| Summary: | 碩士 === 淡江大學 === 教育科技學系碩士在職專班 === 101 === The development of technology and internet leads to a shift in the structure of social life, as well as influences and changes the lifestyle, relationships, information and knowledge sharing and forms of learning. Internet plays an important and critical role in our daily life as everything is digitalized. This includes food, clothing, accommodation, transportation, entertainment, information and communication, knowledge learning, books and cultural resources.
Along with the development of the Internet is the burgeoning internet communities that have no borders. Internet communities with different expertise have different members who have different backgrounds and therefore differ in their social behaviors. Research into the difference in the social behaviors between different internet communities can benefit the development, deployment and applications of these communities. The integration of internet communities into distance learning and supplementary teaching can also enhance social learning and narrow the gap between urban and rural areas.
The study used iThelp as a case study to explore the background and social behavior of the members of the internet community. Questionnaires were employed (N=302) to collect the data. Descriptive analysis, T-test and One-Way ANOVA were adopted to analyze the results. The conclusions are:
There is a difference in the distribution of members’ backgrounds between expert internet community and general internet community ; areas of expertise and reasons for joining internet community have an impact on the distribution of members’ backgrounds.
Expert internet community shows a high level of social behavior recognition while there is a significant difference in the social behavior between members with different backgrounds.
There is an association between motivation and social behaviors. Website management teams and members who are invited by friends to join internet community show a high level of social behavior recognition.
The results can enhance the understanding on the social behaviors of internet community and thus provide useful information for teachers and website management teams in the future.
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