Self-regulated learning as predictor of academic performance

Keyser, J.N.; Viljoen, M.C.

dc.contributor.author	Keyser, J.N.
dc.contributor.author	Viljoen, M.C.
dc.contributor.other	Central University of Technology, Free State, Bloemfontein: Journal for New Generation Sciences
dc.date.accessioned	2016-06-03T13:23:24Z
dc.date.available	2016-06-03T13:23:24Z
dc.date.issued	2015
dc.date.issued	2015
dc.identifier.issn	16844998
dc.identifier.uri	http://hdl.handle.net/11462/800
dc.description	Published Article	en_US
dc.description.abstract	The goal of this study was to research the hypothesis that self-regulated learning (SRL) predicts academic performance in second-year Economics studies. In the theoretical underpinning, self-regulated learning as related to academic performance was explored. Data was analysed using descriptive, correlation analysis and hierarchical regression. A correlation matrix and hierarchical regression revealed a relationship between different aspects of SRL and academic performance. In conclusion, the study recommends that teaching and assessment methods should be used to empower students to apply self-regulated learning strategies. This could greatly enhance their academic performance.	en_US
dc.format.extent	91 908 bytes, 1 file
dc.format.mimetype	Application/PDF
dc.language.iso	en_US	en_US
dc.publisher	Central University of Technology, Free State, Bloemfontein: Journal for New Generation Sciences
dc.relation.ispartofseries	Journal for New Generation Sciences;Vol 13, Issue 3
dc.subject	Academic performance	en_US
dc.subject	Self-regulated learning	en_US
dc.subject	Correlation analysis	en_US
dc.subject	Hierarchical regression	en_US
dc.title	Self-regulated learning as predictor of academic performance	en_US
dc.type	Article	en_US
dc.rights.holder	Journal for New Generation Sciences