Potential Abstract:
In the rapidly evolving landscape of education, the proliferation of educational programs in the market has sparked a contested debate among stakeholders regarding their efficacy and impact. This study employs a mediated approach to investigate the utilization of educational data mining techniques to analyze the effectiveness of these programs. By examining the rich data generated from these programs, this research aims to uncover valuable insights that can inform decision-making processes in education.
Drawing on theories from artificial intelligence and education, this study explores how educational data mining can provide a deeper understanding of the complexities surrounding the marketization of education. Through the lens of mediated analysis, this research seeks to shed light on the diverse perspectives and interests that shape the discourse on educational programs in the market. By unpacking the contested nature of these programs, this study contributes to the ongoing dialogue on the role of technology and data in education.
Potential References:
- Educational data mining: A survey from 1995 to 2005
- Educational data mining and learning analytics: An updated survey
- Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks
- Scalable techniques for mining causal structures
- Learning analytics: drivers, developments and challenges
