Research Article

Grade Prediction in Blended Learning Using Multisource Data

Table 1

The data of MOOC.

Feature typesNumberData descriptionExamples

Teaching video viewing situation102The completion of watching each teaching video is presented in percentage100%, 55%
Student information7School number, name, and other identifying information
Discussion4The number of postdiscussions and reply discussions are presented by the number of replies0, 5
Job scores6Job score, a total score of 50, 4.5, 5
Job completion status6Complete or notYes/no
Job mutual-evaluation status6Rate each other or notYes/no
Scores on tests8Online test scores, out of 1000, 90.0, 100
Test completion time8Test completion time in YYYY-MM-DD, hh:mm:ss2019-12-28, 00:24:09
Watching time duration1Student cumulative time for the video, in minutes721 minutes
Accumulated learning times1Number of times students open a learning platform to learn324
Progress of task point completion4Progress of video viewing and completion of the test, in scores120/120, 1/8
Certificate issuance1The MOOC Platform can apply for certification after completing the specified indicatorsYes/no
The score of online platforms2Regular results and total results on the teaching platform, out of 10090, 100
Five levels1Convert scores to grade systemA, B, C, D, E