Correlation of MOOC Students’ Behavior Patterns and Their Satisfaction with the Quality of the Course

Mozhaeva, Galina; Maslova, Daria; Yakovleva, Kristina

doi:10.2991/aebmr.k.200324.116

Cited by 2 publications

(2 citation statements)

References 8 publications

(11 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…So, the upper bound of equation ( 6) can be constructed by variational approximation [32]. Specifically, for I(Z, Y) in equation (7), let q(y|z) be the variational approximation of p(y|z). From the nonnegativity of KL divergence, we can obtain the following:…”

Section: Variational Information Bottleneckmentioning

confidence: 99%

See 1 more Smart Citation

MOOC Dropout Prediction Based on Multidimensional Time-Series Data

Shou

Chen

Wen

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Massive open online courses have attracted millions of learners worldwide with flexible learning options. However, online learning differs from offline education in that the lack of communicative feedback is a drawback that magnifies high dropout rates. The analysis and prediction of student’s online learning process can help teachers find the students with dropout tendencies in time and provide additional help. Previous studies have shown that analyzing learning behaviors at different time scales leads to different prediction results. In addition, noise in the time-series data of student behavior can also interfere with the prediction results. To address these issues, we propose a dropout prediction model that combines a multiscale fully convolutional network and a variational information bottleneck. The model extracts multiscale features of student behavior time-series data by constructing a multiscale full convolutional network and then uses a variational information bottleneck to suppress the effect of noise on the prediction results. This study conducted multiple cross-validation experiments on KDD CUP 2015 data set. The results showed that the proposed method achieved the best performance compared to the baseline method.

show abstract

Section: Variational Information Bottleneckmentioning

confidence: 99%

“…e MOOC platform stores a large amount of student behavior data, such as student clickstream data, homework submission, achievement information, forum discussion participation, and interactive information [7].…”

Section: Introductionmentioning

confidence: 99%