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A motivation profile analysis of Malay students in Singapore

URI
https://hdl.handle.net/10497/22223
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Type
Article
Files
 APJE-2020-770690.pdf (475.4 KB)
Citation
Liu, W. C., Wang, J. C. K., Kang, H. J., & Kee, Y. H. (2020). A motivation profile analysis of Malay students in Singapore. Asia Pacific Journal of Education, 41(2), 299-311. https://doi.org/10.1080/02188791.2020.1770690
Author
Liu, Woon Chia 
•
Wang, John Chee Keng 
•
Kang, Heon Jin
•
Kee, Ying Hwa 
Abstract
This study aims to examine the motivational profiles of Malay students in Singapore based self-regulated learning framework (Pintrich & De Groot, 1990) and self-determination theory (SDT; Deci & Ryan, 1985). The sample consisted of 740 secondary school Malay students (415 males, 325 females). Using cluster analysis, five different clusters of students were found based on their unique characteristics on self-regulation and learning strategies scores. The clusters were named from best to poor in numeric order. Cluster 1 is characterised by high scores on intrinsic value, self-efficacy, self-regulation, and lower scores on lack of learning strategies and anxiety compared to other clusters. On the other hand, cluster 5 has the lowest intrinsic values, self-efficacy, and self-regulation relative to their scores on other clustering variables. In addition, the more adaptive profiles were also found to score higher in enjoyment and effort, and lower in boredom, compared to other clusters. The findings suggest that intra-individual differences in self-regulated learning behaviour are associated with the expected differences in the type of motivation possessed, and learning outcome measures. Overall, the findings from the study shows that Malays students do possess adaptive qualities known to facilitate learning outcomes.
Keywords
  • Motivation profiles

  • Malay students

  • Self-determination th...

  • Motivated strategies ...

  • Cluster analysis

Date Issued
2020
Publisher
Taylor & Francis
Journal
Asia Pacific Journal of Education
DOI
10.1080/02188791.2020.1770690
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