Learning behavior analysis for MOOC classroom feedback
GU Xin1， HU Po2， HE Tingting2， ZHOU Ruowei2
1.Collaborative & Innovative Center for Educational Technology， Central China Normal University， Wuhan 430079， China；2.School of Computer Science， Central China Normal University， Wuhan 430079， China
Abstract：As a popular interaction between students and instructors， MOOC classroom feedback analysis is crucial to the success of learning and teaching. It may help teachers to grasp students' learning situation precisely and promote students to examine themselves actively. Traditionally， instructors have to analyze these responses in a manually and costly manner. In this work， text-based student feedback after each lecture are automatically collected. Using statistical analysis and natural language processing technology， we then investigate student learning behavior from various reply records and text－based feedback. Experimental results on a student feedback corpus from China College MOOC show how the student's engagement and activeness vary over time. We also demonstrate how students in various disciplines perform differently between their learning behavior and classroom discourse distribution. The results show that students' feedback almost focuses on these course contents themselves， and positive emotions account for a large proportion. But student's engagement and activeness are at a lower level， which need to be worth improving further. There was significant variability of learning behavior between and within different courses. For Arts courses， the rate of students' participation and the activeness of reply present the superior states， the extent of content is higher than other courses. Liberal Arts courses expose the imbalance states between higher engagement and lower activeness， and feedback content focus on the deep thought of topic. While Science courses are inclined to reply questions compactly and repeatable. The improvement of its engagement and activeness contributes to learning communication and knowledge construction process.
2018, Vol. 52 
