The combined effects of goal attributes, motivational beliefs, creativity and grit on self-regulation in online ill-structured problem solving
A fsQCA approach
Bibliographic Data
| ID | 15696393 |
|---|---|
| Authors | Huanhuan Wang (0000-0002-8886-8589, Beijing Normal University), Shaofeng Wang (0000-0002-0300-2453, Fuzhou University), Ahmed Tlili (0000-0003-1449-7751, Beijing Normal University), Mengti Li (0000-0001-7023-1750), Dong Yang (0000-0002-6382-0706, Beijing Normal University, corresponding author), Michael Agyemang Adarkwah (0000-0001-8201-8965, Institute for Education and Culture), Xixian Zhu (0009-0007-2199-5421, Beijing Normal University), Ling Zhu (0000-0002-7046-9635, Beijing Normal University), Ronghuai Huang (0000-0003-4651-5248, Beijing Normal University), Hongyan Kuai (Beijing Normal University) |
| Year | 2025 |
| Volume | 13 |
| Issue | 1 |
| Pages | 27-27 |
| Publication date | 2025-01-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Psychology (JOURNAL) |
| Journal identifiers | ISSN: 2050-7283 • E-ISSN: 2050-7283 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s40359-024-02317-0 |
| PMID | 39789628 |
| OpenAlex | W4406230675 |
| Language | EN |
| Citations received | 1 |
| References cited | 87 |
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
Cognitive psychology · Context (archaeology · Creativity · Goal Orientation · Grit · Mathematics education · Self-regulated learning · Applied Psychology · Grit, Self-Efficacy, and Motivation · Innovative Teaching and Learning Methods · Online Learning and Analytics · Psychology · Social Psychology
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |