achievement and facilitates nuanced music objectives (such as
dynamics, articulation, and interpretation) in tertiary music student practice (Miksza, 2015).
Despite growing evidence supporting the role of SRL for enhancing music practice and achieve-
ment, conclusions that can be drawn from existing research are limited by the predominant
reliance on a decontextualised self-report methodology which does not provide for direct obser-
vation and assessment of practice behaviours. Microanalysis offers a more detailed, context-
based understanding of the ways learners monitor and manage their prog ress towards learning
goals. The purpose of this study was to adapt the microanalysis technique to frame research
aimed at improving musicians’ self-regulated practice, and to understand the content and level
of detail this process might yield in instrumental music learners.
The task-specific nature of the microanalytic technique across performance domains and con-
texts means there will be considerable variability in its application. However, the three-phase
structure remains the same: forethought questions are administered before the task, perfor-
mance questions during the task, and self-reflection phase questions after the task (Cleary &
Callan, in press). An in-depth case study protocol was developed to adopt this three-phase
structure (McPherson, Osborne, Evans, & Miksza, 2015) to explore the behavioural, cognitive,
and emotional states that occur before, during, and after practice sessions. The case study
approach was used in order to gain a rich understanding of the content and potential range of
student attributes, so as to inform future developments of the protocol as a potential measure-
ment and intervention tool. It also enabled an examination of the extent to which musicians
optimise their SRL as they actively draw upon processes and techniques aimed at maximising
personal goals, motivation, positive emotions, and resilience (Butler & Cartier, in press).
Two students, “Helen” and “Suzie”, participated in the case study. These students were part of a
group of 33 first year pianists who auditioned and were admitted into a Bachelor of Music
6 Psychology of Music 00(0)
(Music Performance) programme at a large comprehensive university music school. One student
received the highest-ranking audition score, and the other the lowest-ranking audition score as
measured on a scale of A+ (“definitely suitable for Bachelor of Music/highly recommended for
scholarship”) to C+ (“suitable for BMus with reservations about performance quality”).
Helen, a 17-year old musician who had been learning piano for 13 years, achieved the high-
est audition ranking (A+) for entry into the course. During the study, she worked on two Chopin
études in the core first year music performance subject. At first, she was given Opus 10, No. 1,
which she was working on at the start of the study, but this was changed by the teacher during
week six of the semester because the construction of the first piece (octave jumps) required
movements that were judged to be incompatible with the physiology of her hands. The replace-
ment piece she worked on for the majority of this research study was Opus 10, No. 8. Her end
of semester 1 performance exam result was 92 out of 100, which represented an “outstand-
ing” result in approximately the top 5% of her cohort.
Suzie, who received a C+ for her audition, is an 18-year-old musician and had been learning
piano for nine years. She worked on Chopin étude Opus 25, No. 2. She continued working on
this piece across the semester and performed it at her examination. Her semester 1 performance
exam result was 56 out of 100, which represents a “pass” result that was in the bottom 5% of
The microanalysis protocol was administered at the beginning of the semester (2–3 weeks in),
in the middle, and towards the end of the semester just prior to the participants’ performance
examination. The three sessions occurred in a university practice room where the students nor-
mally practised. Prior to starting their practice, the researcher met with the participant in the
practice room to ask questions addressing the forethought phase of the SRL model. Both the
participant and researcher worked through a printed copy of the microanalysis protocol. This
enabled the researcher to check with participants to clarify their understanding of the ques-
tions posed and the researcher’s understanding of their answers.
The researcher then left the participant to practice alone and for as long as they wanted
while being recorded by a video camera. When they had finished their practice session, the
researcher returned to ask them to reflect on their practice using questions addressing the per-
formance and self-reflection phases of the SRL model. To address questions in the performance
phase, the first 30 minutes of the video recording of the étude practice was replayed to the
participant. Participants provided open-ended descriptions of their metacognitive monitoring
strategies while watching the video. These responses were noted by the researcher and subse-
quently coded into self-regulatory processes soon after the session. Approval for the study was
granted by the researchers’ university human research ethics committees.
Development of our music practice microanalysis technique adhered to the procedure for
ensuring a valid and reliable self-regulation protocol, as detailed by Cleary etal. (2012):
Step 1: Select a well-defined task. A music practice session.
Step 2: Identify target SRL processes. All processes in the three-phase SRL model shown in
Figure 1 were targeted.
McPherson et al. 7
Step 3: Develop SRL microanalytic questions. Based on self-regulation theory and previous music
research, we developed 18 questions linked to the task and context of the practice session.
Step 4: Link cyclical phase processes to task dimensions. Forethought phase questions were
administered prior to practice. Performance phase questions were posed during review of
the video of their practice. Self-reflection phase questions were administered immediately
Step 5: Scoring procedures. Likert scales, ranking items, and open-ended question formats
were used, and verbatim recordings were taken. Open-ended questions were independently
coded by two researchers, facilitated by a structured scoring rubric that included definitions
and examples for each category.
The 18-item guided interview protocol and self-report tool (McPherson etal., 2015) was
developed to capture all three phases and sub-processes of self-regulation as shown in Figure 1.
Expert consensus and prior research by four researchers across three institutions in Australia
and North America was used to develop a pool of potential questions, drawing from their exper-
tise in research and pedagogy using the SRL framework in music practice (see McPherson,
Miksza, & Evans, in press; McPherson, Nielsen, & Renwick, 2013; McPherson, Evans, Kupers,
& Renwick, 2016; Miksza, 2012, 2015; Evans, 2015; Evans & Bonneville-Roussy, 2016). This
item pool was tested in practice workshops with students and subsequently refined to improve
comprehension and minimise repetition.
Administration. At the commencement of the study, before the first practice session, participants
were asked to reflect on their ideal practice session, one in which they were improving techni-
cally and musically with two questions: “What do you do?” and “How do you structure it?” This
enabled us to gauge the participants’ standards for practice efficacy and quality.
Forethought. Before their practice sessions, participants were asked a number of questions to
understand the forethought phase. To understand their task analysis, participants were asked to
identify their technical, musical, and personal goals, and report on how fixed (vs. flexible) and
clear (vs. unclear) their plans were. Self-motivation beliefs were assessed by asking participants
to assess their self-efficacy (from 0 to 100% confidence) and the expectations they had for their
examination mark. Interest was reported on a scale of 0 to 100. Goal orientations were reported
as a ranking of various statements relating to mastery and performance goals.
Performance. The performance phase questions were asked as soon as the session ended. Prior
to assessing performance sub-processes, the researcher asked the participant to compare the
present session to an excellent practice session the participant had experienced in the past. Par-
ticipants commented on the way they structured their environment, the level and quality of
their focus, the strategies they were employing in the performance phase, and the degree to
which they would get help (e.g., from their teacher). The second and third practice sessions
asked whether and how help had been sought from the participant’s teacher or other resources
(e.g., peers, books, sound recordings). The researcher then played the video of the practice ses-
sion to the participant, asking about features of their practice behaviours. Metacognitive moni-
toring was assessed by asking the participant to identify moments where decisions led to
strategies, their consequences, and their thought processes while learning. The dimension of
self-recording was assessed by indicating the degree to which their session was planned and
how dynamic it was.
8 Psychology of Music 00(0)
Self-reflection. Participants were asked to evaluate whether their practice session was productive
and fulfilling of the goals they had set. The attributions of these judgements were assessed by ask-
ing the participants to elaborate on the extent to which their performance was a product of their
self or their environment, and the degree to which they were predictable or not. The participants
were asked how good they felt about their practice, and also the extent to which they agreed with
several affective descriptors (e.g., exhilarated, apathetic, empowered). They were also asked to
describe how optimistic they felt about their next practice session and how well it would go.
General approach to practice
The responses to the opening question “Describe your ideal practice session—one where you’re
improving technically and musically” immediately differentiated the depth of SRL between the
two participants. Helen’s approach involved “specific techniques within the pieces” and how to
play them in a way that “minimises tension and fatigue” after starting with scales and arpeg-
gios. She was mindful of addressing musical elements of expression and character of the music,
and the intentions of the composer. In this respect, Helen could be identified as a proactive
learner, with an emphasis on higher-order contextual goals with the aim of achieving an indi-
vidualised interpretation and mental model of the score, within which she identified and
employed specific strategies and short-term goals in order to frame her progress. In contrast,
Suzie identified no overarching specific goals, and her strategy preference was to work on sec-
tions she “has trouble with”, focusing “mainly on the difficult parts”. Her comments indicated
reactive, habitual strategy use, responding to her perceived difficulty of parts of the piece.
Both participants described poorly self-regulated and reactive learning styles with vague goals.
Helen made comments such as “I want to work on technique—the stretch between the fingers”
(Time 1), “Refining specific sections that might not be as good. Working on contrasting dynam-
ics” (Time 3). In contrast, Suzie was less specific: “Wanting to get étude hands together” (Time
1), and “Making it musical” (Time 3). Thus, rather than articulating goals, both participants
referred to specific strategies without reference to a goal related to the practice session. Strategic
Planning differentiated the learners only in the middle of the semester, where Helen rated sub-
stantially improved strategic planning, while Suzie attained the same level of strategic planning
but only at Time 3.
For Self-Efficacy, Helen demonstrated a reasonable awareness of the expected standard of
mastery of the étude that increased across the three practice sessions: 20% at Time 1, 50% at
Time 2, and 80% at Time 3. Her reasons also differentiated across the three practice sessions
from Time 1 (“Haven’t had it very long”) to Time 2 (“Working on technique. Doesn’t have to be
performance standard right now”) and immediately before her examination at Time 3 where
she was focused on a desired performance standard (“Fixing up little errors and polishing the
whole performance overall”). Although Suzie’s estimates of mastery also increased from the
beginning to the end of the semester (30%–40%–70%), she provided less sophisticated reason-
ing as to why she expected to have achieved these levels of mastery across time: at Time 1, “Just
repetition, nothing in particular”; at Time 2, “I don’t know what ‘master’ means. Just practice
it. Kind of trying to get it more musical, I guess”; and at Time 3, “Playing it through. Working
on harder sections”.
McPherson et al. 9
Outcome Expectancies clearly elicited contrasting responses. Helen consistently aimed for a
very high score, with the minimum cut-off for the highest-grade category being “just” good
enough. This motivated her to invest a high degree of effort to achieve her desired high-perfor-
mance outcome. In contrast, Suzie’s estimates of her grade were consistently lower (ranging
between 54 and 67 out of 100). She based the estimate of her grade on her teacher’s estima-
tion: “My teacher said that’s where I’m at, the standard, at the moment.” Across the semester,
we observed consistent evidence of low to moderate performance expectations for her exam,
and poor confidence that she could master the étude. For example, her expected mark for the
exam by Time 3 is 67/100, with the explanation “Don’t know—it’s a pretty high expectation. I
kinda know my pieces I guess” (Time 3).
Helen rated considerably higher intrinsic motivation to learn and practice the piece in order
to achieve greater skill on her instrument (90–100) than Suzie (40–70). But they provided
identical rankings on the four performance–mastery/approach–avoid goal orientation state-
ments. Both students reported their main goal at each practice session as mastery–approach (to
achieve their personal best). However, probing for elaborations as to why both participants
responded in this way revealed notable differences, particularly at Time 1 and Time 3. We see
Helen’s desire to achieve her personal best related to an understanding of herself as a consist-
ently improving musician: “As a musician, the most important thing is playing, practising, and
achieving to the best that I can. The personal sense of achievement and working hard. Because
I might not be ‘the best’, but as long as I keep improving and developing” (Time 1) and “I need
to play to my personal best and that is achieved through practice” (Time 3), and contrasting
with the performance approach: “This whole thing is my personal achievement, it’s not like I’m
trying to beat other people.”
Although Suzie restates that same desire for mastery as Helen in her Goal Orientation elabo-
rations, the simplicity of her response indicated that she seemed to lack an understanding of
how she could actually achieve her personal best, for example, “That’s what I’m here to do, to
achieve. That’s it” (Time 1), and “I want to achieve my best” (Times 2 and 3). The absence of
behavioural and cognitive strategies indicates a less motivated and aware orientation.
There were also consistent differences at all three time points in Valuing practice and per-
ceived locus of causality of practice goals. Helen’s goals were fully internalised and self-deter-
mined, as she clearly articulated the importance of practice as a valued means for achieving
performance excellence: “Because the only way I can keep improving is through practice.
Therefore, it’s something I value” (Time 1). Although Suzie also noted the importance of prac-
tice, her self-endorsement of practice goals as a means to feel better about herself at all three
time points was not related to incremental causal improvements in order to achieve better per-
formance outcomes. Instead they were vague and non-specific: “That’s what I’m here to do, to
achieve” (Time 1); “I know I’ve practised. It means a sense of achievement” (Time 2); and
“Because it’s coming close to exam Time, I feel the need to practice more” (Time 3).
Helen’s practice sessions typically lasted for two hours, and she purposefully chose to practice
on the grand piano (closely approximating the performance exam instrument) in the formal
dining room of her university residential college. This was a large, quiet, aesthetically pleasing
room (approximately 20 m × 10 m) with wooden floorboards providing an acoustically vibrant
environment to practice in. The choice of a grand piano in a large room is important, given
Helen’s use of the performance phase dimension of Environmental Structuring to enhance the
quality of her practice. In contrast, Suzie’s structured her practice environment by choosing a
10 Psychology of Music 00(0)
piano in a small (3 m × 2 m) carpeted room in one of the music department practice facilities
that housed an upright piano, stool, one or two sitting chairs, a music stand, and a mirror.
These rooms are available on a first-come, first-served basis to students. Suzie aimed to arrive
early to secure a room but was sometimes unsuccessful.
The Self-Control sub-phase also highlighted differences between the students: Helen demon-
strated more interest, focus, and sustained concentration across the three time points than
Suzie. Helen’s self-instructions across the three time points were “targeted—very clear, more
fixed than expected”, stimulating, mindful, focused, attentive, with consistent and often deep
attentional focus. In contrast, Suzie reported the sessions to be tedious, frustrating, and pro-
vided largely surface-level depth of attention comments that oscillated between mindful focus
and lack of focus.
The Task Strategies of both participants showed a reactive, indiscriminate, SRL process with
an emphasis on teacher-directed strategies with one exception, the use of whole-part-whole
chaining strategy which was not teacher-directed. At Time 2 we saw a clear connection between
the Forethought and Performance phases for Helen. She applied strategies that were consistent
with her goal for the practice session which was to learn a new étude. “It’s a new étude, so I’m
playing it slow. Trying to improve technique. Really slow practice, trying not to lift the fingers
too high.” Her Task Strategies comments included “Trying to overcome the trouble with my
hands getting tired. Trying to minimise movement in my fingers. Trying to keep fingers as close
to the keys as possible—teacher observed I was attacking keys from too high.” In contrast, at
Time 2, Suzie’s comment indicated an external regulatory style: “Aim is achieving contrast
between left hand slurring and right hand more staccato-like. That’s what makes the piece
interesting, apparently.” Helen also rated consistently higher belief in the effectiveness of the
techniques she was applying than Suzie.
There are notable differences in the degree of Help Seeking across students. Both actively
sought advice from their teacher and used YouTube, but only Helen consulted CD recordings,
which she had done for the étude prior to Time 1. Helen had listened to “a lot” of different
recordings, compared to “a few” for Suzie. At Time 2, Helen shows a more proactive and indi-
vidualised approach, while Suzie benefitted from advice she was given within her teacher- and
In order to determine whether this method could delineate more or less sophisticated meta-
cognitive strategies, we coded their descriptions into three types of responses: deliberate
(planned, specific, challenging, contextual), routine (unplanned, habitual, non-contextualised)
or off-task (non-productive) events. The percentage frequency of each type of statement out of
the total number of events (descriptions) is presented in Table 1.
The participants’ Metacognitive Monitoring displayed two contrasting profiles. Helen’s was
planned: “Start étude with right hand only because of trouble with a specific section.” (Time 1);
on-task and challenging: “Varying tempo and rhythm to get a different feel. Helps me think more,
instead of mindless repetition” (Time 1); solution-focused: “Now this is the section I noticed
when I was playing it fast that wasn’t good enough. So I’m repeating the specific bars, trying to
make it clearer.” (Time 2); “Running through sections until hitting a snag, then slower and
repeated. I’m stopping at the parts that have er rors, to fix them. Fixing them by repeating them,
or hands separately” (Time 3); and contextualised: “Playing the whole thing really fast after I’ve
worked through a specific section. This helps me see how it fits together and what else needs
work. Do this every practice” (Time 2).
Suzie displayed an almost inverse profile of Metacognitive Monitoring. Hers was unplanned:
“Étude start, from the beginning, because I didn’t know what I was going to do” (Time 2); habit-
ual with limited problem solving in response to problems: “ Stopped, then right hand. Repeating right
McPherson et al. 11
hand. It’s hard to remember why I was doing this” (Time 2); and non-specific: “I did the chords,
then grouped a section of it” (Time 1); and off-task: “Annoyed by squeaky pedal” (Time 1).
All items in the self-reflection phase captured differences in SRL that discriminated across time
and between the two participants. Helen’s Self-Evaluation ratings were consistently higher for
productivity and goal fulfilment (7–10 out of 10) than Suzie (4–5 out of 10). Helen, the high
achieving student, rated the most important reason for practice effectiveness as internal-stable
factors of work ethic and effort. In contrast, Suzie’s external-stable reason (“Help from teacher”)
suggests that she felt minimal control over her performance outcomes in music.
Affective responses varied between both learners. At Time 1, Helen reported that she had
met her goals by following her planned structure for the session. Although vague, they never-
theless facilitated focus and resulted in positive feelings about her approach and practice accom-
plishments. Another notable feature distinguishing Helen and Suzie, which corresponds to the
eventual performance result outcome, is that Helen’s affective response to all three practice
sessions was positive (e.g., “I felt really good about this practice. I did the things I planned to
do”), which she related to her achievement of practice goals, strategies, and progressive mas-
tery of the piece.
Suzie’s Affect reactions were negative (e.g., “I felt really bad about it. I didn’t get as far as I
thought I would”). At Time 1 there is no clear articulation of goals, therefore impeding bench-
marking of progress to strategy, and encouraging attribution to internal, stable causes.
Importantly, at Times 2 and 3, Suzie reports both positive and negative affect for the same vague
approach, that is, how she “normally” practices; e.g., Time 2 “I feel good about it . . . It’s how I
normally practice, just doing what the teacher says, hopefully”. This suggests that Suzie not
only has weak goal setting and strategic planning skills, but that her habitual and externalised
strategies (especially at Time 2) left her disempowered to achieve her potential and susceptible
to seemingly random positive or negative affective responses to her practice efforts.
Helen’s responses consistently linked motivation with mastery goals. She linked incremental
progress at each time point to the overall performance mastery goal she had set to achieve prior
to the end-of-semester exam. Given the characteristics of the responses in respect of the level of
achievement of the two respondents, it would seem that these self-reflection questions in the
microanalysis protocol are particularly indicative of eventual performance success (or lack
Suzie, on the other hand, felt “bad” about her progress in the first session because it was inef-
fective. This prompted her to feel motivated and enthusiastic about the following session, with
Table 1. Percentage of deliberate, routine, and off-task metacognitive monitoring events across three
Deliberate Routine Off-task Deliberate Routine Off-task
Time 1 60 40 0 17 78 6
Time 2 93 7 0 44 56 0
Time 3 88 12 0 16 84 0
Note. Percentage refers to the number of descriptors in each category out of the total number of descriptors, rounded
to nearest whole number.
12 Psychology of Music 00(0)
a resolve to work in a more methodical manner and consolidating progress section-by-section
rather than repeating the haphazard approach she adopted in her first session. Yet, following
this more effective session, she felt “helpless” and poorly motivated about what she might do in
the future. She seemed to be broadly optimistic: “Next session will be slightly different” (Times
1, 2 and 3), but unaware of how she could improve her practice approach in a way that would
lead to a constructive difference: “I don’t know what to do next” (Time 2).
In this study, we developed a microanalysis protocol that aimed to effectively cue students to
describe the SRL processes embedded within their music practice. The protocol provided broad
coverage of the forethought, performance, and self-reflection phases of SRL. The participants’
responses provide initial evidence that first year university music students are receptive to the
questions and broader constructs covered by this technique. While we did not expect vast differ-
ences in all facets of self-regulated learning between only two students, the case studies demon-
strated two broadly contrasting SRL profiles of behaviour, cognition, and affect. Helen was a
proactive learner who tended to discuss higher-order contextual strategies with the aim of
achieving an individualized interpretation and mental model of the score. Suzie indicated less
self-regulated goal setting, and reactive and habitual strategy use.
This study presents a notable divergence from existing SRL literature. Research in music to
date is most often conducted using large scale surveys (Araújo, 2015; McPherson & McCor mick,
1999, 2000; Miksza, 2012; Nielsen, 2004). However, researchers in music have yet to apply
specific microanalysis techniques, shown to be successful in other domains (Cleary, Callan, &
Zimmerman, 2012; Cleary & Callan, in press) to understand students’ SRL strategies in the
music context. Our focus has been on methodological development reflecting the breadth of
SRL strategies and within-subject, moment-to-moment fluctuations in practice quality that
determine the intensity and quality of practice within and across time. Our working assump-
tion was that no single factor would be able to define, or fully explain, each individual student
outcome. Rather, we expected that SRL would be highly individualistic and involve a choreog-
raphy of learning habits, strategies, and abilities that have been developed over the learner’s
entire education. Consequently, we sought to develop a tool that could be used to help musi-
cians become more aware of their own practice efficiency, and an aid that could be used by
teachers who wished to adopt the technique to improve their student’s learning.
Implications for future research
In this study, we have shown that microanalysis techniques built on the three phases of SRL
can be adapted to study music practice. Now that we have a working protocol for monitoring
and cueing practice strategies (McPherson et al., 2015), our continuing work will include
intervention studies aimed at helping developing musicians become more behaviourally, meta-
cognitively, and emotionally involved in their learning. We have repurposed a microanalytic
protocol from an educational context to music practice using the types of cues that can allow
students to scaffold to higher levels of practice efficacy. Readers are encouraged to modify and
adapt the protocol for their own particular research or teaching situation. Thus, our protocol
should serve as a guiding framework rather than a fixed set of questions.
The present research used a case study trial approach to applying a particular microanalytic
protocol (McPherson etal., 2015). This methodology had the advantages of providing deep
illustrative information about the nature of each participant’s practice during the three phases.
McPherson et al. 13
However, it was not a test of effectiveness of the protocol. To this end, future research may
adopt techniques to examine effectiveness. This could consist of using the present methodology
but applying a longitudinal perspective to look at changes in practice habits over time, or larger-
scale quantitative approaches where microanalytic teaching and practice techniques are ana-
lysed in relation to student performance examination results or other indices of music
Applications of the microanalytic technique for teaching and learning
Self-regulation is not a single construct, and conceptions of self-regulation must be framed as a
cyclical rather than static process. The technique developed in this study offers researchers the
advantage of mapping out developmental paths across time in terms of cognitions, behaviour,
and affect. It also offers teachers the opportunity to gain more clarity on the particular parts of
a musician’s learning profile that might need to be optimised in order to improve performance.
We observed pianists who typically relied on habitual approaches every time they sat down
to practice, and who rarely adopted the types of strategies that can optimise learning. For exam-
ple, the students with whom we worked showed little awareness of key attributes within the
forethought and self-reflection phases of SRL. Optimising their practice might therefore involve
devising strategies for encouraging them to set more specific goals and identify ways of plan-
ning and motivating themselves. It would also be important for them to implement richer self-
reflective assessments that could serve as a stimulus for more efficient and goal directed practice
Our future work will attempt to customise the protocol devised for this study so that individual
musicians can focus on specific aspects of the self-regulatory process in which they most need to
change. We will attempt to understand the degree to which the use of the three phases can help
shape, maximise and optimise individual practice sessions and whether students are able to
increase their capacities to make even more sophisticated judgements about the goals, motivation
orientations, and adaptive self-evaluations that allow their practice to be more effective.
In conclusion, our aim in this study was to develop a global self-regulation measure that
could form the basis of attempts aimed at optimising music practice. The resultant microanaly-
sis protocol is based on the three phases of the cyclical SRL process involving forethought, per-
formance, and reflection. In proposing this approach, we are very much aware that changing
habits into productive optimised practice strategies will only occur when students and their
teachers start to think differently about the nature of music practice. We therefore realise that
what we are proposing will challenge the beliefs of musicians more generally if the techniques
suggested by the self-regulation literature are to be fully implemented by individual students,
teachers, and within music schools. It is important to understand also that our proposal is not
to define a single invariant microanalysis technique, but to provide a framework that outlines
the types of processes and abilities that encompass efficient self-regulation in music. This tech-
nique, therefore, should be adapted and modified to fit particular learning contexts, depending
on the abilities of the music learner (Wolters & Won, in press).
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or
publication of this article: This research was funded by the Australian Government through an Australian
Research Council (grant number DP150103330). This study is part of a larger study funded by an
Australian Research Council Discovery Project (DP-150103330) held by the first, third, and fourth
14 Psychology of Music 00(0)
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