the arts, creativity, & opportunity

vivienne alcantar

abstract

This study aims to explores the impact of social factors on creativity and value of arts or culture education. The preexisting literature on this topic mainly focuses on the impact of race and education on arts participation, and how education impacts ideas on arts funding, but there is a gap in the literature focusing on creativity and the self-reported importance of arts education. There are two research questions this study aims to answer. First, is there a relationship between race, class, and how often people get the chance to be creative? Then, does education have an impact on how important people find studying art or culture through classes or lessons? The findings show that there is a partial association within the relationship between race and how often people get the chance to be creative, when controlling for income. This is because the relationship between race and how often people get the chance to be creative, for those whose household income was over $75,000, was proven statistically significant. Although, for those who made less than $75,000, this relationship was proven statistically insignificant. Furthermore, the relationship between education and how important people find studying the arts or culture through classes or lessons was proven statistically significant.

introduction

The arts have long served as a medium for both individuals and communities to express their creativity, experiences, and ideas. Furthermore, the benefits of engaging in the arts and exercising one’s creativity through the arts have proven numerous. For instance, both the arts and creativity have demonstrated various health benefits (Garisch, 2014). In fact, engaging in creative practices has caused the brain to move into meditative and restful states thereby, reducing levels of stress (Lopez-Gonzales & Limb, 2012). Similarly, visual art has had positive impacts on personal health, especially in providing those who are struggling with illness the ability to focus on positive experiences and realize self-worth (Stuckey & Nobel, 2010).

In addition to generating plentiful health benefits, the arts and creativity have also generated higher levels of success in school and reinforced skills that can be translated to a diverse number of other fields and practices (Shaheen, 2010). Indeed, implementation of arts integration programs has even led to higher test scores in reading and science in middle school students (Townes, 2016).

Despite all of these benefits, support for the arts continues to minimize. Changes in educational funding and policy have decreased the presence of the arts and creativity in schools (Major 2013). Moreover, cuts in arts education have been unequally dispersed amongst children across race and socioeconomic status, most disproportionately impacting low-income Black and Latino children (Rabkin & Hedberg, 2011). Therefore, since low-income children from racially and ethnically underrepresented groups have less exposure to creative practices in childhood, do race and income impact opportunities to be creative in adulthood? Furthermore, since arts education has decreased in K-12 schools, will adults value this education in adulthood? If so, with higher exposure to the arts in higher education (Warburton, 2006), will educational level impact how much people value arts education in adulthood? This paper aims to discover if there is a significant relationship between race, income, and opportunities to be creative, and if there is a significant relationship between education and how important people find studying arts or culture through classes or lessons.

While there has not been a great deal of empirical research regarding these specific relationships, there has been research on related topics. Research by Samuel Shaw and Daniel Monroe Sullivan focused on racial exclusion in arts participation and found that Black residents participated less in local arts events than White residents, because they typically felt unwelcome or uncomfortable (2011). Another study discovered that non-Hispanic white participants attended museums and live theatres more than those who were non-white (Paredes, 2016). In regards to education, a study by Aaron Reeves found that education influenced a higher level of arts participation in adulthood (2014). However, arts participation in this study did not include attending arts lessons or classes. When considering the value of the arts, one study by Arthur C. Brooks found that those with a higher level of education would choose to increase public spending for the arts (2014). Therefore, the preexisting research on arts participation may have implications for my hypothesis that race will impact how often people can be creative. Additionally, the research on education, arts participation, and arts funding may have implications for how much adults value arts education. However, there is a gap in the literature on whether or not income and race influence, specifically, how often people can be creative. Additionally, there is a gap in the literature pertaining to arts education in adults and how greatly they value it.

There are two research questions I aim to answer with the results of my analysis. The first, what is the relationship between race, class, and how often people can be creative? The second, does education have an impact on how important people find studying art or culture through classes or lessons? My hypotheses are: There is a relationship between race, class, and how often people can be creative, and that education does have an impact on how important people find studying art or culture through classes or lessons. My null hypotheses are: there is no relationship between race, class, and how often people can be creative, and that there is no relationship between education and how important people believe it is to study arts or culture through lessons or classes.

methods

The dataset I used was, Creating Connection: Building Public Will for Arts and Culture. The data was collected by Arts Midwest, a regional arts nonprofit based out of Minneapolis, and Metropolitan Group, an agency that provides services to organizations and communities working towards social change (Arts Midwest & Metropolitan Group, 2017). The data was collected throughout the month of September in 2014 using a survey that was administered both as a web based survey and through telephone interviews (Arts Midwest & Metropolitan Group, 2017). The study received a total of 2,586 observations, with samples from Minnesota, Oregon, Michigan, and San Jose, California (Arts Midwest & Metropolitan Group, 2017). In this study, the unit of analysis is individuals. The five variables I chose to focus on from this data set were: race, socioeconomic class, education, how often people can be creative, and how important people believe it is to learn about arts or culture through classes or lessons.

My first independent variable, race, is measured nominally. The categories are as follows: American Indian/Alaska Native, Asian, Black, Latino, Native Hawaiian/Pacific Islander, White, Multiracial, other, and I don’t know. I removed the category of “I don’t know,” by marking it as missing from this analysis. Otherwise, all other racial categories were included to create a multiracial analysis.

My second independent variable is socioeconomic class, which is measured ordinally. I chose to measure class by the participants’ self-reported average household income, which was recoded into three different variables in the original dataset. The original variable, household income, included the categories: below $20,000, $20,000-$30,000, $31,000-$40,000, $41,000- $50,000, $51,000-$75,000, $76,000-$100,000, $101,000-$150,000, $151,000-$200,000, and over $200,000. The first recoded version of this variable was labeled, household income 2, which dichotomized the variable into the following two categories, below $50,000 and above $50,000. The second recoded version of this variable was labeled, household income 3, and dichotomized the variable into the categories, below $75,000 and above $75,000. I chose to use household income three, because it seemed like a more accurate distinction between the lower and upper class, which I was more interested in analyzing. Furthermore, using a dichotomous version of this variable would make the layered analysis of race, class, and how often people can be creative, simpler to analyze.

My last independent variable is education, which is measured ordinally. The original categories included: 1-11th grade, high school graduate, non-college post high school, some college, college graduate, and post-graduate degree. I recoded this variable to combine the categories of high school graduate and non-college post high school, because these two categories were similar enough to combine without skewing the responses. Additionally, combining the two categories reduced the total amount of categories from six to five, which made the data easier to analyze.

As for my dependent variables, there were two that I chose to examine. The variable, how often people can be creative, is measured ordinally. The categories for this variable included, very often, somewhat often, rarely, and never. My second dependent variable, how important people find studying arts or culture through lessons or classes, is also measured ordinally. The categories for this variable were, very important, somewhat important, a little important, and not at all important.

While it would have made the layered analysis between, how often people can be creative, race, and class, easier had I recoded this variable to condense the categories, I chose not to. I did not recode either of my dependent variables since they were measured on a likert scale. Therefore, the levels of agreement would have made recoding these variables more difficult, and in an effort to preserve the accuracy of the responses, I left both dependent variable categories as they were.

analysis

In order to analyze my data, I will use SPSS Statistical Software. To execute a comprehensive analysis, I will use both descriptive and inferential statistics in my hypothesis testing. The descriptive statistics I will use are frequency distributions. For inferential statistics, I will create bivariate tables and then perform Chi-square tests on the variables. I will use an alpha level of 0.05 to test for statistical significance between the variables. If I find a p-value of less than 0.05, then I will conclude that there is a statistically significant relationship between my chosen variables. However, if I find that the p-value is above 0.05, then I will need to accept the null hypothesis and recognize that there is no statistically significant relationship between my variables.

I will begin my analysis by running frequency tables for each variable on SPSS. This will provide me with the percentages of individuals in each category for all variables. Afterwards, I will also generate histograms and pie charts which represent these percentages to act as visual aids. Then, I will generate a layered bivariate table that displays the connection between how often people get the chance to be creative and race, while controlling for income. After this, I will conduct a Chi-square test to establish statistical significance or insignificance.

After I have completed my analyses for the variables in my first hypothesis, I will analyze the variables in my second hypothesis. I will do this by first generating a bivariate table focusing on the relationship between how often people study art or culture through classes or lessons and education. Once this is complete, I will perform a Chi-square test to assess the level of statistical significance between the two variables.

results

I will begin sharing my findings by reviewing the results of my frequency tables for each variable. For the first independent variable (See Appendix, Table/Graph 1), race, an immense majority of respondents were white, at 69.56%. Then, 10.91% of respondents were Latino, 8.33% were Black, 7.17% were Asian, 2.11% were Multi-racial, 1.05% were American Indian or Alaska Native, 0.65% identified as “other,” and 0.22% were Native Hawaiian or Pacific Islander. I acknowledge that there is a significant lack of representation in all non-white racial groups in comparison to the white participants, and that this will likely create limitations for the findings in this analysis. However, I included all racial categories in order to conduct a multiracial analysis that could draw comparisons between all racial groups, rather than only a select few.

For my second independent variable (Table/Graph 2), household income, more respondents made less than $75,000, with these participants making up 60.50% of all respondents. Whereas, 39.50% of respondents made above $75,000. For my third independent variable (Table/Graph 3), education, the highest group of respondents were those who attended some college at 34.77%. Following this group, 29.15% of respondents were college graduates, 22.69% were high school graduates, 11.04% attended postgraduate school, and 2.35% completed 1-11th grade. Again, the lower frequency of participants making up those who completed 1-11th grade, and those who attended postgraduate school, will likely create limitations for this analysis. However, I included them in order to draw comparisons between them and other participants who had varying levels of education, because these similarities or differences could prove valuable in the analysis.

Now I will detail the frequency table findings for my dependent variables. For the dependent variable, how often people get the chance to be creative (Table/Graph 4), the majority of respondents answered somewhat often, at 41.91%. Then, 37.71% responded rarely, 15.78% responded very often, and 4.60% responded never. For the dependent variable, how important do people find studying art or culture through classes or lessons (Table/Graph 5), the majority of respondents answered not important at all, at 39.87%. Following this was a little important at 28.67%, somewhat important at 19.51%, and very important at 11.95%.

After completing my frequency tables for all variables, I generated bi-variate tables to discover the connections between my independent and dependent variables. The first table I generated focused on the relationship between race and how often people get to be creative, while controlling for income (Bivariate Table 1). Here, Latino and Black respondents in both income categories, below $75,000 and above $75,000, represented the highest percentages in the more frequently creative category, very often. That is, Latino respondents were the most frequently creative of those who made under $75,000 with 24% having answered that they were creative very often. Additionally, Black respondents who made under $75,000 responded that they were creative very often at 22.2%, making them the second most frequently creative racial group in that income category. These two racial groups also represented the most frequently creative of those who made over $75,000. Although, in this income category, Black respondents had a higher percentage of respondents who answered very often, at 44.4%, than Latinos, at 29.3%.

After examining which racial groups were creative most often in both income categories, I turned my attention to which racial groups had the highest percentage of respondents answer never, in both income categories. For those who made less than $75,000, the racial group with the highest percentage who responded, never, was white at 6.6%. In comparison, for those who made above $75,000, the racial group with the highest percentage who responded, never, was multiracial at 33.3%.

Next, I performed a Chi-square test (Chi-Square 1) to discover whether or not these relationships were significant. The results displayed that the findings below $75,000 were not statistically significant because the P-value was 0.6777, which is greater than the alpha level of 0.05. However, the results also showed that the findings for those who made above $75,000 were indeed, statistically significant. This was proven by the P-value being 0.011 which was less than the alpha level of 0.05. Therefore, the results for those who made over $75,000 were likely not due to random chance, but the results for those who made under $75,000 may have been.

After completing statistical tests for the variables in my first hypothesis, I moved on to those in my second hypothesis. I began by creating a bivariate table (Bivariate Table 2) focusing on the relationship between education and how important people find studying art or culture through classes or lessons. The group with the highest percentages in the category, very important, was those who had completed 1-11th grade at 17.9%. The group with the highest percentage in the category, somewhat important, was those with a postgraduate degree, at 23.8%. The group with the lowest percentage in the category, very important, was those who had attended some college at 9.5%. Additionally, the group with the lowest percentage in the category, somewhat important, was those who attended 1-11th grade at 12.5%. The group that had the highest percentage in the category, a little important, were those who attended 1-11th grade at 32.1%, and the group with the highest percentage in the category, not important at all, were high school graduates at 48.6%.

After generating the bivariate table, I conducted a Chi-square test (Chi-Square 2) to determine the significance of the two variables, education and how important people find studying art or culture through classes or lessons. The results determined that the relationship between these two variables was statistically significant, because the P-value was 0.000 which was less than the alpha value of 0.05. Therefore, these results were likely not due to random chance or an error in sampling.

discussion

This study proved interesting findings especially in regards to my original research hypotheses. The findings displayed that my first hypothesis, that there is a statistically significant relationship between race, class, and how often people can be creative, was only proven partially correct. A partial association exists because, when controlling for income, there was a statistically significant relationship between race and how often people were able to be creative, for those who made above $75,000. However, the relationship between race and how often people were able to creative, for those who made below $75,000 was not statistically significant. Therefore, the null hypothesis would be accepted for those who made below $75,000 and rejected for those who made above $75,000. It should also be noted that these findings may have limitations in regards to race, due to the lack of representation in all other non-white racial groups.

While controlling for income did not prove significant in both categories, what was interesting was that Black and Latino respondents were the most frequently creative in each income category. These findings may suggest implications for the value of creativity amongst racial groups, specifically in Black and Latino communities.

My second hypothesis, that education impacts how important people find studying art or culture through classes or lessons, was proven correct by my findings. Therefore, I reject the null hypothesis. Although, it should be noted that there may be limitations to these findings to due a lack of high representation of those who completed 1-11th grade and attended postgraduate school.

These findings suggest that higher education, and not completing high school, may increase one’s value of studying art or culture through lessons or classes. This is likely caused by the enhanced exposure to arts and culture classes in higher education, and the lack of this exposure, experienced by those who had not completed high school, causing higher value of this education. Furthermore, the findings which displayed the percentages of people who valued studying the arts or culture through classes or lessons overall were surprising. The majority of respondents did not find this education important at all (39.87%), and the second majority only found this education a little important (26.67%). Therefore, the benefits and value of arts or culture education need to be shared further.

Overall, these findings add to the breadth of growing literature pertaining to social factors, the arts, and arts education. However, these findings add to the literature by filling the gap through providing results in specific arts topics. These findings present new research that pertain to relationships between creativity, race, and class, and education and value of arts or culture education in adults.

references

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