Abstract:

The aim of this study is to examine the predictive power of planning, monitoring, evaluation and affective strategies, applied by preservice teachers in a metacognitive level, to predict academic success. The examined group is a collection of 106 second-year students in Department of Primary School Teacher Education in Faculty of Education in Uşak University. The descriptive texture of the study is constructed on relational scanning model and Metacognitive Learning Strategies Determining Scale is used as the data collection tool. The study utilizes arithmetic mean, standard deviation in order to identify the metacognitive learning strategies practiced by preservice teachers, and applies Pearson Moment product-moment correlation analysis to determine the probable linearity between metacognitive learning strategies and success, and finally uses Multiple Regression Analysis Techniques to analyze the power of these metacognitive strategies to predict success. Research results indicate that the preservice teachers use planning, monitoring and affective strategies more and the evaluation strategies lesser. The results over the predictive power of the used strategies by preservice teachers to predict their success show that only the evaluative strategies displayed a meaningful relation to academic success which explained the 8 % of the total variance. 

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