Designing Better MOOCs by Leveraging Socio-Technical Systems 

   Dr. Dilrukshi Gamage

Supervisors: Dr. MSD Fernando, Dr. GIUS Perera

Department: Computer Science and Engineering 

Faculty: Engineering 

Massive Open Online Courses (MOOCs) are a type of online education technology that enables a massive number of participants to learn any course at any time via online platforms such as Coursera, edX, Udacity, etc.

The affordance enabled by these platforms to scale and to provide open access to education is considered to be the globalized solution for acquiring 21st-century skills. However, unrealistic to the vision, pragmatically, MOOCs are facing challenges. Mainly the content-driven pedagogical structure with limited system designs that support collaboration and interactions caused isolation among participants and led to higher dropouts.


In this thesis, I explored solutions to improve the effectiveness of online learning in MOOCs from learners’ perspectives so they can be equipped to face 21st-century challenges. Using methodologies intersecting with Human-Computer Interactions, Computational Social Science and Learning Analytics, my research  - 1) provided empirical evidence to the challenges faced by MOOC participants, 2) solicited a framework to identify and improve the effectiveness of MOOCs, 3) designed a novel peer-reviewing structure with semi-structured community model to learn effectively with a close-knit group of learners and 4) developed novel systems while integrating them to real MOOCs and demonstrated the improved effectiveness. The work of this thesis actively contributes to the nuance of socio-technical systems in designing open scalable learning-at-scale technologies.




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