Research Seminar: Data Science Speeding up the Online learning curve

Open & Online education is a growing force in higher education. Platforms like EdX and Coursera offer a broad spectrum of Massive Open Online Courses. How do we keep learners engaged throughout a course and how do we assess if leaning goals have been achieved? The massive amount of data, produced by learners inside and outside the Massive Open Online Courses and the challenges for online assessment makes Online education a very interesting field for data science research. In this DDS seminar we will explore the research questions around learning analytics, gamification and online assessment.

How can we build comprehensive learner models that provide fine-grained insights into learners’ abilities, motivations, behaviour, knowledge and learning curves? For example a gaze-based indicator of students’ attention in a MOOC video lecture is proposed to define “with-me-ness” at two levels: perceptual, following teacher’s deictic acts; and conceptual, following teacher discourse.

Experiences  of gamification in the classroom give us food for thought for the use of gamification in the online learning environment. How can we use game-based learning to improve the learning outcomes? Assessment in online courses is now often done by multiple choice tests, but many instructors feel a need for automated assessment of “open” answers, designs, programs or other student materials. How can we achieve this? Can natural language processing and machine learning methods enhance online assignments and peer reviews? Will you join us for speeding up the Online learning curve?

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