The combined effects of goal attributes, motivational beliefs, creativity and grit on self-regulation in online ill-structured problem solving: a fsQCA approach

被引:0
作者
Wang, Huanhuan [1 ]
Wang, Shaofeng [2 ]
Tlili, Ahmed [3 ]
Li, Mengti [4 ]
Yang, Dong [5 ]
Adarkwah, Michael Agyemang [6 ]
Zhu, Xixian [1 ]
Zhu, Ling [7 ]
Huang, Ronghuai [1 ]
Kuai, Hongyan [3 ]
机构
[1] Beijing Normal Univ, Fac Educ, Natl Engn Res Ctr Cyberlearning & Intelligent Tech, Beijing, Peoples R China
[2] Fuzhou Univ Int Studies & Trade, Int Business Sch, Fuzhou, Peoples R China
[3] Beijing Normal Univ, Smart Learning Inst, Beijing, Peoples R China
[4] Minist Educ, Educ Informatizat Strategy Res Base, Beijing, Peoples R China
[5] Beijing Normal Univ, Coll Educ Future, Zhuhai, Peoples R China
[6] Friedrich Schiller Univ Jena, Inst Educ & Culture, Chair Adult Educ, Planetarium 4, Jena, Germany
[7] Beijing Normal Univ, Sch Journalism & Commun, Beijing, Peoples R China
关键词
Self-regulated learning; Causal factors; Configural approach; fsQCA; Problem-solving; EXECUTIVE FUNCTION; QUESTION PROMPTS; TASK VALUE; ACHIEVEMENT; VALIDATION; EFFICACY; DETERMINANTS; ORIENTATIONS; PERSPECTIVE; PERFORMANCE;
D O I
10.1186/s40359-024-02317-0
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Self-regulated learning (SRL) has been regarded as one of the indispensable factors affecting students' academic success in online learning environments. However, the current understanding of the mechanism/causes of SRL in online ill-structured problem-solving remains insufficient. This study, therefore, examines the configural causal effects of goal attributes, motivational beliefs, creativity, and grit on self-regulated learning. With the fuzzy sets approach (fsQCA), the proposed association was analyzed based on a sample of students (n = 88) participating in an educational design competition activity. The results uniquely revealed the predictive factors of SRL at both high and low levels. In addition, it was found that no single condition of factors leads to the prediction of high or low self-regulation. More specifically, different conditions of factors, in terms of gender, goal attributes (goal setting and achievement goals), grit, task value, creativity, and self-efficacy, can largely predict high and low self-regulated learning during ill-structured problem-solving in the context of online learning. Implications for theory and policy prescriptions were discussed to enhance self-regulated learning in online ill-structured problem-solving.
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页数:14
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