In this paper, we present a tool that interleaves lengthy lecture videos with questionnaires at optimal moments. This is done to keep students’ attention by making the video interactive. The student will be presented with MCQ type questions based on the topic covered so far in the video, at regular intervals. The questions are generated based on the transcript of the video lecture using machine learning and natural language processing techniques. In order to have continuity and proper flow of teaching, a LDA-based (Latent Dirichlet Allocation) model has been proposed to insert those generated questions at appropriate points called logical points.