The Effect of Choral Music Teacher Experience - Research Paper Example

The Effect of Choral Music Teacher Experience and Background on Music Teaching Style Alan Gumm Central Michigan Research Design: Music teaching behavior of music teachers has been subject of extensive research and different aspects of this subject has been studied in detail and reported by different scholars (Forsythe, 1975; Madsen et al, 1989). However, a holistic and cognitive theory of the development of music teaching was still lacking and this is what has motivated Alan Gumm to carry out research in this area of music education. Alan Gumm is a very senior and dedicated scholar in this field of music education research. The findings reported in this paper of Alan Gumm belongs to one of his work in very matured phase of his career and therefore, this paper has liberally used results from his previous work (Gumm, 1992; Gumm, 1993; Gumm & Essmann-Paulson, 2001), besides those from other published literature in this field. This research was intended to investigate the development of music teaching style based on analysis of years of experience and other background variables of music teachers. The researcher Alan Gumm has tried to explore and establish the effect of choral music teacher experience and background on music teaching style. Besides, he has also tried to explore the relationship between background variables of music teachers. For this purpose the research was designed according to a theoretical model of music teaching style developed by the researcher (Alan Gumm) himself (Gumm, 1993). This theoretical model was validated by the researcher and a multidimensional statistical procedure was developed for use with the variables covered in this paper. It is worth mentioning here that development and validation of the underlying theoretical model was not the subject of this paper, rather that has been done long back by the researcher and the validity of this model was assumed in this paper. Therefore, this paper reports collection and analysis of data according to the model and the conclusions drawn. In this research, the data on the background variables of music teachers and their music teaching style has been collected by using a suitable questionnaire. Thus instrument of data collection was a questionnaire. Whenever, data is collected by using a questionnaire, it is important to explore the reliability of the data collection instrument. By reliability, it means that when same question is presented to the same subject after a sufficient time gap, then there should be consistency in his / her response. Thus reliability is an important aspect of any quantitative experiment design. Other important aspects of a quantitative research are sampling, analysis using suitable statistics and generalizability. These aspects of a quantitative research as relevant to this paper are briefly discussed in the subsequent sections. Validity This is a very important element of any quantitative research. Bollen (1989, 184) has defined validity as “concerned with whether a variable measures what it is supposed to ensure.” This is concerned with the success of measuring what was intended to be measured in the research. This term is used in different sense in relation to a quantitative research like ‘internal validity’, ‘external validity’, ‘ecological validity’, ‘population validity’ etc. Internal validity is something that estimates the degree to which conclusions about causes of relations are likely to be true, in contex of the measures used, the research setting, and the whole research design. Good experimental techniques in which the effect of an independent variable on a dependent variable is studied under highly controlled conditions leads to very high internal validity, however, the same is not the case with a research design that collects data by survey etc. and then seeks to establish a causal relationship. External validity concerns the question to what extent one may safely generalize the findings of an internally valid quantitative research from the sample studied to the target population as well as to the other populations across the time and space. It should be borne in mind that only an internally valid research design could lead to a conclusion with or without external validity. In this research, Alan Gumm has claimed that the theoretical model and the research design used by him in the work reported in this article were validated over a period of a very long time span in his scholarly career. He goes on to the extent of claiming that the work reported in this article was delayed only to ensure that the model was validated before doinng this work. His claims appears to be reasonable consider his experience and scholarly publications in this field, however, only on the basis of this paper, it is difficult to estimate the validity of the theoretical model used in this research. He has not provided, the results of the validity tests performed on the theoretical model used in this work, which he should have provided in stead of simply stating that the model was validated many times in past. Reliability Reliability is concerned with repeatability or accuracy of the actual measuring instrument used for data collection. Reliability is very important in quantitative analysis. It reliability refers to the accuracy and precision of the instrument used for data collection and its internal consistency (Cohen et al 2007). In this study, the questionnaire was the instrument of data collection. Though, the questionnaire was designed by the researcher after extensive literature review and based on his own experience as well as that of his co-workers, it was essential to ensure the reliability of the data collecting instrument the questionnaire. This could have been measured by by test – retest method. In this method, the questionnaire is presented to the same set of subject twice with sufficiently time gap (two weeks or more) between two surveys and then reliability of the questionnaire is measured by using kappa statistics K (Siegel & Castellan, 1988). However, in this paper the researchers have not spoken anything about reliability of the test instrument i.e. the questionnaire. This could be due to the fact that, he must of tested reliability of this questionnaire in their previous studies on topics in the same subject during the course of validation of his theoretical model and therefore, might not have felt it necessary to do it again in this paper. Therefore, on the basis of this paper itself it becomes difficult to comment on the reliability of the data collection instrument i.e. the questionnaire. Sampling and Data Collection Fairly large sample was attempted as the questionnaire was sent to as many as 2000 schools all over the country and thus including approximately one in seven schools in almost every state and territory of the country. The subjects were followed seriously by sending reminders twice to return the questionnaire. As many as 473 responses were received. This number represents a fairly large sample to carry out the kind of study planned in this work. However, the fact that only 473 out of a total 2000 questionnaire returned raises a question or two about efficacy of survey as an instrument of data collection. One obvious problem is, though the researcher had tried to do a stratified random sampling of the schools, while sending the questionnaire, he cannot be sure that the responses which came back to him for analysis also follow the pattern. It may be possible that he received more response from a particular region than from another and this is bound to skew the sample and affect the validity (mainly external) of the research. Another bigger issue is the fact that only ~ 20% of the targeted subjects participated in the survey and this is an indicator of apathy or unwillingness of the subjects to participate in such a survey. Therefore, one may not be sure that those who completed the questionnaire, did it seriously, giving out their true opinion or they have simply filled it just for the sake of doing away with it. If that is the case then also the internal as well as external validity of the research is in jeopardy. One way to minimize this effect could be to offer some incentives to the subjects so that they devote their time and return their honest and true response against the questions in the questionnaire. Use of Appropriate Statistics The data in this study was processed using SPSS – 10 advanced statistical software. Alan Gumm has conducted descriptive statistical analysis of different background variables like Gender, Age, Ethnicity, Religion, Educational Degree, Professional affiliation etc. of the music teachers. The statistics used are descriptive statistics of background variables like mean, median, mode, range etc. While mean, median and mode are measure of central tendency; range and standard deviation are measures of dispersion of data around the mean. These are relevant statistics and in this sense the research has been successful in drawing useful information and trends about the background variables of the music teachers. The researcher has performed Chi-Square test to examine if there was a significant difference in music teaching style of new music teachers and experienced music teachers. Chi-square test is conducted to test goodness of fit for a dataset. This test determines whether the observed frequency distribution is significantly different from theoretical frequency distribution or not. The researcher has also performed regression analysis to explore causal relationship between the background variables and different aspects of music teaching style of the teachers. This is also an appropriate statistical procedure and the researchers have been successful in doing what was needed to be done. In regression analysis, the causal relationship between predictor variable(s) and predicted or dependent variable is quantified. In this study, music teaching style was the predicted variable and the predictor variables are background variables of the music teacher and contextual variables. In regression analysis, the dependent variable is expressed as a multivariate equation with coefficients () for each predictor variable. Besides, there is a very important parameter the coefficient of determination (R2). It is square of Pearson’s correlation coefficient and tells the percent of the variation in the dependent variable is on the account of variation in independent or predictor variable(s). Thus, its value gives an idea about the strength of the regression model. Its value lies between -1 to +1. Values close to -1 imply strong negative correlation; values close to +1 imply strong positive correlation and values close to zero imply no correlation. In this case there was moderate correlation. Conclusion: This article is a good work and it has used appropriate statistics to draw meaningful inferences about the intended study. However, I have strong reservation about Alan Gumm’s claim that surveys are the best way to collect the data for this kind of study. In this study, the data about music teachers’ background as well as the data pertaining obtained by means of a survey, where the teacher fills everything about himself / herself. In my opinion this incorporates lot of personal bias in the data. Which teacher will like to report something about himself which can be construed as weakness or has any negative implication. What I suggest is that the data about their background should have been obtained from the database available with the school administration and about the music style should have been collected by getting the response forms filled by the students. I have not seen any reported work which has collected and analyzed the data about music teaching style of the teachers from their students. Such a data will be more meaningful and throw a better light on the issues that the researcher has tried to look upon. Besides, the researcher should have incorporated the details of the validity and reliability tests – statistics used and the results, in this paper. References Bollen, Kenneth A., “Structural Equations with Latent Variables”, New York: Wiley, 1989, p 184 Cohen L., Manion L., Morrison K., “Research Methods in Education”, 6th Ed., Routledge, 2007 Forsythe, J. L. (1975). "The effect of teacher approval, disapproval, and errors on student attentiveness: Music versus classroom teachers." In C. K. Madsen, R. D. Greer, and C. H. Madsen, Jr. (Eds.), Research in music behavior: Modifying music behavior in the classroom. New York: Teachers College Press. Gumm, A. J. (1992). "Music teaching styles: a review and conceptualization of literature." Southeastern Journal of Music Education, 4, 12-34. Gumm, A. J. (1993). "The development of a model and assessment instrument of choral music teaching styles." Journal of Research in Music Education, 41, 181-199. Gumm, A. J., & Essmann-Paulsen, C. I. (2001). "The effect of instrumental student motivation for music on perceptions of music teaching style." Paper presented at the Southeastern Music Education Symposium, Athens, Georgia, May 18, 2001. Madsen, C. K., Standley, J. M., & Cassidy, J. W. (1989). "Demonstration and recognition of high and low contrasts in teacher intensity." Journal of Research in Music Education, 37, 85-92. Siegel, S., & Castellan, J. N. (1988). Nonparametric statistics for the behavioral sciences. New York: McGraw-Hill Book Co. Read More