Exploring Education as a Complex System
Computational Educational Research with Multi-Level Agent-Based Modeling
Bibliographic Data
| ID | 22043906 |
|---|---|
| Authors | John Vulic (0000-0003-3672-453X, University of Technology Sydney, corresponding author), M J Jacobson (0000-0001-6521-9757, The University of Sydney), James A Levin (0000-0001-6196-1882, University of California San Diego) |
| Year | 2024 |
| Volume | 14 |
| Issue | 5 |
| Pages | 551 |
| Publication date | 2024-05-20 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci14050551 |
| OpenAlex | W4398141964 |
| Language | EN |
| Citations received | 1 |
| References cited | 26 |
Our study employs multi-level agent-based modeling and computational techniques to explore education as a complex system. With an underlying focus that education should be underpinned by a scientific understanding of student learning, we created computational models that simulated learning dynamics in classrooms, integrating both quantitative and qualitative insights. Through these models, we conducted experiments aligned with real classroom data to address key questions, such as “How can we effectively support the academic progress of underperforming students, who are disproportionately from low socio-economic status (SES) backgrounds, to close their multi-year achievement gap in mathematics?” Our study analyzes various instructional approaches for mathematical learning, and our findings highlight the potential effectiveness of Productive Failure as an instructional approach. Considerations of the broader applicability of computational methods in advancing educational research are also provided
Computational model · Educational research · Management science · Mathematics education · Complex Systems and Decision Making · Computer Science · Engineering · Online and Blended Learning · Online Learning and Analytics · Psychology · Artificial Intelligence
Cognitive Load Theory
Productive Failure in Learning Math
A meta‐analysis of the relationship between socioeconomic status and executive function performance among children
Designing for Productive Failure
Productive Failure
Active learning increases student performance in science, engineering, and mathematics
Cognitive Load During Problem Solving
When Problem Solving Followed by Instruction Works
Using Computational Modeling for Building Theory
Teachers and pre-service teachers as partners in collaborative teacher research
Education as a Complex System
Funds of knowledge for teaching
The Impact of Enhancing Students' Social and Emotional Learning
A meta-analysis of the experimental evidence on the near- and far-transfer effects among children's executive function skills
Culture and Mathematics
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |