期刊
INTERNET AND HIGHER EDUCATION
卷 56, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.iheduc.2022.100894
关键词
Social presence; Path analysis; Log data; Social network analysis; Automatic measurement; Indicators
The study aims to identify measures of social presence in online learning environments, which is challenging to measure. Through coding students' postings and using social network analysis and log data, the study conducted an exploratory path analysis to determine appropriate indicators for social presence. The size of the individual student's network, constraint, number of active forums, and number of solved learning activities were found to be indicators of social presence. Furthermore, the study found that four indicators for social presence in online-based courses can be readily obtained from routine data of learning management systems, and the focus will now be on the development of social presence in an ongoing course.
Social presence is a key element in collaborative/cooperative learning. In online learning environments, it is challenging to measure the current state of social presence. This work aims to identify measures of social presence.We manually coded 3546 students' postings (n = 49 students). We selected measures from social network analysis and indices derived from log data as potential indicators. We conducted an exploratory path analysis to define which indicators appropriately describe social presence.The size of the individual egocentric student's network (path coefficient = - 0.56**) and constraint (path coefficient = - 0.51**), as well as the number of forums in which students were active (path coefficient = 0.49**) and the number of solved learning activities (path coefficient = - 0.59**) were indicators of the level of social presence.We were able to identify four indicators for social presence in online-based courses readily available within routine data from learning management systems. We will focus now on how social presence in an ongoing course develops.
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