Social Computing: Supporting Grounding in Communication with IoT-based Knowledge Sharing and Learning

PI: Hao-Chuan Wang (National Tsing Hua University), CoPI: Chien-Wen Yuan (Fu Jen Catholic University)

Champion: Saurav Sahay (Intel) 

Status Quo: 

Work experiences or best practices need to be transferred among workers for maintaining the productivity within an organization. For task training and performing in workplace, there’s need to pass knowledge of task workflow and know-hows from senior experts to novice workers who will take over the task. 

Empirical studies show that the knowledge gap between experts and novices may hinder the task transfer process. For example, experts may overlook troubles novices encounter, or use expert’s language which may not be easily understood by novices. 

To support this knowledge sharing and learning process, we conceptualize and present KnowledgeKeeper (KK), which is a task and solution oriented knowledge repository that can be co-edited (annotated) by experts and learners. It comprises three main parts, capturing knowledge, synthesizing knowledge, and displaying knowledge which meets learners’ and organizations’ needs of knowledge transfer.

Key New Insights:

–     KnowledgeKeeper is a task and solution oriented knowledge repository that is co-edited (annotated) by experts.

–     It comprises three main parts: capturing knowledge, synthesize knowledge, and display knowledge                          which meets learners’ and organizations’ needs of knowledge transfer.

–     Different feedback sources provide different support for experts’ to externalize their knowledge.

–     Learners’ questions need to be archived or simulated to facilitate experts’ knowledge externalization.

–     To facilitate experts generating more knowledge content, it is possible to pair them with someone without any          domain knowledge. 

 (Updated in Jul, 2017)