摘要：In this study, Structural Equation Modeling was used to determine the factors that affect reading skills. To determine the factors data of PISA 2009 was used. It assessed students’ capacities to apply knowledge and skills in reading, mathematical and scientific literacy. It describes some wider findings about what lies behind results. Structural Equation Modeling is examined and four independent latent variables as “reading attitudes,” “study habits,” “stimulate,” and “strategies the teacher used” are determined. It was observed that the most important variable was the “strategies the teacher used” (γ=0.33). The second important latent variable that affected the students’ reading comprehension skill was “teacher stimulating students”(γ=0.26). Another latent variable affecting the students’ reading comprehension level was observed as “the students’ study habits” (γ=0.22). The final latent variable was “attitude towards reading” (γ=0.16).
其他摘要：In this study, Structural Equation Modeling was used to determine the factors that affect reading skills. To determine the factors data of PISA 2009 was used. It assessed students’ capacities to apply knowledge and skills in reading, mathematical and scientific literacy. It describes some wider findings about what lies behind results. Structural Equation Modeling is examined and four independent latent variables as “reading attitudes,” “study habits,” “stimulate,” and “strategies the teacher used” are determined. It was observed that the most important variable was the “strategies the teacher used” (γ=0.33). The second important latent variable that affected the students’ reading comprehension skill was “teacher stimulating students”(γ=0.26). Another latent variable affecting the students’ reading comprehension level was observed as “the students’ study habits” (γ=0.22). The final latent variable was “attitude towards reading” (γ=0.16)
