Research on Online Collaborative Problem-Solving in the Last 10 Years: Current Status, Hotspots, and Outlook—A Knowledge Graph Analysis Based on CiteSpace

Abstract

Collaborative problem-solving is a crucial skill to be developed in education. With the development of information technology, collaborative problem-solving in online environments has received increasing attention in recent years. There has been some foundation of research on computer-supported collaborative learning (CSCL) and collaborative problem-solving (CPS). They both have a focus, but there is a trend to combine them. Further understanding of the current state of research on online collaborative problem-solving is much needed. This study reviews 528 relevant papers from the last decade. The researchers summarized the current state of research and hotspots in online collaborative problem-solving based on the visual analysis of CiteSpace. It was found that the number of papers on online collaborative problem-solving is on the rise, with CPS and CSCL as the main research content and ‘feature extraction’, ‘task analysis’, and ‘computation modeling’ as the hot research topics in the past three years. The current research power on CPS and CSCL is mainly distributed in China and the United States, but the inter-institutional collaboration is little. Based on the research results, this paper proposes four future directions to improve the research in online collaborative problem-solving: identity awareness in online collaborative problem-solving, interdisciplinary online collaborative problem-solving, online collaborative problem-solving for teachers, and online collaborative problem-solving and ICT skills.

Knowledge Graph Construction Based on a Joint Model for Equipment Maintenance

“…KGs have the ability to organize and store large amounts of knowledge and can be divided into two categories: general KGs and domain KGs [9], of which general KGs are not limited to specific domains and cover a very wide range of knowledge, while domain-specific KGs are for specific domains such as finance, e-commerce or healthcare [2]. In comparison with general knowledge graphs, domain-specific knowledge graphs can be highly accurate due to their in-depth research and specialized knowledge, as they can capture the details and complexities of specific domains, which can provide more precise results.…”