Although flow theory is one way of measuring the quality of a student’s experience in a music ensemble, the majority of flow research utilizes samples of high school or collegiate level musicians thus causing us to generalize findings to young adolescent (middle school) populations. Using a convergent parallel mixed methods design, the purpose of this study was to examine factors that may contribute to flow experiences of students in a middle school band. Quantitative data (surveys that included the Experience Sampling Method) and qualitative data (case study of an eighth grade band) were analyzed separately before being merged into a final analysis. Results provide evidence to support that flow is an individualized experience even though students were not in flow based on self-perceived ratings of challenge and skill. Mixed methods results also suggest that young adolescent students may not conceptualize flow in the same manner as older adolescents, thus erroneously suggesting that flow did not occur. Recommendations for future research include exploring alternative vocabulary for flow characteristics for use in Experience Sampling Method surveys, expanding the sample to include music programs at multiple middle schools to create additional regression model predictor variables, and longitudinal explorations of flow over time within large ensembles.
CarbonaroW. (2005). Tracking, students’ effort, and academic achievement. Sociology of Education, 78, 27–49.
2.
CassieV. K. (2011). An investigation of flow experience in middle school beginner string orchestra students (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses database. (UMI No. 3483220)
3.
ClementsonC. J. (2018). Flow in the middle school band. Manuscript in preparation.
4.
CramerR. (1997). What materials are you going to teach “about music” “through music” while “performing music?” In MilesR. (Ed.), Teaching music through performance in band (pp. 7–10). Chicago, IL: GIA Publications.
5.
CreswellJ. W. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, CA: Sage.
6.
CreswellJ. W.Plano ClarkV. L. (2011). Designing and conducting mixed methods research (2nd ed.). Thousand Oaks, CA: Sage.
7.
CsikszentmihalyiM. (1990). Flow: The psychology of optimal experience. New York, NY: Harper & Row.
8.
CsikszentmihalyiM.CsikszentmihalyiI. S. (Eds.). (1988). Optimal experience: Psychological studies of flow in consciousness. New York, NY: Cambridge University Press.
9.
CustoderoL. (1997). An observational study of flow experience in young children’s music learning (Doctoral dissertation). University of Southern California, Los Angeles, CA.
10.
CustoderoL. A. (2005). Observable indicators of flow experience: A developmental perspective on musical engagement in young children from infancy to school age. Music Education Research, 7, 185–209.
11.
DiazF. M.SilveiraJ. M. (2012). Dimensions of flow in academic and social activities among summer music camp participants. International Journal of Music Education, 31, 310–320.
12.
DollB. (2007). ClassMaps. Unpublished instrument. Lincoln: University of Nebraska Lincoln.
13.
DollB.SpiesR. A.ChampionA.GuerreroC.DooleyK.TurnerA. (2010). The ClassMaps survey: A measure of middle school science students’ perceptions of classroom characteristics. Journal of Psychoeducational Assessment, 28, 338–348.
14.
DollB.SpiesR. A.LeClairC. M.KurienS.FoleyB. F. (2010). Student perceptions of classroom learning environments: Development of the ClassMaps survey. School Psychology Review, 39, 203–218.
15.
EcclesJ. S.MidgleyC.WigfieldA.Miller BuchananC.ReumanD.FlanaganC.Mac IverD. (1993). Development during adolescence: The impact of stage-environment fit on young adolescents’ experiences in school and in families. American Psychologist, 48(2), 90–101.
16.
EngeserS.Schiepe-TiskaA. (2012). Historical lines and an overview of current research on flow. In EngeserS. (Ed.), Advances in flow research (pp. 1–22). New York, NY: Springer.
17.
FitzpatrickK. R. (2008). A mixed methods portrait of urban instrumental music teaching (Doctoral dissertation). Retrieved from ProQuest Dissertation and Theses Database. (UMI No. 3303647)
18.
FreerP. K. (2008). Teacher instructional language and student experience in middle school choral rehearsals. Music Education Research, 10, 107–124.
19.
GarsonG. D. (2013). Preparing to analyze multilevel data. In GarsonG. D. (Ed.), Hierarchical linear modeling: Guide and applications (pp. 27–54). Thousand Oaks, CA: Sage.
20.
GrbichC. (2007). Qualitative data analysis: An introduction. Thousand Oaks, CA: Sage.
21.
HargreavesA.EarlL.RyanJ. (1996). Schooling for change: Reinventing education for early adolescents. Washington, DC: Falmer Press.
22.
HektnerJ. M.SchmidtJ. A.CsikszentmihalyiM. (2007). Experience sampling method: Measuring the quality of everyday life. Thousand Oaks, CA: Sage.
23.
JacksonS. A. (2001). LONG dispositional flow scale (DFS-2). Mind Garden. Retrieved from www.mindgarden.com
24.
JarosM. D. (2008). Optimal experience in the choral rehearsal: A study of flow and affect among singers (Doctoral dissertation). University of Minnesota, Minneapolis, MN.
25.
KellerJ.LandhäußerA. (2012). The flow model revisited. In EngeserS. (Ed.), Advances in flow research (pp. 51–64). doi: 10.1007/978–1–4614–2359–1_2
26.
KrausB. N. (2003). Musicians in flow: Optimal experience in the wind ensemble rehearsal (Doctoral dissertation). Arizona State University, Phoenix, AZ.
27.
LeCompteM. D.SchensulJ. J. (2013). Analysis and interpretation of ethnographic data. Lanham, MD: Rowman & Littlefield.
28.
LillA. L. (2015). Informal learnings? Young people’s informal learning of music in Australian and British schools (Doctoral dissertation). University of Sydney, Sydney, Australia.
29.
LipsitzJ. (1977). Growing up forgotten: A review of research and programs concerning early adolescence. Lexington, MA: D.C. Heath and Company.
30.
LounsburyJ. H.ClarkD. C. (1990). Inside grade eight: From apathy to excitement. Reston, VA: National Association of Secondary School Principals.
31.
MarottoM.RoosJ.VictorB. (2007). Collective virtuosity in organizations: A study of peak performance in an orchestra. Journal of Management Studies, 44, 388–413.
32.
MartinA. J.JacksonS. A. (2008). Brief approaches to assessing task absorption and enhanced subjective experience: Examining “short” and “core” flow in diverse performance domains. Motivation and Emotion, 32, 141–157.
33.
MertensS. B.AnfaraV. A.Jr.CaskeyM. M. (Eds.). (2007). The young adolescent and the middle school. Charlotte, NC: National Middle School Association.
34.
MonetaG. B. (2012). On the measurement and conceptualization of flow. In EngeserS. (Ed.), Advances in flow research (pp. 23–50).
35.
MonetaG. B.CsikszentmihalyiM. (1996). The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality, 64, 275–310.
36.
MontanezC. M. (2011). An exploration of flow experiences among California Central Valley high school instrumental music students (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses Database. (UMI No. 3465728)
37.
MorrisonS. J. (2001). The school ensemble: A culture of our own. Music Educators Journal, 88(2), 24–28.
38.
National Research Council and the Institute of Medicine. (2004). Engaging schools: Fostering high school students’ motivation to learn. Washington, DC: The National Academies Press.
39.
OareS. (2008). The Chelsea House Orchestra: A case study of a non-traditional school instrumental ensemble. Bulletin of the Council of Research in Music Education, 177, 63–78.
40.
O’NeillS. (1999). Flow theory and the development of musical performance skills. Bulletin of the Council of Research in Music Education, 141, 129–134.
41.
OnwuegbuzieA. J.CollinsK. M. T. (2007). A typology of mixed methods sampling designs in social science research. The Qualitative Report, 12, 281–316.
42.
OnwuegbuzieA. J.LeechN. L. (2007). Sampling designs in qualitative research: Making the sampling process more public. The Qualitative Report, 12, 238–254.
43.
RaudenbushS. W.ByrkA. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.
44.
RheinbergF. (2008). Intrinsic motivation and flow. In HeckhausenJ.HeckhausenH. (Eds.), Motivation and action (pp. 323–348). Cambridge, UK: Cambridge University Press.
45.
SchmidtJ. A.ShernoffD. J.CsikszentmihalyiM. (2007). Individual and situational factors related to the experience of flow in adolescence. In OngA. D.van DulmenM. H. M. (Eds.), Oxford handbook of methods in positive psychology (pp. 542–558). New York, NY: Oxford University Press.
46.
ShernoffD. J. (2013). Optimal learning environments to promote student engagement. New York, NY: Springer.
47.
ShernoffD. J.CsikszentmihalyiM. (2009). Flow in schools: Cultivating engaged learners and optimal learning environments. In GilmanR.HuebnerE. S.FurlongM. J. (Eds.), Handbook of positive psychology in schools (pp. 131–145). New York, NY: Routledge.
48.
SinnamonS.MoranA.O’ConnellM. (2012). Flow among musicians: Measuring peak experiences of student performers. Journal of Research in Music Education, 60, 6–25.
49.
Slonim-NevoV.NevoI. (2009). Conflicting findings in mixed methods research: An illustration from an Israeli study on immigration. Journal of Mixed Methods Research, 3, 109–128.
50.
Smolej FritzB.AvsecA. (2007). The experience of flow and subjective well-being of music students. Horizons of Psychology, 16(2), 5–17.
51.
StakeR. E. (1994). Case study: Composition and performance. Bulletin of the Council for Research in Music Education, 122, 31–44.
52.
StakeR. E. (1995). The art of case study research. Thousand Oaks, CA: Sage.
