Abstract:

Video lectures bring flexibility and enable distance learning in education. With the help of videos, educational organizations are able to serve a wider and more heterogeneous group of students. While streaming videos have become essential part of teaching in higher education, the quality of service (QoS) issues should be taken more into consideration. However, the systematic quality monitoring on video lecture delivery is rarely used to our knowledge.

A streaming video lecture producer can affect factors like conditions on the recording set or the encoding parameters to make videos which meet specified requirements. But when the video is delivered to a student, either live or on-demand streaming, the internet transmission conditions or even student’s PC may cause deterioration in quality. Typical QoS parameters include bandwidth and the ratio of lost data packets. Along with the usage of mobile terminals, the bandwidth is more likely to variate. Lost data packets are usually a result of congestion in a transmission channel. Insufficient bandwidth and other interferences may cause a response in the media player which the student sees as interruptions, unsmooth playing and distorted video image. The decline in student’s viewing experience inflicts frustration and anxiety which interfere learning. For a distance learner, the lecture videos may be the only way to participate in teaching. Thus the QoS matters cannot be ignored either in educational context.

Monitoring quality statistics from streaming servers may be sufficient for having an overview of the quality level received by the students and information about internet connections they are using. To get more precise information about quality the person is experiencing the metrics can be collected near the student for example with the instrumented media player. Since students have power over some factors causing interferences they are observing in the video, the information about the quality should be offered them too. In addition, students’ awareness about adaptive streaming is rising and they are more eager to know if they are having the best quality possible. When designing our QoS evaluation practices for lecture video delivery our objective was to get parameters near the students and make them also aware of the quality they are receiving.

This paper describes our ongoing research on developing a streaming video quality evaluation tool integrated in a learning environment our master’s students use. The tool collects quality parameter values from both the streaming server and the media player. The quality indicator is created based on measurements conducted in a test environment. The application shows a student real time information about the streaming quality in a simple graphical form. The student is also provided an estimation whether the problems are a result of poor internet connection or overloaded processor. The tool serves also the education provider by producing reports about streaming quality of video lectures students are having. A pilot version of the tool is tested with a group of students and the usability of the tool is evaluated with a SUS Survey.

Keywords:

Video lecture, QoS-awareness, video quality, video streaming, video quality evaluation tool.