computing the mean scores to the questions It is made clear to stud ents that

Computing the mean scores to the questions it is made

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computing the mean scores to the questions “It is made clear to stud ents that the inappropriate use of technology will not be tolerated by school administration” and “Our school has a clear policy regarding cell phones and other portable electronic devices.” The seventh and final dependent variable, which was titled “school climate”, was created by computing the mean scores to the questions “We work to create a climate in which cyberbullying is not considered „cool‟ among the student population” and “We take actual and suspected incidents of cyberbullying seriously.” Quantitative Results A series of independent sample t- tests were run using the question “Is your cyberbullying policy effective?” as the independent variable. Of the respondents who answered the question “Is your cyberbullying policy effective?”, 33 (71.7 %) indicated that their cyberbullying policies were effective while only 13 (28.3%) indicated that their cyberbullying policies were not effective. Seven variables described above were employed as the dependent variable: knowledge and prevalence; student education; parent communication; teacher involvement; anonymous reporting system; technology policy; and school climate. The results of the t-tests are displayed in Table 8. The first t-test, employing “knowledge and prevalence” as the dependent variabl e, revealed that there was not a significant difference between those who answered “yes” to indicate that their cyberbullying policy was effective( M = 2.48, SD = 1.00) than people who answered “no” ( M = 2.31, SD = 1.16), t (44) = .52, p = .61. When “student education” was employed as
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79 the dependent variable, a significant difference was noted between those individuals who answered “yes” to indicate that their cyberbullying policy was effective ( M = 4.33, SD = .186) than those who answered “no” ( M = 3.54, SD = .256), t (44) = 11.69, p <.001. When “parent communication” was employed as the dependent variable, again a significant difference was noted between those individuals who answered “yes” to indicate that their cyberbullying policies were effective ( M = 4.09, SD = .605) than those who answered “no” ( M = 3.54, SD = .852), t (44) = 2.47, p = .017. When teacher involvement was employed as the dependent variable, it was revealed that there was not a significant difference between those who answered “yes” tha t their policy was effective ( M = 3.68, SD = .635) than people who answered “no” ( M = 3.31, SD = 1.09), t (44) = 1.45, p = .153. The fifth t- test, which employed “anonymous reporting system” as the dependent variable, also failed to reveal a significant difference between those who answered “yes” that their policy was effective ( M = 3.72, SD = 1.33) than people who answered “no” ( M = 3.46, SD = 1.51), t (44) = .588, p = .559. When “technology policy” was employed as the dependent variable, again, there was not a significant difference between those who answered “yes” that their policy was effective ( M = 4.73, SD = .309) than those who answered “no” ( M = 4.50, SD = .577), t (44) = 1.62, p = .112. The seventh and final t- test, which employed “school climate” a s the dependent variable, did find a significant difference between those who answered “yes” that their policy was effective ( M = 4.48, SD = .405) and those who answered “no” ( M = 4.12, SD = .506), t (44) = 2.60, p = .013.
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