Leveraging Metacognitive Data Visualization in Business Problem-Solving: An Empirical Study
Scaffolding—a pedagogical framework where experts provide incremental support to help learners master complex tasks—has been widely examined in educational contexts, yet its metacognitive dimensions in professional problem-solving remain underexplored. Despite growing interest in metacognitive scaffolds (i.e., strategies guiding how to think), two critical questions persist: (1) What is the relationship between metacognitive awareness and self-evaluated problem-solving performance? (2) How do metacognitive scaffolding mechanisms function in data-intensive business scenarios? This study adopts a multimodal analytics perspective combining quantitative modeling and big data visualization techniques. We collected behavioral and self-report data from 57 third-year business students engaged in simulated business tasks. SPSS 22.0 facilitated hierarchical quantitative analyses, while Wordclouds processed the big textual data to identify scaffolding patterns. Key findings include: (1) Metacognitive regulation and metacognitive knowledge are positively related to business problem-solving performance even though the relation in between is statistically insignificant; (2) Metacognitive knowledge such as procedural knowledge and information management strategy could significantly affect an individual's problem-solving performance. Metacognitive scaffolding plays a vital role in assisting students to solve complex business problems more effectively. Crucially, the visualization outputs reveal that effective metacognitive scaffolding often functions as cognitive bridges – when domain experts provide structured guidance, learners demonstrate enhanced capacity to internalize complex business protocols that would otherwise exceed their ZPD. Theoretical implications challenge the assumption of metacognitive awareness as a unitary construct, demonstrating the primacy of domain-specific procedural knowledge in business contexts. Practical guidelines propose integrating visualization dashboards with metacognitive prompts in management training systems. Limitations regarding sample representativeness (single-institution undergraduates) and measurement granularity (self-reported performance scales) suggest directions for replication studies with industry professionals using neurocognitive metrics.
Authors
- Xueyan Yin
Institutions
- Guangdong University of Foreign Studies (CN)
Publication Details
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1109/icccbda64898.2025.11030433
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00