Higher-order structure of noncognitive constructs and prediction of PISA 2003 mathematics achievement
By Jihyun Lee, L. Stankov. 2013
106 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Experimental and Cognitive Psychology, Social Psychology
View Paper: https://www.semanticscholar.org/paper/e66fea64e70d4e7303fa4034f00536ca4531827d
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In Developmental and Educational Psychology
In Experimental and Cognitive Psychology
- Anastasios Karakolidis
- Vasiliki Pitsia
- A. Biggart
- Jihyun Lee
- L. Stankov
- Juyeon Song
- D. Kalaycioğlu
- Yi Jiang
In Social Psychology
- Anastasios Karakolidis
- Vasiliki Pitsia
- A. Biggart
- L. Stankov
- D. Kalaycioğlu
- Juyeon Song
- Minhye Lee
- Yi Jiang
Citations in the corpus
- Quest for the best non-cognitive predictor of academic achievement (2014, background): “Thus, Lee and Stankov (2013) show that measures of self-beliefs (self-efficacy, anxiety and self-concept) are the best non-cognitive predictors of mathematics achievement in PISA 2003, while some of the cherished constructs – e.g. motivation, learning strategies and attitudes toward school – showed…”
- The Influence of Socioeconomic Status, Self-Efficacy, and Anxiety on Mathematics Achievement in England, Greece, Hong Kong, the Netherlands, Turkey, and the USA (2015, background): “At the cross country level however, the relationship between math self-efficacy, anxiety, and achievement is relatively complicated (Bodas & Ollendick, 2005; Liu, 2009). One’s perception of self-efficacy may have different meanings across different cultures. According to Schaubroeck, Lam, and Xie (2”
- The role of students' self-beliefs, motivation and attitudes in predicting mathematics achievement: A multilevel analysis of the Programme for International Student Assessment data (2017, methodology): “Nonetheless, once students’ self-beliefs and attitudes were controlled for in the above studies, intrinsic motivation became a poor predictor of mathematics achievement or even an insignificant one, due to its overlap with the above-mentioned constructs (Jiang et al., 2014; Lee & Stankov, 2013).”
- A Model of Factors Contributing to STEM Learning and Career Orientation (2015, methodology): “Learning strategies have not been incorporated in path models based on SCCT, but they have been investigated in other research showing direct and indirect influences on achievement (Cano, Garcia, Berben, & Justicia, 2014; Lee & Stankov, 2013).”
- Self-efficacy and achievement goals as motivational links between perceived contexts and achievement (2014, background): “Lee and Stankov (2013) obtained similar results when they analysed the Programme for International Student Assessment (PISA) data.”