Resumen de A personal social knowledge network (PSKN) facilitates learners’ wayfnding and its diferences in behavior patterns between high and low performers in connectivist learning

Jinju Duan, Kui Xie, Qiuhua Zhao

• Wayfnding, which is a part of learning in connectivist learning, involves consolidating a wide variety of resources and information and building connections among them.

  However, learners often encounter difculties in wayfnding, and are lost without technological support in connectivist learning. This study examined the wayfnding processes occurring within a network of learners in a personal social knowledge network (PSKN), explored diferences in behavior patterns between high and low performers in PSKN. The results reveal the diversity and complexity of wayfnding in a PSKN, including fnding and connecting nodes, forming cognitive maps, fnding and fltering information, and creating new nodes. Moreover, the characteristics of wayfnding in the PSKN difered across participants, and high- and low-performing participants demonstrated diferent and unique wayfnding behavioral patterns, which provided a basis for comprehensive analyses of wayfnding. These fndings can be used to provide instructional support and network navigation in connectivist learning for learners at various performance levels. The proposed PSKN shows promise in facilitate wayfnding including fnding nodes and connecting nodes, as well as relations between knowledge nodes and the course base demonstrated by PSKN, providing great convenience for learners to form cognitive maps based on the node sequence.

  Compared with current studies, this research focuses on diversifed interaction data and resource behavior rather than teaching videos and quizzes or exercises as the main resources and considering that course and technological factors infuence the ways in which learners access resources in connectivist learning.