Title: Enhancing learners' metacognition for smart learning: effects of deep and surface learning, disorganisation, achievement goals and self-efficacy

Authors: Kam Cheong Li; Billy Tak-Ming Wong

Addresses: The Open University of Hong Kong, Hong Kong ' The Open University of Hong Kong, Hong Kong

Abstract: Learners' metacognition has been recognised as a key factor in their success in smart learning. However, for enhancing their metacognition for smart learning, the effects of other variables have been rarely addressed. This paper presents a study on the effects of deep and surface learning, disorganisation, achievement goals and self-efficacy on metacognition. Questionnaires measuring these variables were administered to 311 Hong Kong undergraduate students. Correlational analysis showed significant correlations among all these variables. Regression analysis showed that deep and surface learning, and self-efficacy, were significant predictors of metacognition. Among all the predictors, deep learning was shown to be the strongest, followed by surface learning, disorganisation and self-efficacy. The implications of the results are discussed in respect of the strategies to enhance metacognition to facilitate learners' success in a smart learning environment.

Keywords: smart learning; metacognition; deep learning; surface learning; disorganisation; achievement goals; self-efficacy.

DOI: 10.1504/IJSMARTTL.2019.099507

International Journal of Smart Technology and Learning, 2019 Vol.1 No.3, pp.203 - 217

Received: 17 Jul 2018
Accepted: 06 Sep 2018
Published online: 07 May 2019 *

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