Li, NanKidzinski, LukaszJermann, PatrickDillenbourg, Pierre2015-06-092015-06-092015-06-092015https://infoscience.epfl.ch/handle/20.500.14299/114979For MOOC learners, lecture video viewing is the central learning activity. This paper reports a large-scale analysis of in-video interactions. We categorize the video behaviors into patterns by employ- ing a clustering methodology, based on the available types of interactions, namely, pausing, forward and backward seeking and speed changing. We focus on how learners view MOOC videos with these interaction patterns, especially on exploring the relationship between video interaction and perceived video difficulty, video revisiting behaviors and student performance. Our findings provide insights for improving the MOOC learning experiences.MOOConline educationvideo analysisvideo interactionclustering analysistext::conference output::conference proceedings::conference paper