The impact of age, math level, reading level, and socioeconomic status on net words a minute of selected Mississippi Eighth Grade Tech Prep Computer Discovery students.

摘要

Mississippi's Eighth Grade Tech Prep Computer Discovery students are to type 30 net words a minute (NWAM) at the end of the school year, yet many are not meeting this goal. The research question addressed by this study was: Is there a statistically significant relationship regarding student age, math level, reading level, and SES with regard to NWAM keyed on a three-minute straight-copy timed writing?;Pearson Correlation and multiple linear regression revealed correlations between NWAM and math level, (r = 0.34, SE = 0.68), NWAM and reading level (r = 0.25, SE = 0.69), and NWAM and SES (r = 0.29, SE = 0.47). Two-tailed significance levels indicated no significance between variables, although 95% confidence intervals indicated possible linear relationships regarding math level and SES on NWAM. The regression model did not fit the data of this study well (R = 0.382). Fourteen percent of the variability (R2 = 0.14) in students' NWAM was explained by age, math level, reading level, and SES, which was not enough on which to base predictions. The F ratio was 23.29 while the observed significance level was not less than 0.00005 (Signif F = 8.6409), meaning there were no statistically significant linear relationships between the variables. Power was not an issue.;Recommendations for practice were: (a) train non-business education teachers in methods of keyboarding instruction, (b) supplement keyboarding software with direct instruction, (c) spend majority of class time engaging students in hands-on keyboarding activities; provide extra time for students to master keyboarding, (d) provide concentration drills to improve keyboarding, (e) improve student spelling and reading skills in the elementary grades, and (f) give extra attention to students as keyboarding skills develop. Recommendations for further research were: (a) expand this research by focusing on teacher predictor variables, (b) expand this research by adding other student predictor variables, (c) expand this research to include a larger population of students, concentrating on only a few predictor variables, (d) replicate this study in a different school district from which this study originated using the same predictor variables, and (e) replicate this study in the school district from which this study originated using the same predictor variables.