Posted in May 2019
MOOC Analytics: Learner Modeling and Content Generation
Doctoral thesis of Guanliang Chen, successfully defended on May 6th 2019.
Abstract
Massive Open Online Courses (MOOCs), as one of the popular options for people to receive education and learn, are endowed with the mission to educate the world. Typically, there are two types of MOOC platforms: topic-agnostic and topic-specific. Topic-agnostic platforms such as edX and Coursera provide courses covering a wide range of topics, while topic-specific MOOC platforms such as Duolingo and Codeacademy focus on courses in one specific topic. To better support MOOC learners, many works have been proposed to investigate MOOC learning in the past decade. Still, there are many other aspects of MOOC learning to be explored.In this thesis, we focused on (i) learner modeling and (ii) generation of educational material for both topic-agnostic and topic-specific MOOC platforms.
Keywords
Reference
Download
Large-Scale Learning Analytics: Modeling Learner Behavior & Improving Learning Outcomes in Massive Open Online Courses
Doctoral thesis of Dan Davis defended on May 7th 2019.
Keywords
learning analytics, web information systems, learning science, educational data mining, MOOCs
Reference
Davis, D. (2019). Large-Scale Learning Analytics: Modeling Learner Behavior & Improving Learning Outcomes in Massive Open Online Courses. https://doi.org/10.4233/uuid:b8be8302-84a0-4b29-a6fe- 761a3f872420