This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces: (1) VLE, a novel dataset that consists of content and video based features extracted from publicly available scientific video lectures coupled with implicit and explicit signals related to…

We propose a new model for learning that relates video watching behavior and engagement to quiz performance. In our model, a learner's knowledge gain from watching a lecture video is treated as proportional to their latent engagement level, and the learner's engagement is in turn dictated by a set of behavioral features we propose that quantify…

Although millions of students have access to varieties of learning resources on Massive Open Online Courses (MOOCs), they are usually limited to receiving rapid feedback. Providing guidance for students, which enhances the interaction with students, is a promising way to improve learning experience. In this paper, we consider to show students the…

We investigate the use of consumer-grade eye tracking to automatically detect Mind Wandering (MW) during learning from a recorded lecture, a key component of many Massive Open Online Courses (MOOCs). We considered two feature sets: stimulus-independent global gaze features (e.g., number of fixations, fixation duration), and stimulus-dependent…

Since MOOC is suffering high dropout rate, researchers try to explore the reasons and mitigate it. Focusing on this task, we employ a composite model to infer behaviors of learners in the coming weeks based on his/her history log of learning activities, including interaction with video lectures, participation in discussion forum, and performance…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…