"Flipped classrooms" have been tested in engineering education through the on-line delivery of lectures using speech-synchronized PC-screen-capture technology (SS-capture) to increase engineering students' enthusiasm towards studying. The SS-capture system records Screenshots as a series of still images synchronously with input from a microphone. The resultant recording is akin to a slide show and can be readily distributed and viewed on-line using a web server and browser respectively. The SS-capture system removes barriers that ordinarily inhibit average teachers in faculties of engineering, who often lack a background in educational technology, from implementing a flipped classroom. Although the SS-capture system requires students to exert more effort than in a traditional lecture-based classroom, they nevertheless gave it high praise since it allowed them to learn at their own pace. The benefits of flipped classrooms include increased learning time, proactive student participation/interaction, a subjective understanding of course content, and a substantial rise in academic performance.

In this paper we examine the affective content of meeting videos. First we asked five subjects to manually label three meeting videos using continuous response measurement (continuous-scale labeling in real-time) for energy and valence (the two dimensions of the human affect space). Then we automatically extracted audio-visual features to characterize the affective content of the videos. We compare the results of manual labeling and low-level automatic audio-visual feature extraction. Our analysis yields promising results, which suggest that affective meeting video analysis can lead to very interesting observations useful for automatic indexing.

We present a system based on a new, memory-cue paradigm for retrieving meeting video scenes. The system graically represents important memory retrieval cues such as room layout, participant's faces and sitting positions, etc.. Queries are formulated dynamically: as the user graically manipulates the cues, the query results are shown. Our system (1) helps users easily express the cues they recall about a particular meeting; (2) helps users remember new cues for meeting video retrieval. We discuss the experiments that motivate this new approach, implementation, and future work.