Técnicas Invasivas en Pediatría 1 Técnicas de bloqueo regionales

Despite the student engagement subtypes, measurements of the subtypes are still debatable (Betts, Appleton, Reschly, Christenson, & Huebner, 2010). The SEI is a student self-report measure survey completed on paper to identify five subtypes of student engagement. The five subtypes include academic, behavioral, time on task,

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attendance, and homework completion (Appleton et al, 2006). The 4-point, 33-item scale addressed the five subtypes with .72-.92 reliability and Appleton et al. (2006)

demonstrate construct validity using a confirmatory factor analysis (Fredricks et al., 2011). The SEI instrument is primarily used with middle school and high school students in pubic K-12 education.

The Rochester Assessment Package for Schools- Student Self-Report (RAPS-S) is a single score measuring overall engagement based on 16 items. The RAPS is considered to be the most common measure of cognitive and emotional engagement (Fredricks, 2003). The RAPS is a diagnostic instrument to provide information about the current status of student engagement from both the teacher and student perspective. The RAPS-S is the most extensive of the measures and is a student self-report that references student engagement, student beliefs about school, student beliefs about self, and student

perceptions of interpersonal support with .68-.77 reliability (IRRE, 1998). The second measure is the RAPS-T and is a brief teacher measure identifying student engagement with .87 reliability (Fredricks et al., 2011). Significant positive correlations a reported on students’ scores on the engagement scale and academic achievement (Fredricks et al., 2011). Teachers assess student academic performance accurately, sometimes better than standardized measures (Banger-Downs & Pyke, 2002). In the RAPS-T, teachers identify levels of student engagement for each student in the classroom. Learning engagement has not only a cognitive component, but also a motivational one, and Banger-Downs and Pyke (2002) identify that teachers rate behavioral and cognitive engagement with

different success rates. By supplementing the RAPS-T with additional measures of student engagement, one will be better able to identify levels of engagement. Both of the

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instruments are available in forms for the elementary and middle school levels. No separate high school versions of the RAPS are available, but the middle school versions have been used successfully in high school evaluation projects (IRRE, 1998). The RAPS engagement scale has been administered to 200,000 students since 1997 (Murray, 2009).

Past research has focused on academic performance as an indicator of student engagement. Many items that measure student engagement and academic performance include quantitative, cognitive data. Indicators for academic performance and student engagement include the student’s grade point average (GPA), achievement test scores, and completion of homework (Jimerson et al., 2003). This information is compiled by teachers, such as local test data and homework completion. In addition, school records are utilized to identify GPA and standardized test scores on state examinations. Some studies use student self-reports for students to rate their own view of their academic performance (Jimerson et al., 2003).

Summary

Virtual world environments can provide opportunities in CMC for simulations, immersion, motivation and engagement. They provide a promise toward enhancing the curriculum and stimulating learners by providing enhanced communication capabilities, while offering anytime, anywhere learning. The virtual world provides a constructivist learning environment where one can engage with dialogue with others and construct knowledge. The element of social presence in the virtual world creates a meaningful environment where participants can engage in discourse (Bronack et al., 2006). CMC in virtual worlds provides learners the time to think of responses that may not be possible in the traditional FtF classroom. For the foreign language learner, CMC and virtual worlds

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allow for real-time target language practice without the disruption of the conversation (Meskill & Anthony, 2005). In an L2 classroom, virtual worlds can create an immersive environment where learners are engaged in the learning (Coffman & Klinger, 2007). Virtual worlds can create environments that are possibly as engaging as the FtF counterparts, while still providing time in CMC to practice language development (Csikszentmihalyi, 1990). Class discussions over a computer network can increase collaboration and discourse. The lack of nonverbal cues can be both a benefit and a challenge in online learning.

The U.S. Department of Education identified the lack of studies comparing online learning environments with FtF conditions for K-12 students (2010). Students using CMC tools learn just as much as their traditional counterparts (Lester & King, 2009). Past studies indicate student engagement in CMC, but they are primarily focused on post- secondary education. Student engagement is commonly referenced, but under researched (Harris, 2008) and the majority of research focuses on academic and behavioral

engagement (Appleton et al., 2006). Research on student engagement needs to analyze all three forms of student engagement: cognitive, emotional, and behavioral (Russell et al., 2005) in the K-12 classroom.

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CHAPTER III

METHODOLOGY

Introduction

The use of computer technology for foreign language learning is reported to increase one’s self-esteem, preparedness, language proficiency and overall academic success (Dunkel, 1990). Student self-esteem and overall academic success are linked to student engagement in school. One way to predict and improve academic achievement is to identify student engagement. Identifying the three areas of student engagement in school can assist in creating a positive learning environment where students experience increased opportunities for academic success. The purpose of this study was to evaluate student engagement in the high school foreign language classroom and determine if a virtual world learning environment impacts student engagement, under the

multidimensional constructs of emotional, cognitive, and behavioral criteria. This dissertation research examined the differences in student engagement between the virtual world and the traditional face-to-face learning environments in high school foreign language classrooms. One of the primary purposes of this study was to determine if there are differences in overall student engagement between learning in a virtual world setting versus a traditional face-to-face setting while learning a foreign language. Another purpose of this study was to determine if there are group differences in the multidimensional constructs of student engagement. Student engagement is identified as having emotional, cognitive, and behavioral components (Gambone, Klem, Moore, & Summers, 2002; Gambone, Klem, Summers, Akey, & Shipe, 2004; Klem & Connell, 2004; Murray, 2009).

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The first research question was: “When practicing conversational foreign language, are there differences in reported student engagement between in the virtual world and in the traditional face-to-face environments?” To answer this research question, high school foreign language classrooms participated in a quasi-experimental survey. Student engagement was measured using the Research Assessment Package for Schools (RAPS), student and teacher editions using a six-point interval scale. The independent variables were the virtual world and face-to-face settings. The dependent variable was student engagement, with the constructs of emotional, behavioral, and cognitive elements.

Since student engagement is a multidimensional construct, the next series of research questions compare group differences in the emotional, cognitive, and behavioral components of student engagement with the group environments of the virtual world and face-to-face setting. The second research question was: “Are there significant group differences of emotional engagement between the virtual world and the face-to-face environments while learning a foreign language?” In this question, the independent variables were the virtual world and face-to-face educational settings. The dependent variable was emotional engagement, with the covariates being cognitive and behavioral student engagement. To address the second research question, the same pre- and post- intervention survey data was used for analysis.

The third question was: “Are there significant group differences of cognitive engagement between the virtual world and face-to-face environments while learning a foreign language?” In this question, the independent variables were the virtual world and face-to-face educational settings. The dependent variable was cognitive engagement,

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with the covariates being emotional and behavioral student engagement. To address the third research question, the same pre- and post-intervention survey data was used for analysis.

The fourth question was: “Are there significant group differences of behavioral engagement between the virtual world and face-to-face environments when learning a foreign language?” In this question, the independent variables were the virtual world and face-to-face educational settings. The dependent variable was behavioral engagement, with the covariates being cognitive and emotional student engagement. To address the fourth research question, the RAPS-TM results were used. The survey results were used to identify behavioral components of student engagement.

SPSS Statistics Standard Version 20.0.0 will be used for data analysis. To answer question one, a MANOVA analysis was performed. To answer question two, an

ANCOVA analysis, controlling for the cognitive and behavioral covariates was performed. To answer question three, an ANCOVA analysis, controlling for the emotional and behavioral covariates was performed. To answer question four, a t-test analysis was used.