TPC-Journal-V5-Issue3

The Professional Counselor /Volume 5, Issue 3 345 internal consistency. Recent evaluation of the PRQ’s psychometric properties by Tabaeian, Amiri, and Molavi (2012) supported it as a highly reliable and valid instrument that should continue to be used in research. Student Engagement in School Success Skills Survey . The SESSS is a 33-item student self-report of cognitive engagement in SSS program skills and strategies, using language specific to the SSS curriculum, and takes approximately 15 minutes to complete (Carey, Brigman, Webb, Villares, & Harrington, 2013). Students are asked to circle how often they have engaged in a list of behaviors within the last 2 weeks (e.g., “I tried to encourage a classmate who was having a hard time doing something,” “I noticed when another student was having a bad day,” “I listened to music so that I would feel less stressed”). Possible responses include I didn’t do this at all , I did this once , I did this two times or I did this three or more times . The SESSS is intended for use with students in grades 3–12. Though a four-factor model was first revealed in an exploratory factor analysis conducted by Carey et al. (2013), a subsequent confirmatory factor analysis revealed the following three factors: self- direction of learning (which represents the combination of two original factors—management of learning and application of learning strategies), support of classmates’ learning and self-regulation of arousal, which correspond to the three subscales of the SESSS (Brigman et al., 2014). Coefficient alphas for the three SESSS subscales were as follows: self-direction of learning: 0.89, support of classmates’ learning: 0.79 self-regulation of arousal: 0.68, and 0.90 for the SESSS as a whole (Villares et al., 2014), indicating good internal consistency. My Class Inventory-Short Form-Revised . The MCI-SFR is a 20-item instrument that intends to measure the perceptions of students in grades 4–6 of four areas related to classroom climate (satisfaction, friction, competitiveness and cohesiveness). The instrument takes approximately 10–15 minutes to complete and respondents are asked to select either “yes” (3 points) or “no” (1 point). Omitted or invalidly scored items receive two points. Reports on the psychometric properties for both the MCI-SF and MCI-SFR have indicated strong concurrent validity when comparing long and short versions across each of the scales (.91–.97). Additionally, some degree of internal consistency (largely adequate coefficient alphas) has been reported for class means with Australian children (.58–.81). The MCI-SF yielded more acceptable alpha coefficients for each of the scales (.84–.93) than did the long version, the MCI. Modifications to the revised MCI-SFR produced a better overall instrument, improving factor interpretability and reliability (Fraser, 1982; Sink & Spencer, 2005). Sink and Spencer (2005) reported that interpreting students’ responses from pretest to posttest on the MCI-SFR should be straightforward, with higher scores on the satisfaction and cohesion scales providing positive indicators of a healthy classroom environment, and higher scores on the competitiveness and friction scales suggesting needed improvement in this area. Data Analysis Individual students were the units of analysis in the study. An alpha level of . 05 and one-way analysis of variance (ANOVA) tests were used to analyze differences in prosocial behaviors, bullying behaviors, school engagement skills and perceptions of classroom climate between students who participated in the SSS program (treatment group) and students who did not (comparison group). A post hoc Bonferroni correction was used to lessen the chance of a Type I error. Prior to the analyses, all the variables of interest were examined for accuracy of data entry, missing values, outliers and the normality of distributions. In addition, effect sizes (ES) were calculated to determine the practical significance of the SSS classroom program for the various student outcomes. In this study, a partial eta-squared (ES; h p 2 ) calculation was computed by SPSS (Field, 2009; Howell, 2008; Sink & Mvududu, 2010). The ES addresses the magnitude of the difference between