Over View of the chosen Article

The selected journal article is “An Analysis of Middle School Students Physical Education  physical Activity Preferences” by Hill, G., and Hannon, J. C. (2008). The objective of the study was to establish whether there existed any relationship between sports activity choices of middle school students and their gender, skill level, or out of school sports participation. The study target population was middle school students who were signed up for physical activity classes. Chi-square statistical tool was used as the tool of analysis in the research study.

Research Question for the Study

The research question for the study was: “Is there a relationship between sports activity choices of middle school students and their gender, skill level, and out of school sports participation?”

The specific objectives of the study was to determine which physical education activities middle school students like to have included in the yearly curriculum and if there were any differences in responses based on gender, student motor skill competency, grade level, and participation in physical activities outside of  regular school hours.

Hypotheses

The null hypothesis for a chi-square test states that the relative proportions of one variable are independent of the second variable. That is, the proportions at one variable are the same for different values of the second variable. Following are the statistical notations of the null hypothesis and alternative hypothesis;

H₀: µ_(x) = µ_(y)

H₁: µ_(x) ≠ µ_(y)

The null hypothesis supposes no significant relationships exists between the sports activity choices of middle school students and the variables of gender, skill level, and out of school sports participation, while the alternative hypothesis supposes that significant relationships exists between the sports activity choices of middle school students and the variables of gender, skill level, and out of school sports participation. However, it is worth noting that when using a chi-square statistical test, a rejection of the null hypothesis does not necessarily mean an acceptance of the alternative hypothesis. This forms one of the key limitations of the chi-square test.

Methodsand study design

The target populations of the study were students enrolled in physical education at two public middle schools, each with a population of approximately 750 students and located in the southwestern United States. The ethnic populations in the two schools were similar to the district averages: Caucasian- 74%, Hispanic-15%, African American-5%, Asian/pacific islander-5%, American Indian- 4%, other-7%.The study sample population was 881 students, 430 from one school and 451 from the other school. Among classes selected to participate, over 97% of those students completed surveys.

The method used was survey where the participants were required to complete a survey that included: a demographic section that required the biographical information of the student including age, grade level, gender, level of involvement in after school sports; a list of activities pertinent to middle school physical education; and two additional lines so that students could have the option of writing additional activities of interest. The format of the survey was adopted from surveys by Hill and Cleven (2005). The construct validity of the survey was checked by three middle school physical education teachers and three university professors. Internal validity was controlled by using the layout and design suggested by Dillman (2000). The survey was administered by two teachers each from the two middle schools who were directed to emphasize to the students the importance providing honest and candid responses. The teachers later ranked the students according to their motor skill competency.

The variables of the study were the different sports activities available on one hand and the differential characteristics of the student on the other hand. The different sports activities are nominal variables, and so are the student’s differential characteristics such as gender, skill level, grade level and out of school participation. Both of these variables are categorical or nominal variables since they can take two or more categories which have no intrinsic ordering. This characteristic of the variables makes them appropriate for the use of a Chi-square statistical analysis.

Data Analysis

Statistical analysis for all data in the study was conducted using SPSS; however, the data was first entered into an Excel spread sheet. Frequencies and percentages were generated to describe the data both by group and gender. In addition, chi-square analysis was used to determine if significant relationships existed between the curricular choices of respondents and the selected variables of gender, skill level, and out of school sports participation.

The demographics of the study population were as follows:  of the 881 completed surveys, 55.7% were filled out by boys and 44.2% by girls, with one survey with no gender. Frequencies for grade levels were: 7^th grade, N=315; 8^th grade, N=267; and 9^th grade, N=297. 53% of the students indicated that they participate in a sport outside school hours.

With respect to activity preferences and preferences by school, chi-square analysis revealed a significant main effect for nine activities when responses were compared between students of the two schools. Significantly higher percentages of students in the school with mixed gender classes selected bowling (69.5% vs. 57.0%, p< .000), swimming 65.1% vs. 53.4%, p<.000), archery (65.1% vs. 49.4%, p<.000), skating (61.9% vs. 46.8%, p<.000), table tennis (60.2% vs. 48.3%, p<.000), volleyball ( 56.3% vs. 47.7%, p< .010), canoeing ( 54.7% vs. 39.2%, p<.000), water polo ( 44.9% vs.29.9%, p< .000), and walking (38.4% vs. 26.6% p<.000). Activities selected by at least half of the respondents from the two schools were: basket ball 67.4%, football 63.7%, bowling 63.1%, swimming 59.1%, table tennis 54.1%, skating 54.1% and volleyball 51.9%.

With respect to activity preference by gender, a majority of boys selected football, basket ball, bowling, table tennis, swimming, hockey and fencing, while a majority of girls selected swimming, skating, volleyball, bowling, basketball, gymnastics, soccer, softball, football, canoeing and yoga. Twenty-one activities revealed a significant chi-square value when responses were compared by gender. Of those activities, eight revealed a preference by more than half of one gender and less than half by the other gender.

When it comes to activity preference by skill level, nine activities revealed a significant chi-square value when responses were compared by skill level. Of these activities, four were preferred by a majority of those in the highest skill level and by less than a majority of those in the lowest skill level. The four activities were: soccer (high=62.2%, middle=53.7%, low=41.6%, p<.000), softball (high=59.8%, middle=45.5%, low=41.2%, p<.000), weight training (high=53.3%, middle=43.7%, low=35.1%, p<.000) and football (high=78.7%, middle=66.2%, low=44.1%, p<.000)

With regards to activity preference by grade level, a comparison of responses based on grade level,higher percentage of 7^th graders than 9^th graders indicated interest in 28 out of the 33 activities listed. For eleven of these activities there was a significant chi-square value. Of the eleven activities, six were preferred by a majority of 9^th graders.

An additional chi-square analysis conducted separately comparing male and female responses at each grade level.For males, significant declines in percentages were noted from 7^th to 9^th grade in activities such as archery (7^th= 73.3%, 8^th=56.7%, 9^th =59.1%, p<.006), fencing(7^th= 62.3%, 8^th=43.3%, 9^th =43.9%, p<.001),swimming(7^th=  60.6%, 8^th=54.0%, 9^th =40.9%, p<.001), walking(7^th= 34.9%, 8^th=54.0%, 9^th =40.9%, p<.001), canoeing(7^th= 54.3%, 8^th=36.7%, 9^th =36.6%, p<.002),  hockey (7^th= 60.6%, 8^th=56.7%, 9^th =37.2%, p<.000), skating (7^th= 50.9%, 8^th=47.3%, 9^th =29.9%, p<.001), and water polo(7^th= 40.6%, 8^th=38.7%, 9^th =22.6%, p<.001). For females, significant declines in percentages from 7^th grade to 9^th grade were found in gymnastics(7^th= 68.6%, 8^th=65.8%, 9^th =40.9%, p<.001) and swimming(7^th= 81.4%, 8^th=73.5%, 9^th =50.8%, p<.000).

Analysis based on activity preference by additional sport participation, 12 activities revealed a significant chi-square value when responses were compared by the variable of additional sport participation. Of these activities, four were preferred by a majority of those who reported additional sport participation and less than a majority of students who report no additional activity participation. These activities were weight training (Additional sport participation=50.2%, no additional sport participation=37.1%, p< .000), canoeing (Additional sport participation=53.0%, no additional sport participation=39.6%, p< .000), soccer (Additional sport participation=57.1%, no additional sport participation=48.1%, p< .010), softball (Additional sport participation=52.8%, no additional sport participation=43.4%, p< .010),

In brief, of the 33 activities that were included, the chi-square analysis revealed significant  differences for 21 activities by gender, 10 activities by skill level, 11 activities by grade, and 12 activities by after school sport/ activity participation. The participants wrote in an additional 30 activities not included on the survey checklist. Therefore, the research study rejects the null hypothesis that supposed no significant relationships exist between the curricular choices of middle school students and the variables of gender, skill level, and out of school sports participation.

Critique

A key limitation of the study was that the two schools offered several sports activities that were not included in the survey, this overlooking creates a major source for wrong inference, and despite the inclusion of a space for the students to write additional activities, it will not bring the validity that would have been associated with the inclusion of these additional activities.

Another weakness of the study stems from its use of the chi-square. Although this tool deals with the statistical significance of observed cell frequencies, it does not provide any indication of the degree or strength of association among contents of the cells. For example, in this study it revealed that there are significant differences between middle school males and females activity selection, however, the strength of association between activity choice and gender was not ascertained. Therefore, there arises a need for a nonparametric correlation coefficientto describe the degree of association between variables in the contingency table.Additionally, while chi-square is invaluable when determining whether two variables are significantly related, it does not address whether the relationship is meaningful or what the nature of the relation might be. As a result, it is generally considered more of a starting point than an end to itself.

In addition, the use of chi-square is heavily affected by sample size. One requirement of chi-square is that it has to have a fairly large N, otherwise it is not reliable as a test of independence. If the N is much large than what is required for the accurate results, however, it quickly reached a point that almost any difference between the variables will show up as significant. In the context of the research study, the findings cannot be ascertained to be a true reflection of the relationship between the variables, or just an extension of influences impacted by the inappropriateness of the sample size.

Finally, when using a chi-square, the alternative hypothesis is not supported by a rejection of the null hypothesis. Just because the null hypothesis is rejected does not mean that there is no relationship between the variables.

Summary

In brief, of the 33 activities that were included, the chi-square analysis revealed significant  differences for 21 activities by gender, 10 activities by skill level, 11 activities by grade, and 12 activities by after school sport/ activity participation. The participants wrote in an additional 30 activities not included on the survey checklist. Therefore, the research study rejects the null hypothesis that supposed no significant relationships exist between the curricular choices of middle school students and the variables of gender, skill level, and out of school sports participation.

The results of this research study demonstrate the importance of considering multiple factors including gender, skill, grade, and after school sport/activity participation when making decisions on curricular offerings for middle school physical education.

Conclusion

The objective of the study was to establish whether there existed any relationship between sports activity choices of middle school students and their gender, skill level, or out of school sports participation. It revealed no significant relationships exist between the sports activity choices of middle school students and the variables of gender, skill level, and out of school sports participation. These findings inform middle school physical educators that they can now consider ways to ensure their yearly curriculums are not gender biased. Yearly surveys can be employed to solicit student’spreferences of activities as an effective way to match student interest with curriculum offerings for both male and female students.

References

Hill, G., & Hannon, J. C. (2008). An Analysis of Middle School Students Physical Education physical Activity Preferences. Physical Educator, 65(4), 180-194.

 
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