Sequential Pattern Mining Model of Performing Video Learning History Data to Extract the Most Difficult Learning Subjects
7 Pages Posted: 19 Nov 2018
Date Written: September 6, 2018
The paper aim is to define a method for performing video learning data history of learner’s video watching logs, video segments or time series data in consistency with learning processes. To achieve this aim, a theoretical method is introduced. Sequential pattern mining with learning histories are used to extract the most difficult learning subjects. Based on this method, it is designed a model for understanding and learning the most difficult topics of students. The performed video learning history data of learner’s video watching logs makeup of stop/replay/backward data activities functions. They correspond as output of sequence of the learning histories, extraction of significant patterns by a set of sequences, and findings of learner’s most difficult/important topic from the extracted patterns. The paper mostly aim to devise the model for understanding and learning the most difficult topics through method of mining sequential pattern.
Keywords: Sequential Pattern Mining (SPM); Video; Learning; Keyword Topic (KT)
JEL Classification: O33
Suggested Citation: Suggested Citation