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Context-based learning environments are being developed in various countries to renew science education and create new vital learning environments to fulfil the diverse needs of students, society and science (Osborne & Dillon, 2008; see also Chapters 2 and 12). Fensham (2009) observes an increasing interest in contextbased science education from a large number of recent publications (De Jong, 2015; Meijer, Bulte, & Pilot, 2013; Millar, 2007; Roehrig, Kruse, & Kern, 2007; Sevian & Bulte, 2015; Sevian & Talanquer, 2014; Sjöström & Talanquer, 2014; Tytler, 2007).

Context-based approaches in science education, such as context-based chemistry or physics are gaining ground. For example, in The Netherlands new context-based curricula have been developed for the natural sciences,1 which will be implemented in the years to come (SLO, 2010). However, in order to create effective contextbased education, teachers will need to change the classroom culture, the social norms and forms of interaction that shape classroom practice (Cobb & Yackel, 1998).

Over the years, researchers have developed statistical methods to help them investigate and interpret issues of interest in many discipline areas. These methods range from descriptive to inferential to multivariate statistics. As the psychometrics measures in education become more complex, vigorous and robust methods were needed in order to represent research data efficiently.

One of the main characteristic of democratic society is political participation. In order to insure its existence, a democratic society is demanded to grant its future citizens an experience in the democratic arena (Dewey, 1916/1944). This participation is not obviously guaranteed, and there is a need in persistent education system aiming at developing the role of democratic citizen among the young generation. This need is even more essential in recent years, due to decreasing political participation of adolescents. This trend includes a significant decrease of willingness to vote and to belong to a political party (Bennett, 1998).

A key component of the research program focused on the development of two instruments: one to assess students’ perceptions of the learning environment and another to assess their attitudes and academic self-efficacy beliefs.

The purpose of this study was to investigate the relation between constructivist learning environment and students'motivation to learn science by testing whether students' self-efficacy in learning science, intrinsically and extrinsically motivated science learning increase and students' anxiety about science assessment decreases when more opportunities for personal relevance, student negotiation, shared control,critical voice, and uncertainty for scientific knowledge is provided. Constructivist Learning Environment Survey and Science Motivation Questionnaire were administered to 243 elementary school students. The hypothesized model for students' motivation to learn science in their perceived learning environment was tested via LISREL. The results revealed that the students were negatively motivated to learn science in more constructivist learning environment. On the other hand, the findings indicated that the students were more motivated to learn science when they had more opportunities in relating science with the real world issues. Therefore, science educators should emphasize more on the connectedness of science at school to real life for motivating students to learn science.