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PCN: Quantifying Learning Activity for Assessment based on Time-series Comments.

, and . CSEDU (2), page 419-424. SciTePress, (2011)

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Comments Data Mining for Evaluating Student's Performance., , , and . IIAI-AAI, page 25-30. IEEE Computer Society, (2014)Analysis of Students' Learning Activities through Quantifying Time-Series Comments., and . KES (2), volume 6882 of Lecture Notes in Computer Science, page 154-164. Springer, (2011)Correlation of grade prediction performance and validity of self-evaluation comments., , and . SIGITE Conference, page 35-42. ACM, (2013)Prediction of Students' Grades Based on Free-Style Comments Data., , , and . ICWL, volume 8613 of Lecture Notes in Computer Science, page 142-151. Springer, (2014)Predicting Student Grade based on Free-style Comments using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons., , , and . EDM, page 396-399. International Educational Data Mining Society (IEDMS), (2015)Comment Data Mining to Estimate Student Performance Considering Consecutive Lessons., , and . Educational Technology & Society, 20 (1): 73-86 (2017)Automated Evaluation of Student Comments on Their Learning Behavior., , and . ICWL, volume 8167 of Lecture Notes in Computer Science, page 131-140. Springer, (2013)Predicting students' grades based on free style comments data by artificial neural network., , , and . FIE, page 1-9. IEEE Computer Society, (2014)Efficiency of LSA and K-means in Predicting Students' Academic Performance Based on Their Comments Data., , , and . CSEDU (1), page 63-74. SciTePress, (2014)PCN: Quantifying Learning Activity for Assessment based on Time-series Comments., and . CSEDU (2), page 419-424. SciTePress, (2011)