Massive open online courses have difficulty dynamically allocating computational resources and maintaining a good learner experience.Existing methods, using system metrics, do not consider the impact of collective psychological states on demand.This paper puts forward a group psychological state-oriented elastic resource allocation framework.We analyse multimodal behavioural data to build a predictive model of learner states such as engagement or confusion.The prediction dynamically guides cloud resource scaling through a state-aware algorithm.Extensive experiments on the public massive open online courses dataset prove the effectiveness of our approach.The accuracy of recognising the psychological state reaches 89.3%, and it can save about 30% of resources compared with traditional methods.This study shows how mixing psychological knowledge enables better resource management, making them more useful and quicker to react for big online learning places on internet.
Ya Zhou (Thu,) studied this question.