Abstract

Trends in International Mathematics and Science Study (TIMSS) provides unique and detailed information to explore the competencies and attitudes of fourth and eighth-grade students worldwide. The "Environmental Awareness Scale" was developed for the first time in the TIMSS 2019 cycle to measure students' environmental awareness. This cognitive scale gives essential information on students' scientific understanding of some environmental problems at the national and international levels. Using this scale to assess students' environmental awareness will improve education for sustainable development (ESD) in this setting since the obtained data provide reliable information that education policymakers use to integrate the most important environmental education topics and concepts into their curricula and identify the factors that should be considered to raise students' environmental awareness. This study aims to investigate to what extent the science self-concept variable from science-related factors, as well as the gender and socioeconomic status (SES) variables from demographic characteristics, predict the environmental awareness of eighth-grade students in Türkiye participating in the TIMSS 2019. For this purpose, a theoretical model was developed and analyzed with Structural Equation Modeling (SEM) to investigate the association between students' environmental awareness and science self-concept, gender, and SES. The analysis revealed that science self-concept, SES, and gender variables together explained 36% of students' environmental awareness. Furthermore, while science self-concept appears to be the strongest predictor of students' environmental awareness, SES level was also a significant variable explaining students' environmental awareness. On the other hand, there was no significant difference in environmental awareness between male and female students. The study's findings are discussed based on the United Nations Educational, Scientific and Cultural Organization (UNESCO)'s emphasis on the periodic monitoring and evaluation of progress in implementing ESD based on data.

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