移动学习中基于人际关系的助手推荐

Chengjiu Yin, Yan Dong, Yoshiyuki Tabata, H. Ogata
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引用次数: 15

摘要

在本文中,我们提出了一个基于假设的系统,当我们向他人寻求帮助时,1)人与人之间的关系越亲密,越容易得到帮助,2)简单的事情越容易得到帮助。我们进行了一项调查来检验这个假设。结果表明,这一假设是正确的。基于这一假设,我们提出了一个基于移动环境的社交网络服务网站——SENSMILE,它支持学习者在网络社区中找到一个可以解决自己问题的伙伴,并根据学习者的请求,利用个人关系推荐一个合适的朋友请求链。该系统还通过使用基于位置的传感信息支持协作学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recommendation of Helpers Based on Personal Connections in Mobile Learning
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.
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