Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-08T01:59:59.031Z Has data issue: false hasContentIssue false

Student musicians' self- and task-theories of musical performance: the influence of primary genre affiliation

Published online by Cambridge University Press:  02 October 2009

Allan Hewitt*
Affiliation:
Tom Bone Building, 76 Southbrae Drive, Glasgow G13 1PP, [email protected]

Abstract

One hundred and sixty-five undergraduate music students studying in Scotland completed a 30-statement Q-sort to describe their self- and task-theories of musical performance. Statements reflected the importance of effort, confidence, technical ability, significant others and luck/chance in determining a successful performance. The Q-sorts were reduced to six underlying sorting patterns, or viewpoints. The relationship between sorting patterns and participants' primary genre affiliation was explored in order to identify whether self and task-theories were a function of genre affiliation. Some intuitive hypotheses of what performers of particular musical genres might think were supported by the data. However, results suggested that there was considerable diversity in self- and task-theory of performance within each of the genre affiliation groups, which supports previous research. Other background factors, such as gender, years of playing, chronological age and type of institution, were not significant predictors of self- or task-theory of musical performance.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

AUSLANDER, P. (2004) ‘Performance analysis and popular music: a manifesto’, Contemporary Theatre Review, 14 (1), 113.CrossRefGoogle Scholar
BROWN, J. S., COLLINS, A. & DUGUID, P. (1989) ‘Situated cognitions and the culture of learning’, Educational Researcher, 18 (1), 3242.CrossRefGoogle Scholar
BROWN, S. R. (1980) Political Subjectivity: Applications of Q Methodology in Political Science. New Haven, CT: Yale University Press.Google Scholar
BURT, R. & MILLS, J. (2006) ‘Taking the plunge: the hopes and fears of students as they begin music college’, British Journal of Music Education, 23, 5173.CrossRefGoogle Scholar
COPE, P. (2002) ‘Informal learning of musical instruments: the importance of social context’, Music Education Research, 4, 93104.CrossRefGoogle Scholar
CREECH, A., PAPAGEORGI, I., DUFFY, C. et al. (2008) ‘Investigating musical performance: commonality and diversity among classical and non-classical musicians’, Music Education Research, 10, 215234.CrossRefGoogle Scholar
CRUZ-ALCAZAR, P. P., VIDAL-RUIZ, E. & PEREZ-CORTES, J. C. (2003) Musical Style Identification using Grammatical Inference: The Encoding Problem Progress in Pattern Recognition, Speech and Image Analysis. Berlin: Springer.Google Scholar
DANIEL, R. (2004) ‘Peer assessment in musical performance: the development, trial and evaluation of a methodology for the Australian tertiary environment’, British Journal of Music Education, 21, 89110.CrossRefGoogle Scholar
DWECK, C. S. (1999) Self-theories: Their Role in Motivation, Personality and Development. Philadelphia: Psychology Press.Google Scholar
HARGREAVES, D. & MARSHALL, N. A. (2003) ‘Developing identities in music education’, Music Education Research, 5, 263273.CrossRefGoogle Scholar
HEWITT, A. (2004) ‘Students’ attributions of sources of influence on self-perception in solo performance in music’, Research Studies in Music Education, 22, 4258.CrossRefGoogle Scholar
KERLINGER, F. N. (1973) Foundations of Behavioral Research. New York: Holt, Rinehart and Winston.Google Scholar
LAVE, J. & WENGER, E. (1991) Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
LEBLANC, A., JIN, Y. C., OBERT, M. & SIIVOLA, C. (1997) ‘Effect of audience on music performance anxiety’, Journal of Research in Music Education, 45, 480496.CrossRefGoogle Scholar
LITTLE, T. D., LOPEZ, D. F., OETTINGEN, G., & BALTES, P. B. (2001) ‘A comparative-longitudinal study of action control beliefs and school performance: On the role of context’, International Journal of Behavioral Development, 25, 237245.CrossRefGoogle Scholar
MCKEOWN, B. & THOMAS, D. (1988) Q Methodology. Newbury Park: Sage Publications.CrossRefGoogle Scholar
MEYER, L. B. (1989) Style and Music: Theory, History and Ideology. Chicago: University of Chicago Press.Google Scholar
MILLS, J. (2002) ‘Conservatoire students’ perceptions of the characteristics of effective instrumental and vocal tuition’, Bulletin of the Council for Research in Music Education, 153–154, 7882.Google Scholar
SCHMITZ, B. & SKINNER, E. A. (1993) ‘Perceived control, effort, and academic performance: Interindividual, intraindividual, and multivariate time-series analysis’,Journal of Personality and Social Psychology, 64, 10101028.CrossRefGoogle Scholar
SKINNER, E. A. (1995) Perceived Control, Motivation and Coping. Thousand Oaks, CA: Sage Publications.CrossRefGoogle Scholar
STANLEY, M., BROOKER, R. & GILBERT, R. (2002) ‘Examiner perceptions of using criteria in music performance assessment’, Research Studies in Music Education, 18, 4656.CrossRefGoogle Scholar
STEPHENSON, W. (1953) The Study of Behavior: Q-Technique and its Methodology. Chicago: University of Chicago Press.Google Scholar
STOCKFELT, O. (2004) ‘Adequate modes of listening’, in Cox, C. & Warner, D. (Eds), Audio Culture: Readings in Modern Music. London: Continuum.Google Scholar
VYGOTSKY, L. S. (1986) Thought and Language. Cambridge, MA: MIT Press.Google Scholar
WELCH, G., PAPAGEORGI, I., HADDON, L. et al. (2008) ‘Musical genre and gender as factors in higher education learning in music’, Research Papers in Education, 23, 203217.CrossRefGoogle Scholar