Detecting Users' Online Knowledge Sharing Behavioral Patterns in a Knowledge Management System: Using Sequential Analysis to Explore Online Knowledge Construction Process of an Online Teacher Community

Promoting knowledge sharing behaviors of online community members is a crucial issue for knowledge management(KM) systems, and detecting of users' knowledge sharing behavioral patterns will be able to find out the limitations instantly during their knowledge sharing process and provide a good reference for KM system to provide intelligent guidance to the process instantly. This research adopted the sequential analysis calculation, which can individually examine whether the sequential relationship between each knowledge sharing behavior has been achieved significantly, aiming to infer the knowledge construction behavioral patterns of online communities through analysis of actual behaviors. This research conducted an empirical observation and analyzed online knowledge sharing of a teacher community in Taiwan. The study detected the teachers' sequential knowledge construction patterns and also proposed further suggestions for online intelligent KM systems according to the analysis method and the patterns we found out.