Design of a Novel Intelligent Framework for Finding Experts and Learning Peers in Open Knowledge Communities

Abstract

Open knowledge communities (OKCs) are computer supported collaborative learning environments that provide opportunities for social knowledge construction, collaboration, participation and communication for ubiquitous learning and informal learning. However, with the rapid expanding of learning content resources and users, it is difficult for learners to find the right persons they need as knowledge experts and learning peers in OKCs using traditional search engines. To solve this problem, the paper presents a novel intelligent framework for finding the right experts and learning peers based on social knowledge network. After describing the architectural details of the framework, the authors elaborate on the intelligent framework design, the work principle, and mechanism of each module. Finally，the authors conclude by showing the learning application scenarios of this intelligent framework.

A Curation Activity-Based Self-Regulated Learning Promotion Approach as Scaffolding to Improving Learners’ Performance in STEM Courses

“…Moreover, with respect to connectivism, as mentioned by Clarà and Barberà (2013), learning is to construct the relations among different nodes in learning spaces, and people are the most important nodes. Therefore, constructing contexts that can help learners find experts and peers for social interaction can improve learning (Wu & Yu, 2015).…”