Date

2017-08-25

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Yerdelen, Sündüs
Sungur, Semra

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Contribution Social Cognitive Theory suggests that human functioning can be explained in terms of the reciprocal interactions between personal, behavioral, and environmental factors (Bandura, 1986). Among these factors, classroom learning environment is reported to have important role in students’ academic achievement (Fraser & Walberg, 1991, Walberg, 1981). Therefore, investigating the features of learning environment that positively affects students’ learning outcomes is crucial for improving instructional quality, and reaching educational goals. Actually, studies on learning environment have been remarkably accelerated after 1960’s by the development of several measures of classroom learning environment. Most recently, Fraser, Fisher, and McRobbie (1996) developed WIHIC questionnaire by including subscales which had been frequently found associated with student’s learning outcomes, WIHIC also prepared by considering contemporary cognitive approach to science learning (Kim, Fisher, & Fraser, 2000). WIHIC questionnaire includes 7 dimensions: (1) Student Cohesiveness, emphasizing the student-student interaction in terms of how friendly, helpful, and supportive they are to each other, (2) Teacher Support, concerning how helpful, friendly, and supportive teachers are to their students, (3) Involvement, emphasizing the extent to which students have attentive interest, participate in classroom activities, and enjoy the class, (4) Investigation, focusing on the skills and inquiry and to the extent that students use them in problem solving and investigation, (5) Task Orientation, involving whether students accomplish the given tasks and planned activities, and focus on the works they were expected to do, (6) Cooperation, emphasizing the students cooperation with each other while doing classroom activities, and (7) Equity, concerning whether teachers treat students equally in terms of feedback, praise, asking questions, and opportunities (Waldrip, Fisher & Dorman, 2009). According to Waldrip et al. (2009) using WIHIC when examining learning environments is beneficial for predicting student outcomes. According to relevant literature, another important factor influencing student achievement appears to be teacher effectiveness (Bolyard & Moyer-Packenham, 2008). Teacher effectiveness research considers several characteristics of teachers and suggests that teachers may influence students learning processes by several ways (Patrick & Smart, 1998). In the current study teacher effectiveness was examined in terms of teacher beliefs and occupational well-being. Regarding teacher beliefs, this study focused on teachers’ self-efficacy beliefs (Tschannen-Moran & Woolfolk Hoy, 2001) and implicit beliefs about intelligence (Dweck, 1999). Occupational well-being, on the other hand, was investigated in terms of job satisfaction, emotional exhaustion, and personal accomplishment. Although some researchers suggested that teachers’ occupational well-being, self-efficacy beliefs, and implicit beliefs about intelligence have substantial effect on students’ learning processes and classroom learning environment, these variables are rarely studied empirically. Moreover, although there are several studies that examined the relationship between classroom learning environment and student outcomes (e.g., den Brok, Telli, Cakiroglu, Taconis, & Tekkaya, 2010; Chionh & Fraser, 1998; Snyder, 2005; Wolf & Fraser, 2008), little is known about the influence of teacher beliefs and occupational well-being on these variables and these associations. As well as overmentioned teacher variables, teachers’ gender and experience will also be considered while examining the relationship between learning environment and science achievement. Thus, the present study is expected to extend the information about the variables that influence middle school students’ science learning. Accordingly the main research question guided to this study is that: To what extent do perceived classroom learning environment and teacher effectiveness (i.e., occupational well-being, beliefs, experience, and gender) predict students’ science achievement? Method In the present study, correlational survey method was used. A nationally representative teacher and student sample was selected by using two stage random selection method. Each school which includes a science teacher and one of the 7th grade classrooms’ students of that teacher received questionnaires by mail. Valid data were obtained from 372 middle school science teachers and their 8198 seventh grade students. Student questionnaires included What is Happening in This Class (WIHIC) questionnaire (Fraser, Fisher, & McRobbie, 1996). WIHIC includes 56 items and 7 subscales: Student Cohesiveness, Teacher Support, Involvement, Investigation, Task Orientation, Cooperation, and Equity; and each subscale include 8 items. Cranbach’s alpha coefficients of all subscales were ranged between .78 and .88, which shows that internal consistency of responses are high enough. Results of the confirmatory factor analyses also indicated good model fit to the data. Moreover, students’ science achievement was assessed by using 14-item multiple choice Science Achievement Test developed by the researchers. The reliability coefficient (KR 20) was found to be 0.78. Furthermore, Teacher questionnaire included Teachers’ Sense of Self efficacy Scale (TSES) (Tschannen-Moran & Hoy, 2001) which consisted of 12-item 3 subscales: Efficacy for Student Engagement, Efficacy for Instructional Strategies, and Efficacy for Classroom Management. Teachers’ job satisfaction and burnout were measured by using 3-item Teacher Job Satisfaction Scale (Skaalvik & Skaalvik, 2010) and 2 subscales of Maslach Burnout Inventory (MBI) (Maslach & Jackson, 1981), respectively. Teachers’ beliefs about students’ ability in science was measured by using 3-item Implicit Theory of Science Ability Scale [adapted from Dweck and Henderson’s (1989) Implicit Theories of Intelligence scale]. Cranbach’s alpha for these scales were ranged between .76 and .87. Confirmatory factor analyses result revealed god model fit for each scale. Hierarchical Linear Modeling HLM was used to analyze the data, since the obtained data were in hierarchical structure which was nested within classes. Therefore, the similarities of the responses to the scales of the students in the same classrooms would not be ignored and more plausible results would be obtained by this way. Expected Outcomes Based on the results of the null model, IntraClass Correlation Coefficient (ICC) for Science Achievement was found to be .295. In other words, in seventh grade classrooms, about 30 percent of the variance in Science Achievement was explained by the differences between classrooms. On the other hand, approximately 70 percent of the variance in Science Achievement was attributable to the differences among students in the same classroom. Namely, this high level distinction among classes suggested using HLM analysis to determine class-level variables influencing science achievement. Then, student-level and class-level variables were included in the model subsequently. Results of the intercepts and slopes as outcomes model showed that among the class level variables, teachers’ Experience (γ = .069, p < .05), Efficacy for Student Engagement (γ = .095, p < .01), and Implicit Theory of Science Ability (γ = .064, p < .05) were significantly predicted students science achievement. Namely, students tended to get higher scores from science test in the classroom thought by science teachers who were more experienced, more confident in student engagement in science class, or hold the belief that people’s ability in science can be improved. Moreover, Involvement (γ = .135, p < .001), and Task Orientation (γ = .192, p < .001), were significantly and positively associated with Science Achievement. However, Investigation (γ = -.031, p < .05) and Cooperation (γ = -.065, p < .001) was found as negatively related to Science Achievement. Results also yielded a cross-level interaction between student and class level predictors of Science Achievement. Teacher’s Gender (γ=.060, p < .01) was significantly associated with the Equity slope coefficient. In other words, Teacher’s gender moderated the effect of Equity on Science Achievement. We can conclude that students’ perception on classroom learning environment is a good predictor of science achievement and teachers have an influence on their achievement too.

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http://www.eera-ecer.de/ecer-programmes/conference/22/contribution/41238/
https://hdl.handle.net/11511/71106

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Department of Secondary Science and Mathematics Education, Conference / Seminar