Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3574
Full metadata record
DC FieldValueLanguage
dc.contributor.authorShaw, Rabi-
dc.contributor.authorMohanty, Chinmay-
dc.contributor.authorPradhan, Animesh-
dc.contributor.authorPatra, Bidyut Kr-
dc.date.accessioned2021-07-26T12:38:30Z-
dc.date.available2021-07-26T12:38:30Z-
dc.date.issued2021-07-
dc.identifier.citationIEEE 21st International Conference on Advanced Learning Technologies, 12-15 July 2021, ICALT 2021en_US
dc.identifier.urihttp://hdl.handle.net/2080/3574-
dc.descriptionCopyright of this paper is with proceedings publisheren_US
dc.description.abstractFlipped Classroom is a mode of learning which is developed based on students’ academic engagement inside and outside the classroom. In this learning pedagogy, students take lessons from pre-loaded lecture videos before coming to the classroom for doubt clearing, discussion, problem solving, etc. However, it is very difficult to ensure that students really pay attention while watching lecture videos. In this paper, we adopt a feature selection technique called 1D local binary pattern (1D-LBP) to analyze captured brain signals of the students. The proposed feature selection technique is termed as 1D Multi-Point Local Ternary Pattern (MP-LTP), which extracts unique statistical features from EEG signals. Subsequently, standard classification techniques are exploited to analyze the attention level of students. Experimental results show that the proposed method outperforms state-of-the-art classification techniques using LBPen_US
dc.subjectElectroencephalogram (EEG),en_US
dc.subjectMulti-Point Localen_US
dc.subjectTernary Pattern (MP-LTP),en_US
dc.subjectFlipped Learning (FL),en_US
dc.subjectDiscrete Wavelet Packet Transform (WPTen_US
dc.titleAttention Analysis in Flipped Classroom using 1D Multi-Point Local Ternary Patternsen_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
Patrab_ICALT2021.pdf136.03 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.