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With an expansive and ubiquitously available gold mine of educational data,Massive Open Online courses (MOOCs) have become the an important foci oflearning analytics research. The hope is that this new surge of developmentwill bring the vision of equitable access to lifelong learning opportunitieswithin practical reach. MOOCs offer many valuable learning experiences tostudents, from video lectures, readings, assignments and exams, toopportunities to connect and collaborate with others through threadeddiscussion forums and other Web 2.0 technologies. Nevertheless, despite allthis potential, MOOCs have so far failed to produce evidence that thispotential is being realized in the current instantiation of MOOCs. In thiswork, we primarily explore video lecture interaction in Massive Open OnlineCourses (MOOCs), which is central to student learning experience on theseeducational platforms. As a research contribution, we operationalize videolecture clickstreams of students into behavioral actions, and construct aquantitative information processing index, that can aid instructors to betterunderstand MOOC hurdles and reason about unsatisfactory learning outcomes. Ourresults illuminate the effectiveness of developing such a metric inspired bycognitive psychology, towards answering critical questions regarding students'engagement, their future click interactions and participation trajectories thatlead to in-video dropouts. We leverage recurring click behaviors todifferentiate distinct video watching profiles for students in MOOCs.Additionally, we discuss about prediction of complete course dropouts,incorporating diverse perspectives from statistics and machine learning, tooffer a more nuanced view into how the second generation of MOOCs be benefited,if course instructors were to better comprehend factors that lead to studentattrition.

"Your click decides your fate": Leveraging clickstream patterns from MOOC videos to infer students' information processing & attrition behavior