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Download full textLundqvist, Karsten Ø.; Liyanagunawardena, Tharindu; Starkey, Louise – International Review of Research in Open and Distributed Learning, 2020
Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the use of automated sentiment analysis in assessing…
Descriptors: Feedback (Response), Online Courses, Student Experience, Peer Relationship
Hew, Khe Foon; Qiao, Chen; Tang, Ying – International Review of Research in Open and Distributed Learning, 2018
Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884…
Descriptors: Learner Engagement, Large Group Instruction, Online Courses, Man Machine Systems
Giannakos, Michail N.; Chorianopoulos, Konstantinos; Chrisochoides, Nikos – International Review of Research in Open and Distributed Learning, 2015
Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may…
Descriptors: Video Technology, Lecture Method, Educational Technology, Technology Uses in Education
