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Table 4

Regression Analysis for POPTST Regressed on the Music Listening Siyle Scores for Popular Music and CONTST

A t-test was used to analyze the differences among the test score means for CLASTST, POPTST, and CONTST. Table 5 presents the comparison of math test score means and their corresponding t-tests. The t-test revealed no statistically significant differences among the three testing conditions. One may assume that the presence of either classical or popular background music had no effect on the subjects' math test performance.

Table 5

Comparison of Math Test Score Means

Table 6 presents the results of the post-hoc procedure where the variables YC ("When I study, listening to classical music interferes with my concentration") and YP ("When I study, listening to popular music interferes with my concentration") were coded 1 for a yes and 0 for a no response. 33% of the respondents indicated that classical music interferes with their studying, while 43% of the subjects indicated that popular music interferes with their studying. The variables CLASTST and POPTST were then regressed on YC and YP respectively, Controlling for CONTST . The variables YC and YP also had no statistically significant effect on, or correlation with, CLASTST and POPTST respectively. Also, the various independent variables were tested for interactions and curvilinearity, revealing no statistically significant results as illustrated in Table 7.

Table 6

Post Hoc Results of the Effects of Students' Preferences for Study with Music on Math Test Scores

Dependent Variable = POPTST

Dependent Variable = CLASTST

Table 7

Correlation Coefficients of Classical and Popular Music Listening Styles

p <.05

Conclusions and Discussion

The music listening styles selected as independent variables for this study had no statistically significant effect on the dependent variables, math test scores. Examination of the correlation matrices in Table 7 revealed no significant bivariate correlations between music listening styles and math test scores. However, correlations among the independent variables implied that multicolinearity may have contributed to the lack of statistical support for the model. However, an exploratory factor analysis of the variables did not reveal any second order factors.

CONTST, the math test taken with no background music, was a statistically significant predictor of math performance under both classical and popular music listening conditions. However, there was not a statistically significant difference in the mean scores of the three tests, leading one to question if background music has any effect, either positive or negative, on math test performance. Also, the students' self report data on interference by background music suggested no effect on the math test scores. This finding supports studies by Wolfe (1983) and LaBach (1960) reporting that students' self reports of background music interference had no effect on their performance.

Future studies of this nature might employ a hypothesis suggested by Roth (1975) when he investigated the effects of background music on a variety of academic tasks; and look toward an interaction between the music and task. The present study suggests that music listening styles have no effect on the interference effect of background music. Also students' attitudes toward background music during testing situations may present an interesting.study. Although several studies have refuted the short term effect of background music on academic performance (LaBach, 1960; Wolfe, 1983; Kelly, 1993), a long term effect in attitude toward a subject and achievement might be the subject of future studies.

References

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