Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/183844
Authors: 
Doko, Edona
Abazi Bexheti, Lejla
Shehu, Visar
Year of Publication: 
2018
Citation: 
[Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018 [ISSN:] 2706-4735 [Volume:] 4 [Pages:] 342-348
Abstract: 
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.
Subjects: 
Sequential Pattern Mining (SPM)
Video
Learning
Keyword Topic (KT)
JEL: 
O33
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/4.0/
Document Type: 
Conference Paper

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