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Predictors of self-regulated learning in Malaysian smart schools


Ng Lee Yen 
School of Educational Studies, University of Science Malaysia
nglyen@yahoo.com

Kamariah Abu Bakar 
Faculty of Education, Universiti Putra Malaysia 

Samsilah Roslan 
Faculty of Education, Universiti Putra Malaysia 

Wong Su Luan 
Faculty of Education, Universiti Putra Malaysia 

Petri Zabariah Megat Abd Rahman
Faculty of Education, Universiti Putra Malaysia

 

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Abstract

This study sought to uncover the predictors of self-regulated learning in Malaysian smart schools. The sample consisted of 409 students, from six randomly chosen smart schools. A quantitative correlational research design was employed and the data were collected through survey method. Six factors were examined in relation to the predictors of self-regulated learning. These factors were levels of IT-integration, student-teacher interactions, motivational beliefs, self-regulative knowledge, information literacy, and attitudes towards IT. Multiple regression analysis showed that levels of IT-integration, student-teacher interactions, motivational beliefs, and self-regulative knowledge significantly predict self-regulated learning in Malaysian smart schools. 

Self-regulated learning, smart schools, levels of IT-integration, motivational beliefs, student-teacher interactions

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 Ng, L.Y., Kamariah, A.B., Samsilah, R., Wong, S.L. and Petri, Z. (2005) Predictors of self-regulated learning in Malaysian smart schools. International Education Journal, 6 (3), 343-353.
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