to students becoming independent spellers at their own levels. The interwoven nature between spelling, reading, and writing benefited the students. When Thames and studied the effects of an individualized, integrated language arts approach on the attitudes of struggling readers (as cited in Argo, 1995), student attitudes became increasingly positive. When students become increasingly excited to learn, additional achievement takes place. Connecting the various aspects of reading and writing in a classroom can make a significant impact on student success. Assessment Score Comparisons Thames, Reeves, Kazelskis, York, Newell, and Wang (2008) conducted a study that examined the impact of low readers’ comprehension scores when taught in an integrated language arts setting. The students in this study were from grades four through eight, and all students read at a lower level for their grade. The treatment group consisted of 51 students who received the integrated language arts strategies. In contrast, the comparison group consisted of 42 students who received basal reading instruction throughout the study. A pre-test and post-test were given to both groups of students in this study. A multivariate analysis of covariance was used to interpret the Analytical Reading Inventory comprehension scores. The vast majority of the statistically significant differences were found in the treatment group of this study. The results of this particular study strongly suggest that using an individualized, integrated language arts approach will benefit students with lower reading levels (Thames et al., 2008). In 2003, Donahue, Daane, and Grigg (as cited in Stevens, 2006) the National Assessment of Educational Progress reading report stated that the literacy skills in
Instructional Plan Validity: Content FQ2 How do student assessment scores compare when literature and language arts are taught together as opposed to when they are taught separately? Student Outcome Thames, Reeves, Kazelskis, York, Charlotte, Newell, and Wang (2008) Argo (1995) Stevens (2006) Type of Method: Standardized: Mock CRCT Type of Data: Interval Type of Validity: Content Dependent t Independent t Effect Size To determine if there are significant differences between means from two groups To measure the magnitude of a treatment effect FQ3 What are the teacher and student attitudes when language arts and literature are taught together? Self reflection and student affect Keating-Toro (1998) Smith (2003) Wixon (1986) Type of Method: reflective journal surveys Type of Data: Qualitative Type of Validity: Construct Coded for themes: Recurring Dominant Emerging Looking for categorical and repeating data that form patterns of behaviors Research Design This study was in accordance with the action research design. McKay (1992) described action research as a cyclical process, which included six different steps. The first step involved identifying the particular issue in which to study. In the second step, the researcher gathered and reviewed information that relates to the topic. In steps three through five, the researcher developed the plan of action, implemented the plan, and then evaluated the results. In step six, the cycle can be repeated as many times as necessary
Hypothesized Mean Difference 0 df 69 t Stat 1.984033815 P(T<=t) one-tail 0.025615718 t Critical one-tail 1.667238549 P(T<=t) two-tail 0.051231435 t Critical two-tail 1.99494539 T(69) = 1.98, P < .05. In Table 4.9, we see that the mean is higher for the girls than for the boys. The obtained value is greater than the critical value in this test, so we reject the null. This independent t-test has significance. In Table 4.10, an independent t-test is performed to examine the post-test differences between the girls and the boys in literature. Table 4.10 t-Test: Two-Sample Assuming Unequal Variances GIRLS BOYS Post Test - Lit Post Test - Lit Mean 29.43333333 25.14634146 Variance 27.01264368 60.32804878 Observations 30 41 Hypothesized Mean Difference 0 df 69 t Stat 2.783621707 P(T<=t) one-tail 0.003465077 t Critical one-tail 1.667238549 P(T<=t) two-tail 0.006930154 t Critical two-tail 1.99494539 T(69) = 2.78, P < .05. In Table 4.10, the mean is higher for the girls than for the boys. The obtained value is higher than the critical value, and this independent t-test has significance. We
must reject the null. The effect size is 0.65, which is large. In Tables 4.11 through 4.14, we examine the scores from the regular education students and the special education students. Table 4.11 displays a dependent t-test for the pre-test and post-test in language arts for regular education students. Table 4.11 t-Test: Paired Two Sample for Means ES = 0.125 REGULAR EDUCATION Pre Test - LA Post Test - LA Mean 33.25490196 34.78431373 Variance 39.35372549 33.93254902 Observations 51 51 Pearson Correlation 0.748604911 Hypothesized Mean Difference 0 df 50 t Stat P(T<=t) one-tail 0.007222908 t Critical one-tail 1.675905026 P(T<=t) two-tail 0.014445815 t Critical two-tail 2.008559072 T(50) = 2.53, P < .05. In Table 4.11, the obtained value is greater than the critical value. There is significance for the regular education students’ outcome in language arts, and we must reject the null. The effect size is -0.125, which is small. Table 4.12 examines the pre-test and post-test in literature for regular education students. Table 4.12 t-Test: Paired Two Sample for Means REGULAR EDUCATION Pre Test - Lit Post Test - Lit Mean 26.60784314 28.52941176 Variance 30.00313725 30.65411765 Observations 51 51 Pearson Correlation 0.802316759 Hypothesized Mean Difference 0