Recommendation of Helpers Based on Personal Connections in Mobile Learning

Abstract

In this paper, we propose a system based on hypothesis that when we ask for help from others, 1) the closer people are, the more easy it is to get help, 2) the more simple things are easier to get help with. We carried out a survey to examine the hypothesis. The results show that this hypothesis is correct. Based on this hypothesis, we proposed a social networking service site based on a mobile environment called SENSMILE, which supports learners to find a partner who can solve their problems at the online community, and an appropriate request chain of friends will be recommended upon their request by utilizing personal relationships. The system also supports for collaborative learning by using location based sensing information.