Abstract
Online cooperative learning is a structured teaching strategy in which team members jointly complete knowledge construction or solution acquisition through online discussion. The process evaluation of cooperative learning mainly about how well a student focus on the discussion. However, the evaluation mostly focuses on subjective evaluation, lacking quantitative and objective evaluation. This paper develops a video-based online cooperative learning quantitative evaluation method. Firstly, Considering that there are few online cooperative learning video data sets at present, we have established the online cooperative learning Video data set through classroom practice(100 students, 8000minutes), secondly, we proposed an artificial intelligence strategy combining intensive trajectory tracking, feature map extraction, VLAD feature encoding, and linear classifiers to evaluate students’ devotion in the online discussion. 76.21% accuracy was obtained on the self-built data set, which laid a good foundation for subsequent online cooperative learning research.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have