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eISSN 2317-6377
Exploring engagement and flow experiences in collective
music practices of amateurs, students and professional
musicians
Explorando o engajamento e as experiências de fluxo nas práticas
musicais coletivas de músicos amadores, estudantes de música e
músicos profissionais
Anderson Toni1
andersontoni12@gmail.com
Rosane Cardoso de Araújo2
1Universidade Federal de Mato Grosso, Departamento de Artes, Cuiabá, Mato Grosso, Brasil
2Universidade Federal do Paraná, Departamento de Artes, Curitiba, Paraná, Brasil
SCIENTIFIC ARTICLE
Section Editor: Fernando Chaib
Layout Editor: Fernando Chaib
License: "CC by 4.0"
Submitted date: 27 jul 2024
Final approval date: 14 sep 2024
Publication date: 01 oct 2024
DOI: https://doi.org/10.35699/2317-6377.2024.53731
ABSTRACT: The purpose of this research was to explore the engagement and flow experiences in collective music
practices of amateurs, students, and professional musicians. Based on the first phase of a sequential explanatory
mixed methods research design, this article presents the results obtained from an online survey with 102 participants
from diverse collective music practices. The results obtained were analyzed using both descriptive and inferential
statistics. Some statistically significant differences were observed in the interaction between participant groups
(amateurs, students, and professionals) and dimensions of engagement (behavioral, cognitive, and emotional), as
reported in the results and discussed in relation to the literature. In summary, we were able to explore and discuss
some aspects of engagement, motivation, and flow experience based on the participants’ responses regarding their
collective music practices.
KEYWORDS: Engagement; Flow; Motivation; Collective music practices; Music ensemble.
RESUMO: O objetivo desta pesquisa foi explorar o engajamento e as experiências de fluxo em práticas musicais
coletivas de músicos amadores, estudantes de música e músicos profissionais. Com base na primeira fase de uma
pesquisa de métodos mistos sequencial explanatória, este artigo apresenta os resultados obtidos a partir de um
survey on-line com 102 participantes de diversas práticas musicais coletivas. Os resultados obtidos foram
analisados utilizando tanto estatísticas descritivas quanto inferenciais. Algumas diferenças estatisticamente
significativas foram observadas na interação entre os grupos de participantes (amadores, estudantes e profissionais)
e as dimensões de engajamento (comportamental, cognitivo e emocional), conforme relatado nos resultados e
discutido a partir da literatura. Em resumo, foi possível explorar e discutir alguns aspectos do engajamento, da
motivação e da experiência de fluxo com base nas respostas dos participantes sobre suas práticas musicais
coletivas.
PALAVRAS-CHAVE: Engajamento; Fluxo; Motivação; Práticas musicais coletivas; Grupo musical.
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Toni, Anderson; Araújo, Rosane Cardoso de.
“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
1. Introduction1
Numerous studies discuss the importance of understanding student engagement and its
motivations and indicators. In this sense, engagement is understood as active participation in an
activity that is determined by the quality of behavioral and psychological (cognitive and emotional)
dimensions of an individual’s experience when performing an action (e.g., Fredricks et al. 2004;
Rose-Krasnor 2009; O’Neill 2012; Reeve 2018; Reschly and Christenson 2022). The literature
commonly presents three dimensions of engagement and its indicators: (1) behavioral
engagement (e.g., frequency, intensity, duration, and actions performed in an activity); (2)
cognitive engagement (e.g., seeking strategies, thinking and reflecting on activities, and
preference for challenge); and (3) emotional engagement (e.g., interest, enjoyment, and sense of
belonging) (Christenson et al. 2012). Reschly and Christenson (2012) argue that one of the most
prominent discussions revolves around the dynamic relationship between motivation and
engagement: while the former concerns what moves an individual towards an action, the latter
concerns active participation. When addressing the debate on the relationship between
motivation and engagement, Bempechat and Shernoff (2012) highlight that deep engagement
can be related to flow experiences since it involves elements such as concentration, interest, and
enjoyment. This approach enables the understanding of motivational pathways that lead to
engagement, which can be qualified as deep engagement when characterized as a flow
experience (Csikszentmihalyi and Hermanson 1995; Shernoff 2013).
The flow experience can be understood as a state in which individuals are deeply engaged in an
activity and experience a high level of concentration and enjoyment in the task. Csikszentmihalyi
(1990) identifies nine characteristics of the flow experience: challenge-skill balance, action-
awareness merging, clear goals, feedback, concentration on the task, a sense of control, loss of
self-consciousness, transformation of time, and autotelic experience. Csikszentmihalyi (1990)
highlights that one of the most commonly reported activities in flow experiences is socialization,
and music is closely intertwined with our social connections with others. In this regard, recent
studies indicate that collective flow can be a shared experience among individuals within a group
(Walker 2010; Salanova et al. 2014; Sawyer 2017; Pels et al. 2018). Tay and colleagues (2021)
assert that studying flow based on individual experiences can serve as a foundation for
understanding collective flow. However, the authors emphasize that collective flow is not simply
the sum of individual parts, and it emerges from a collective sharing dynamic that needs to be
considered in research.
In this study, musical engagement is understood as the active participation in a musical activity
that is determined by the quality of behavioral and psychological (cognitive and emotional)
dimensions of an individual’s experience when performing a musical action. There is a recent
literature investigating the role and presence of musical engagement in different contexts of
music making, listening, teaching, and/or learning (e.g., Lamont 2012; O’Neill and Senyshyn 2012;
Beineke 2015; Richmond et al. 2016; Joseph and Southcott 2017; Chen and O’Neill 2020; Toni
2023, 2024; Toni and Araújo, 2023). Furthermore, researchers have been adopting the flow theory
1This work was financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
(CAPES), Fundação Araúcária and Conselho Nacional de Desenvolvimento Científico e
Tecnológico (CNPq).
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Toni, Anderson; Araújo, Rosane Cardoso de.
“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
to discuss elements related to the engagement of students and musicians in their musical
practices (e.g., Custodero 2005; Lamont 2012; O’Neill 2012, 2016; Croom 2015). Elliott and
Silverman (2015) state that enjoyment can emerge from active musical engagement in musicing
and listening, actions that can be closely related to the flow experience, both at an individual and
collective level. Therefore, collective flow has also been a relevant approach, considering
engagement in studies on collective music practices (e.g., Hart and Di Blasi 2015; Gaggioli et al.
2017; Sawyer 2017).
Musical activities are immersed in a collective social dynamic negotiated by individuals’
engagements in their actions (Small 1998; Mithen 2005; Olsson 2007; O’Neill 2012; Elliott and
Silverman 2015; Savage et al. 2021). Furthermore, engagement and flow are subjective
experiences that can occur in collective music practices and are reported by ensemble musicians
(Hart and Di Blasi 2015; Elliott and Silverman 2015; Gaggioli et al. 2017; Sawyer 2017). The
current study addresses the self-reported musical engagement and flow experiences of
ensemble musicians in their practices. In this sense, the purpose of this research was to explore
the engagement and flow experiences in collective music practices of amateurs, students, and
professional musicians.
2. Method
A sequential explanatory mixed methods design was employed in the research project
associated with this article2(Wise 2014; Creswell and Plano Clark 2017). In the first phase of a
sequential explanatory mixed methods project, the primary goal is to explore the research aims
using quantitative data. Accordingly, this article employed a survey as the method for the initial
phase of the study, given its common usage in describing characteristics present among a group
of individuals (Cohen et al. 2007).
2.1. Participants and contexts
In this research, a non-probabilistic sampling method was employed, intentionally selecting
individuals from three distinct participant groups (Cohen et al. 2007). The three intentionally
selected participant groups consisted of: (1) amateur musicians, those who participate in music
ensembles without pursuing music as a profession or holding a degree in music; (2) music
students, those who participate in music ensembles and are currently pursuing an undergraduate
degree in music; and (3) professional musicians, those who participate in music ensembles and
rely on music as their primary source of income. The selection of these participant groups was
based on the opportunity to understand how individuals from diverse music backgrounds
perceive their collective music practices. Furthermore, the contexts of collective music practice
were voluntarily chosen by the participants, which can be relevant for investigating engagement
in an activity. This is because the reports can better express indicators that assist in assessing
and characterizing engagement in voluntary activities (Shernoff 2013; Ramey et al. 2015;
Fredricks 2011; Ryan et al. 2019). However, it was not possible to control for a variable where
2This research was approved by the Ethics Committee of the Federal University of Paraná (Brazil)
under the code CAAE 46763121.4.0000.0102.
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Toni, Anderson; Araújo, Rosane Cardoso de.
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only highly engaged individuals responded to the questionnaire in such voluntarily chosen
contexts.
The research involved 102 participants (34 in each participant group). Regarding the participants’
gender, 67 described themselves as cisgender men, 34 as cisgender women, and one as other
gender. They were between 18 and 59 years old (M= 29.5. SD = 10.7).3In terms of educational
background, 46 participants completed high school, 29 completed undergraduate studies, and
27 pursued postgraduate studies. Nineteen participants reported not having any musical
education, while 83 participants reported having a music education background that included
general music and instrumental classes, undergraduate music degrees, and/or postgraduate
music degrees.
Participants’ collective music practices varied as follows: 44 in bands, 21 in orchestras, 18 in
choirs, nine in marching bands, five in percussion ensembles, and five in other types of music
groups. Collective music practices with up to five individuals were predominant (37 participants)
in this research, but there were also reports of participation in collective music practices with
more than 20 individuals (28 participants), five to 20 individuals (19 participants), and over 50
individuals (18 participants). The majority of participants reported that their collective music
practices were located in the Southern region of Brazil. Additionally, there were no participants
from the Northern region of Brazil and some participants reported remote music practices. The
reasons for participating in the collective music practice were categorized into six groups:
personal identification with the practice, interest in learning music, remuneration or work,
professional development, leisure, and/or social interaction.
2.2. Measures and materials
An online questionnaire was sent to the participants. The first section of the questionnaire
comprised an introduction to the research and gathered information about participant
characteristics and their collective music practices. The second section of the questionnaire
comprised a list of statements concerning behavioral, cognitive, and emotional engagement, as
well as the characteristics of flow experience (Table 2). Participants were asked to rate their
agreement with each statement using a five-point scale, ranging from 0 (strongly disagree) to 4
(strongly agree). The authors developed this list of statements in Brazilian Portuguese,
considering the existing construct (engagement and flow) operationalization in the consulted
literature (e.g., Busseri and Rose-Krasnor 2008; Shernoff 2013; Ramey et al. 2015; Richmond et
al. 2016; O’Neill and Senyshyn 2012; Fredricks, Parr et al. 2019; Chen and O’Neill 2020).
Considering the diverse operationalization of engagement across studies, the validation of
construct coherence with existing literature holds significance when defining and enumerating
items to formulate a data collection instrument that aligns with the construct delineated in
scholarly discourse and the theoretical framework under consideration (Cohen et al. 2007; Betts
2012). In this sense, the overlaps between flow and engagement were considered in the research,
and flow theory was considered as a theoretical framework that enables the understanding of
3Some additional information about the participants’ ages may be relevant. Amateur musicians,
they were between 18 and 50 years old (M = 25.8. SD = 8.4). Music students, they were between
18 and 42 years old (M = 24. SD = 5.8). Professional musicians, they were between 23 and 59
years old (M = 38.8. SD = 10.7).
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Toni, Anderson; Araújo, Rosane Cardoso de.
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motivational pathways that lead to engagement, which can be qualified as deep engagement
when characterized as a flow experience (e.g., Csikszentmihalyi and Hermanson 1995; Shernoff
and Csikszentmihalyi 2009; Steele and Fullagar 2009; Bempechat and Shernoff 2012; Shernoff
2013). Cronbach’s alpha indicated a good internal consistency of the list in the pilot study (α =
0.71) and in the total sample of participants (α = 0.83).4
2.3. Procedures
Given that this is a sequential explanatory mixed methods study with an exploratory first phase,
the participant recruitment procedures occurred through purposive (participant groups) and
voluntary non-probabilistic sampling methods (Cohen et al. 2007; Creswell and Plano Clark 2017).
The questionnaire was sent to the participants through social media platforms and e-mail.
Participants were contacted with information about the research and the Informed Consent Form.
They were also provided with a link to access the online questionnaire and were given the
opportunity to ask any questions related to their participation in the research. Participants were
invited to take part in the research while ensuring the security of their response information and
the voluntary nature of their participation in the study. Contact information for research
participants was accessed from publicly available sources, such as music ensemble websites
(e.g., choirs and orchestras), social media platforms, and e-mail lists. Throughout the data
collection process, the obtained responses were continuously monitored in order to balance the
number of individuals in each participant group.5
2.3. Analysis
The questions concerning the characterization of participants and the contexts of collective
music practice (presented in the participants and contexts section) were analyzed using
descriptive statistics and a categorical content analysis procedure (Bardin 2016). The data
collected through the list of statements related to engagement and flow experience were
analyzed using descriptive and inferential statistics (presented in the results section). The
Kolmogorov-Smirnov and Shapiro-Wilk tests indicated that the data from the list did not follow
parametric distributions. Similarly, the Levene’s test indicated that there was no homogeneity of
variances in some of the data distributions. Consequently, Friedman and Kruskal-Wallis tests
were conducted to examine the main effect on the participants’ responses, considering
dimensions of engagement and participant groups. Pairwise comparisons were also conducted
to identify statistically significant differences. Statistical differences were considered significant
when the calculated pvalues were below 0.05. Bonferroni correction was applied in multiple
comparisons and reported in the results.
4Cronbach’s alpha was also calculated for each dimension of engagement in the total sample of
participants (N = 102): behavioral engagement (α = 0.61), cognitive engagement (α = 0.52), and
emotional engagement (α = 0.80).
5Upon reaching a total of 34 participants for music students and professional musicians, it was
necessary to exclude three participants from the amateur musician group in order to maintain a
balance in the size of the three groups. The exclusion criterion was based on participants’ self-
reports not identifying themselves as amateur musicians. The same verification was carried out in
the self-reports of music students and professional musicians.
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Toni, Anderson; Araújo, Rosane Cardoso de.
“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
3. Results
The results section presents descriptive and inferential statistics derived from the list of
statements (engagement and flow), organized as follows: (1) general comparisons between
dimensions of engagement and participant groups; and (2) comparisons between each statement
and participant groups.
3.1. General comparisons between dimensions of engagement and participant
groups
Table 1 presents the descriptive statistics of engagement distributed in general mean values and
separated into behavioral, cognitive, and emotional dimensions for all participants, amateur
musicians, music students, and professional musicians.
Tab. 1 – Descriptive statistics of engagement distributed in general mean values and separated into behavioral, cognitive,
and emotional dimensions for all participants, amateur musicians, music students, and professional musicians
ALL
(N = 102)
AMATEURS
(N = 34)
STUDENTS
(N = 34)
PROFESSIONALS
(N = 34)
ENGAGEMENT
M
SD
M
SD
M
SD
M
SD
General mean values
3.51
0.54
3.51
0.48
3.44
0.61
3.58
0.51
Behavioral
3.76
0.34
3.66
0.38
3.74
0.35
3.87
0.27
Cognitive
3.31
0.55
3.32
0.52
3.21
0.66
3.39
0.45
Emotional
3.46
0.59
3.55
0.49
3.35
0.66
3.47
0.62
Note. M = Mean. SD = Standard Deviation. N = Number of participants
As presented in Table 1, the mean values for engagement were high across all participant groups,
considering that the data was collected on a scale ranging from 0 to 4. When considering the
three participant groups, the highest general mean value was observed for behavioral
engagement, followed by emotional and cognitive engagement. In the comparison of the general
mean values for engagement among the three participant groups (amateurs, students, and
professionals), the Kruskal-Wallis test indicated that there was no statistically significant
difference [χ2(2) = 1.818. p= 0.403]. In the comparisons of the general mean values for the
dimensions of engagement (all participants: behavioral, cognitive, and emotional), the Friedman
test indicated a statistically significant difference in the participants’ responses [χ2(2) = 67.497. p
< 0.001]. In this regard, the multiple pairwise comparisons indicated statistically significant
differences between: (1) behavioral and cognitive engagement (p< 0.001); (2) behavioral and
emotional engagement (p< 0.001); and (3) emotional and cognitive engagement (p= 0.017).
Figure 1 presents the mean values for the dimensions of engagement (behavioral, cognitive, and
emotional) in interaction with the participant groups (amateurs, students, and professionals).
Considering Table 1 and Figure 1, the inferential statistics are described based on between- and
within-group comparisons. In the between-group comparisons, the Kruskal-Wallis test indicated
a statistically significant difference among the responses of the three participant groups in
relation to behavioral engagement [χ2(2) = 8.865. p= 0.012]. In this regard, the multiple pairwise
comparisons test indicated only one statistically significant difference in the comparison of
responses for behavioral engagement between amateur and professional musicians (p= 0.009).
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Toni, Anderson; Araújo, Rosane Cardoso de.
“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
The Kruskal-Wallis test indicated that there were no statistically significant differences among the
responses of the three participant groups for cognitive engagement [χ2(2) = 0.392. p= 0.822] and
emotional engagement [χ2(2) = 1.880. p= 0.391].
Continuing to consider Figure 1 and Table 1, in the within-group comparisons, the Friedman test
indicated a statistically significant difference among the dimensions of engagement in the
responses of amateur musicians [χ2(2) = 13.019. p< 0.001]. In this regard, the multiple pairwise
comparisons test indicated only one statistically significant difference in the comparison of
responses between behavioral and cognitive engagement (p< 0.001) among amateur musicians.
The Friedman test also indicated a statistically significant difference among the dimensions of
engagement in the responses of music students [χ2(2) = 25.096. p< 0.001]. In this regard, the
multiple pairwise comparisons indicated statistically significant differences between behavioral
and cognitive engagement (p< 0.001) and between behavioral and emotional engagement (p=
0.011) among music students. Lastly, the Friedman test indicated a statistically significant
difference among the dimensions of engagement in the responses of professional musicians [χ2(2)
= 35.009. p< 0.001]. In this regard, the multiple pairwise comparisons indicated statistically
significant differences between behavioral and cognitive engagement (p< 0.001) and between
behavioral and emotional engagement (p< 0.001) among professional musicians.
3.2. Comparisons between each statement and participant groups
Table 2 presents the descriptive statistics derived from the list of statements (engagement and
flow) for all participants, amateur musicians, music students, and professional musicians.
As presented in Table 2, the general mean values for the statements related to behavioral
engagement were the highest, followed by the statements related to emotional and cognitive
Figure 1 – Dimensions of engagement (behavioral, cognitive, and emotional) in interaction with the participant groups
(amateur musicians, music students, and professional musicians)
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engagement. An exception to this pattern occurred in the general mean values for statements 14
and 15 of emotional engagement, which had lower mean values compared to some statements
of cognitive engagement. The Friedman test indicated a statistically significant difference among
the statements based on the general mean values [χ2(14) = 196.559. p< 0.001]. In this sense,
Table 3 presents the statistically significant differences in the multiple pairwise comparisons of
the statements (engagement and flow) based on the general mean values.
Tab. 2 – Descriptive statistics derived from the list of statements (engagement and flow) for all participants, amateur
musicians, music students, and professional musicians
STATEMENT
ALL
(N = 102)
AMATEURS
(N = 34)
STUDENTS
(N = 34)
PROFESSIONALS
(N = 34)
M
SD
M
SD
M
SD
M
SD
BEHAVIORAL
S1 – I participate or have an interest in
participating in this musical activity whenever
it is held
3.83
0.42
3.79
0.41
3.79
0.54
3.91
0.29
S2 – I really focus and concentrate on this
musical activity when I am doing it
3.78
0.50
3.68
0.59
3.76
0.49
3.91
0.98
S3 – I participate or have an interest in
participating in this musical activity for a long
period of time
3.63
0.73
3.62
0.70
3.59
0.74
3.68
0.77
S4 – I ask questions and seek resources to
improve my skills in playing an instrument (or
singing) in this musical activity
3.70
0.64
3.44
0.82
3.73
0.62
3.94
0.24
S5 – I keep trying to play/sing even when I
have difficulties
3.84
0.44
3.79
0.54
3.82
0.46
3.91
0.29
COGNITIVE
S6 – I think this musical activity is challenging
for me, but worth the effort
3.15
1.08
3.26
0.93
3.15
1.05
3.03
1.27
S7 – I think I know what to do and I am
encouraged to make my own choices about
what and how to play
3.22
0.90
3.03
0.97
3.06
0.98
3.59
0.61
S8 – I think I am good at this musical activity
and I can contribute to my personal growth
and the group growth
3.52
0.75
3.38
0.82
3.41
0.86
3.76
0.49
S9 – I think about this musical activity even
when I am not doing it
3.29
0.96
3.32
0.81
3.12
1.22
3.44
0.78
S10 – I sometimes feel absorbed in the action
when I am doing this musical activity that I
lose track of time
3.37
1.01
3.65
0.64
3.32
0.98
3.15
1.28
EMOTIONAL
S11 – I enjoy this musical activity and I have
fun when I am involved
3.77
0.56
3.85
0.43
3.76
0.55
3.70
0.67
S12 – This musical activity gives me a sense
of accomplishment and it would be very hard
for me to give up this musical activity
3.47
0.87
3.50
0.75
3.29
1.09
3.62
0.74
S13 – I feel a sense of belonging and
connection to other people when I am doing
this musical activity
3.64
0.67
3.65
0.60
3.56
0.82
3.70
0.58
S14 – If I am doing this musical activity with
other people, I feel they value it as much as I
do
3.14
0.93
3.41
0.74
2.85
1.02
3.15
0.96
S15 – If I am doing this musical activity with
other people, I feel they are supportive and
caring
3.28
0.93
3.35
0.88
3.29
1.06
3.20
0.84
Note. S = Statement. M = Mean. SD = Standard Deviation
As presented in Table 3, the multiple pairwise comparisons indicated some statistically significant
differences in the comparisons of statements (engagement and flow) based on the general mean
values. It was observed that some of the statements related to behavioral engagement had
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Toni, Anderson; Araújo, Rosane Cardoso de.
“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
statistically higher mean values than three of the statements related to cognitive engagement, as
well as some of the statements related to behavioral engagement had statistically higher mean
values than two of the statements related to emotional engagement. It was also observed that
some of the statements related to emotional engagement had statistically higher mean values
than three of the statements related to cognitive engagement. Finally, it was observed that some
statements related to emotional engagement had statistically higher mean values than two other
statements within the same dimension of engagement. Figure 2 presents the mean values for
each of the 15 statements (engagement and flow) in interaction with the participant groups
(amateurs, students, and professionals).
Tab. 3 – Statistically significant differences in the multiple pairwise comparisons of the statements (engagement and flow)
based on the general mean values
WITHIN-GROUP COMPARISONS (ALL PARTICIPANTS)
BEHAVIORAL AND COGNITIVE ENGAGEMENT
BEHAVIORAL AND EMOTIONAL ENGAGEMENT
Statement
M
Statement
M
p
Statement
M
Statement
M
p
S1
3.83
S6
3.15
**
S1
3.83
S14
3.14
***
S2
3.78
**
S2
3.78
***
S4
3.70
*
S3
3.63
**
S5
3.84
***
S4
3.70
***
S1
3.83
S7
3.22
***
S5
3.84
***
S2
3.78
***
S1
3.83
S15
3.28
**
S3
3.63
*
S2
3.78
**
S4
3.70
**
S4
3.70
*
S5
3.84
***
S5
3.84
***
S1
3.83
S9
3.29
*
S2
3.78
*
S5
3.84
**
EMOTIONAL AND COGNITIVE ENGAGEMENT
EMOTIONAL ENGAGEMENT
Statement
M
Statement
M
p
Statement
M
Statement
M
p
S11
3.77
S6
3.15
**
S11
3.77
S14
3.14
***
S11
3.77
S7
3.22
***
S13
3.64
**
S13
3.64
*
S11
3.77
S15
3.28
**
S11
3.77
S9
3.29
*
Note. S = Statement. M = Mean. * p< 0.05. ** p< 0.01. *** p< 0.001
Considering Table 2 and Figure 2, the inferential statistics are described based on between- and
within-group comparisons. In the between-group comparisons for each statement, the Kruskal-
Wallis test indicated a statistically significant difference among the responses of the three
participant groups only for statement S4 [χ2(2) = 11.228; p= 0.004], S7 [χ2(2) = 8.856; p= 0.012],
and S14 [χ2(2) = 6.631; p= 0.036]. In the within-group comparisons for each statement, the
Friedman test indicated a statistically significant difference among the responses of amateur
musicians [χ2(14) = 64.068; p< 0.001], music students [χ2(14) = 88.277; p< 0.001], and
professional musicians [χ2(14) = 91.912; p< 0.001]. Table 4 and Table 5 present the statistically
significant differences in the multiple pairwise comparisons of the statements (engagement and
flow) based on between- and within-group comparisons.
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Tab. 4 – Statistically significant differences in the multiple pairwise comparisons of the statements (engagement and flow)
based on between-group comparisons
BETWEEN-GROUP COMPARISONS
Statement
Participant Groups
M
Participant Groups
M
p
S4
Professionals
3.94
Amateurs
3.44
**
S7
Professionals
3.59
Amateurs
3.03
*
Professionals
3.59
Students
3.06
*
S14
Amateurs
3.41
Students
2.85
*
Note. S = Statement. M = Mean. * p< 0.05. ** p< 0.01.
Tab. 5 – Statistically significant differences in the multiple pairwise comparisons of the statements (engagement and flow)
based on within-group comparisons
WITHIN-GROUP COMPARISONS
STUDENTS
PROFESSIONALS
Statement
M
Statement
M
p
Statement
M
Statement
M
p
S1
3.79
S14
2.85
**
S1
3.79
S14
3,41
*
S2
3.76
**
S2
3.68
*
S3
3.59
*
S4
3.44
*
S4
3.73
**
S5
3.79
*
S5
3.82
**
S2
3.68
S15
3,35
*
S11
3.76
**
S4
3.44
*
S5
3.82
S7
3.06
*
AMATEURS
Statement
M
Statement
M
p
S1
3.79
S7
3.03
*
S5
3.79
**
S11
3.85
**
Note. S = Statement. M = Mean. * p< 0.05. ** p< 0.01.
Figure 2 – Mean values for each of the 15 statements (engagement and flow) in interaction with the participant groups
(amateur musicians, music students, and professional musicians)
Note. S = Statement
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As presented in Table 4 and Table 5, the multiple pairwise comparisons indicated some
statistically significant differences in the comparisons of statements (engagement and flow)
based on between- and within-group comparisons. In the between-group comparisons, it was
observed that the mean value for: (1) statement S4 was statistically higher for professional
musicians compared to amateur musicians; (2) statement S7 was statistically higher for
professional musicians compared to both amateur musicians and music students; and (3)
statement S14 was statistically higher for amateur musicians compared to music students.
Regarding amateur musicians, in the within-group comparisons, it was observed that two
statements related to behavioral engagement (S1 and S5) and one statement related to emotional
engagement (S11) had statistically higher mean values than one statement related to cognitive
engagement (S7). Regarding music students, it was observed that all five statements related to
behavioral engagement and one statement related to emotional engagement (S11) had
statistically higher mean values than one statement related to emotional engagement (S14).
Additionally, it was observed that one statement related to behavioral engagement (S5) had a
statistically higher mean value than one statement related to cognitive engagement (S7). Finally,
regarding professional musicians, it was observed that four statements related to behavioral
engagement (S1, S2, S3, and S5) had statistically higher mean values than one statement related
to emotional engagement (S14). Additionally, it was observed that two statements related to
behavioral engagement (S2 and S5) had statistically higher mean values than one statement
related to emotional engagement (S15).
4. Discussion
This study contributes to exploring the engagement and flow experiences in collective music
practices of amateurs, students, and professional musicians. In general, behavioral engagement
showed the highest mean values in this research, especially due to its ease of description based
on the actions performed by individuals in a task (Fredricks and McColskey 2012; Fredricks et al.
2019). This description of musical activities performed by individuals (related to behavioral
engagement) can be found in research using questionnaires that provide a list of musical actions
(e.g., Chin and Rickard 2012; Vanstone et al. 2016; Leung and Cheung 2020). Additionally, the
measurement of engagement based on observable behaviors is also found in other studies that
considered aspects of behavioral engagement to infer possibilities of cognitive and emotional
engagement that may eventually lead to a flow experience (e.g., Custodero 2005; Beineke 2015;
Wilson 2019). In this sense, behavioral engagement is revisited in the discussion of the results
concerning its relationship with cognitive and emotional engagement.
The cognitive engagement showed some of the lowest mean values, which supports discussions
in the literature about the challenges in measuring individuals’ cognitive engagement in a task
(Fredricks and McColskey 2012; Fredricks et al. 2019). Two statements related to cognitive
engagement (challenges and efforts, and self-perceived skills; S6 and S7) had statistically lower
mean values compared to statements related to behavioral and emotional engagement in both
general and specific comparisons. The statements regarding challenges and skills (S6, S7, and
S8) had similar mean values for amateur musicians and music students, although professional
musicians reported slightly higher mean values for self-perceived skills compared to reports for
challenges, as indicated by the descriptive statistics. The challenge-skill balance is crucial in a
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flow experience, as well as in the actions of participants within a group during collective flow
experiences (e.g., Walker 2010; Sawyer 2017). This study indicates a challenge-skill balance in
the three participant groups, which is also reflected in reports of emotional engagement,
considering that the feedback from the social process tends to have a shared emotional
component within the group in collective flow, often achieved through the sharing of challenges,
skills, and actions. In the case of professional musicians, their self-perceived skills (S7) showed
higher mean values than amateur musicians and music students, and they also reported higher
mean values of asking questions and seeking resources (S4) compared to amateur musicians,
results that could indicate a dynamic process of seeking resources and increasing challenges to
balance with their skills.
Some statements related to behavioral and emotional engagement (S1, S2, S5, and S11) showed
higher mean values than the statement related to reflection on the activity in cognitive
engagement (S9). The reflection on the activity tends to be difficult to measure, but the
statistically significant differences found could be related to behavioral and emotional
engagement as a way to describe some of the participants’ cognitive processes. This can be
observed when an individual performs an action that could be characterized as an extension of a
previously completed task related to their cognitive reflections, which could also be related to
aspects such as immersion and repetition of the task in a flow experience. In this regard,
Custodero (2005) suggests, for example, that the extension or continuation of an action can be
observed as a process of cognitive engagement in monitoring potential challenges in a flow
experience. Other examples of research with children, adolescents, and adults indicate the
presence of actions in the researcher’s observations and participants’ reports that represent the
extension and continuation of an action, which could be related to cognitive engagement as a
reflection on the activity (e.g., Beineke 2015; Hart and Di Blasi 2015; Toni 2023). At the same time,
considering emotional engagement, Custodero (2005) states that the extension of an action that
reflects possible cognitive aspects of reflection and challenge monitoring can represent a pursuit
to continue the enjoyment derived from an activity. The enjoyment resulting from cognitive
engagement is also described in other studies on subjective experiences of flow (e.g.,
Csikszentmihalyi 1990; Shernoff and Csikszentmihalyi 2009; Pekrun and Linnenbrink-Garcia
2012). Therefore, it is possible to propose a reflection on how behavioral and emotional
engagement can assist in describing aspects of cognitive engagement, which reinforces the need
to consider an interdependent relationship between the dimensions of engagement (e.g.,
Fredricks et al. 2004; Rose-Krasnor 2009; Christenson et al. 2012; O’Neill 2012, 2016; Fredricks
et al. 2019).
In the comparisons between participant groups for cognitive engagement, professional musicians
showed statistically higher mean value for the statement related to self-perceived skills (S7)
compared to amateur musicians and music students. This statement is related to self-regulatory
and metacognitive processes that enable the individual to develop more efficient cognitive
strategies in a domain (Garcia and Dubé 2012; Hallam 2016; Veloso and Araújo 2017). Indeed, it
is a relevant aspect of the literature on motivation and engagement, as it is also related to
cognitive strategies for learning (Fredrick et al. 2004; Cleary and Zimmerman 2012). Furthermore,
the literature indicates that musicians and individuals who are more experienced in their domains
tend to possess higher levels of self-regulatory and metacognitive skills acquired through
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experiences and processes of practice and learning over time (Ericsson and Pool 2016), this
aspect is also present in the descriptions provided by professional musicians in this study
regarding their musical background. Another implication of the literature regarding self-perceived
skills is related to the potential of linking engagement with individuals’ self-efficacy beliefs (e.g.,
Richmond et al. 2016; Kahu and Nelson 2018), as well as collective efficacy and collective flow
(Salanova et al. 2014).
In this study, the amateur musicians reported that their interest and frequency of participation,
efforts to persist in the task, and positive affective experiences of enjoyment (S1, S5, S11) were
statistically higher than the statement regarding self-perceived skills (S7). Similarly, the music
students reported that the statement regarding efforts to persist in the task (S5) was statistically
higher than the self-perceived skills (S7). These statistical differences complement the
discussions on self-regulatory and metacognitive processes, suggesting that both amateur
musicians and music students showed higher mean values for behavioral actions compared to
their self-perceived skills as a cognitive engagement. In this regard, there appears to be a
developmental path in self-perceived skills (from amateurs to professional musicians) that can
impact the pursuit of challenges and the extension of a task related to the individuals’ cognitive
reflections, considerations that were also described by Csikszentmihalyi (1996) in his
investigations on flow, creativity, and individuals’ self-perceived skills in different domains. For
amateur musicians, when they start participating in a collective music activity, the emotional
feedback from the social interaction can be an important aspect of their engagement and
collective flow (Walker 2010), a situation that is also highlighted by MacRitchie and Garrido (2019)
when describing some aspects of the behavioral and emotional engagement of amateur
musicians. Emotional engagement, in turn, can contribute to reinforcing an individual’s
motivations to engage in an activity (Janosz 2012), which could influence a process of skill
development (and their self-perceptions) over time through cognitive engagement, as observed in
professional musicians. In this process, O’Neill (2012, 2016) asserts that understanding
transformative music engagement enables us to consider development and learning in a way that
involves a transformation in how individuals perceive a challenge and construct reflections on the
development of their skills. The author states that this understanding implies reflecting on how
musical development and engagement occur in practice, teaching, and learning for different
individuals.
The emotional engagement showed a higher general mean value than cognitive engagement and
a lower general mean value than behavioral engagement, with a similar pattern observed for
some of the statements within this dimension of engagement. Corroborating research on
individuals’ engagement in music practice, teaching, and learning contexts, emotional
experiences are often mentioned in relation to (1) motivational aspects that influence individuals’
engagement, and in relation to (2) the subjective experience of engagement described in music
practices (e.g., Lamont 2012; O’Neill and Senyshyn 2012; Leung and Cheung 2020; Toni 2023).
Furthermore, social aspects such as social connection and a sense of belonging are also
presented as relevant in the literature as antecedents and indicators of musical engagement (e.g.,
Cross et al. 2012; O’Neill 2012; Joseph and Southcott 2017), which can influence the
development of a network of social and musical relationships (Juvonen et al. 2012; O’Neill 2017;
Kahu and Nelson 2018).
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The general mean values of the statements related to behavioral engagement and the emotional
engagement statements regarding the sense of belonging and the affective experiences of
enjoyment with the activity (A11 and A13) were statistically higher than the emotional
engagement statements regarding participants’ perception that other group members value
musical practice and support participation in the group (A14 and A15). In general, based on the
descriptive statistics, the mean value for the statement regarding participants’ perception that
other group members value musical practice (A14) was not significantly different from the other
statements for amateur musicians, but the reports of music students and professional musicians
may have contributed to lower the general mean value for this statement. Corroborating these
observations, amateur musicians had a statistically higher mean value for the statement
regarding participants’ perception that other group members value musical practice (A14)
compared to music students, as well as this was the only participant group that did not show a
statistically significant difference between the behavioral and emotional dimensions of
engagement. Considering the inferential and descriptive results, it is possible that music students
and professional musicians continue to engage in the actions (behavioral engagement) and
experience emotional and social aspects (emotional engagement), even if they do not perceive
that other group members value musical practice and support participation in the group. In this
case, some music students and professional musicians may not have a voluntary choice, leading
to behavioral engagement in the form of carrying out actions due to possible extrinsic motivations
(Ryan and Deci 2000; Ramey et al. 2015). However, this situation contrasts with the experiences
of belongingness and enjoyment reported by the participants. Furthermore, this discussion could
imply that individuals may experience individual flow within collective contexts (including the
reports on emotional engagement), but not necessarily collective flow that emerges from a
dynamic of sharing where the perception that other group members value musical practice and
support participation in the group plays an important role (Walker 2010; Tay et al. 2021).
It is worth considering in the detailed reports of the participants that the emotional engagement
statements related to the sense of belonging and the affective experiences of enjoyment with the
activity (A11 and A13) showed higher mean values than other statements of cognitive and
emotional engagement. Therefore, the literature suggests that it is necessary to consider
engagement not only as a product but primarily as a dynamic process that involves a series of
negotiations by individuals in a given context and task (Reschly and Christenson 2012; Wang et
al. 2019). In this way, the sense of belonging and emotional experiences can be present and can
contribute to enhancing a flow experience, even if some aspects are still consolidating or
undergoing transformation for the individual or the group (such as participants’ perception that
other group members value musical practice and support participation in the group). Indeed,
research on collective flow in music practices indicates that a sense of belonging and emotional
experiences also emerges from the process of negotiation within the group (e.g., Hart and Di
Blasi 2015; Tan et al. 2021), considering that making music in a group requires cooperative and
collaborative aspects of musical practice that can influence individuals’ motivations and emotions
(Goodman 2002; Schiavio et al. 2019). Regarding the results of this research, group music
activities can promote a sense of affiliation in which the feelings and understandings of an
individual can also be felt and understood by others through processes of social negotiation (e.g.,
Mithen 2005; Levitin 2006; Elliott and Silverman 2015; Cross 2016; Juslin 2019; Savage et al.
2021).
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Inferential statistics enable more precise conclusions to be drawn from between- and within-
group comparisons. In this way, practical interventions can be considered based on these
statistical differences, considering the results and discussion presented in this article. However,
in addition to the statistical differences, it is necessary to consider that some statements had
similar mean values for the three participant groups, contributing to the absence of a statistically
significant difference in the mean values of engagement in the general comparisons for
participant groups. An example of similar mean values among the participant groups is the
statement related to the participant’s perception of feeling absorbed in the action and the
distortion of time (S10), one of the subjective experiences reported in the state of flow
(Csikszentmihalyi 1990). Another case is the statement related to the sense of accomplishment
and the aspect that it would be very hard for the participant to give up the musical activity (S12).
In this second example, behavioral engagement could also be related to the participants’ actions
that can sustain their participation, as in the case of the behavioral engagement statement about
the interest in participating in the musical activity for a long period of time (S3). Considering deep
engagement in an activity or task that can characterize the experience of flow, Nakamura (2001)
and Nakamura and Csikszentmihalyi (2003) propose an expanded perspective on what they refer
to as vital engagement. This concept is understood as a way of relating to the world intensely and
positively, characterized by a subjective sense of meaning, enjoyment, and flow. In this sense,
the authors argue that it is difficult to sustain engagement without enjoyment, and it is difficult to
commit over time to an activity that does not provide a broader sense of accomplishment and
meaning to the individual.
5. Limitations, future research directions, and conclusion
This study has some limitations, such as using self-reported data and relying on participants’
recollections of group music practices. Therefore, future studies could consider methods such as
direct observations of group music practices, analyses of interaction between individuals,
longitudinal studies, and/or other approaches (e.g., Fredricks and McColskey 2012; Sawyer 2017;
Fredricks et al. 2019). The present study investigated the self-reported experiences of amateur
musicians, music students, and professional musicians, but the participant sample could be
expanded and further refined in future research. Additionally, future research can explore diverse
musical contexts and repertoires, and/or ensembles of different ages, with varying durations of
existence, and with different numbers of individuals. The results and discussions presented in
this study focus on individual experiences in different collective music groups, highlighting the
need for further exploration of components that explain collective flow in musical groups. It is
important to note that an individual may experience flow within a group even without the
presence of collective flow (Pels et al. 2018). Therefore, as this is the initial phase of an
explanatory sequential mixed methods project (Creswell and Plano Clark 2017), the theme will be
further explored in a study that aims to deepen the relationship between engagement and
collective flow.
Finally, this research assisted in deepening the understanding of individuals’ engagement in
collective music practices by considering that deep engagement can lead to individual flow or
collective flow experiences within an ensemble. Based on the results and discussions of this
research, individuals in a collective music practice seem to require sharing actions, reflections,
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“Exploring engagement and flow experiences in collective music practices of amateurs, students and professional musicians”
and collectively negotiated emotions that can contribute to sustaining motivations for
engagement and flow in collaborative musical and learning processes.
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7. Acknowledgment
We would like to thank all the participants for their contributions to this research.
