Towards quality monitoring and managing for online learning

在2022财年，我们调查了在线学习的体验质量（QoE）和视频交付问题。我们对PC和移动的用户的大量质量模型进行了评估。由于在线学习主要是通过PC显示器接收的，并且持续时间很长，因此我们发现只有少数质量模型适用于测量学习者侧的QoE。此外，研究了多特征学习方法在建模中的应用潜力。对于视频传输，提出了一种新的解决方案，将相同的视频发送给多个用户。我们的解决方案采用了可伸缩视频编码和组播机制，有效地提供了一个视频到多个用户在一个会话。我们还研究了疫情后在线学习QoE管理系统实施的关键问题和技术。

In AY2022, we investigated problems of Quality of Experience (QoE) and video delivery for online learning. We evaluated of a large number of quality models for both PC and mobile users. Because online learning is mostly received via PC displays and has long durations, we found that just a few of quality models were appropriate for measuring the QoE at the learner’s side. Besides, the potential of multi-feature learning approach was studied for modeling. For video delivery, a new solution was proposed to send the same video to multiple users. Our solution employed scalable video coding and multicast mechanism to effectively deliver a video to many users in a session. We also investigated key issues and techniques in system implementation for QoE management for post-pandemic online learning.