Potential Abstract: This study delves into the intersection of algorithmic practices, second-order cybernetics, and open science within the context of Massive Open Online Courses (MOOCs) in a capitalist society. As digital platforms continue to shape educational landscapes, understanding the underlying algorithms that govern these platforms becomes crucial. Through a second-order cybernetics lens, this research investigates how algorithms influence the design, delivery, and outcomes of MOOCs, particularly in the realm of open science. By employing a critical perspective on the power dynamics at play within capitalist educational systems, this study aims to uncover the implications of algorithmic decision-making in shaping the future of education.
Potential References:
- Beyond the “c” and the “x”: Learning with algorithms in massive open online courses (MOOCs)
- Educational data science in massive open online courses
- Active algorithms: Sociomaterial spaces in the e-learning and digital cultures MOOC
- Reflections on the last decade of MOOC research
- Novel online recommendation algorithm for massive open online courses (NoR-MOOCs)
