Regression analysis on agent roles in personal knowledge management processes: Significance of a connect agent in mediating human's personal knowledge management

• Main Authors: Ismail S., Ahmad M.S., Hassan Z.
• Other Authors: 57225447357
• Format: Conference paper
• Published: IEEE Computer Society 2023
• Subjects: cognitive enablers; GUSC model; nodal approach; personal knowledge management; software agent technology; Factor analysis; Knowledge management; Research and development management; Software agents; Agent roles; Cognitive enabler; Computer technology; Internet technology; Knowledge management process; Nodal approach; Personal knowledge management; Research domains; Software agent technology; Regression analysis
• Institution: Universiti Tenaga Nasional

Across the literature, there is a gradual development of research on personal knowledge management (PKM) from theoretical to technical perspective on managing personal knowledge over the computer and internet technologies. This research domain has aroused the interest of researchers in Malaysia with the introduction of a PKM model to accommodate the understanding of PKM among knowledge workers. In this model, called the GUSC model, there are four main processes, which are get knowledge, understand knowledge, share knowledge and connect to knowledge sources. This model entails four cognitive enablers that are proposed to mediate the PKM processes. This paper analyses the quantitative data on the GUSC model to further understand the roles of software agents in mediating human's PKM processes. It also analyses the role of cognitive enablers as mediating factors for the PKM processes, which are seen as potential strong notions for software agency. The results of the analysis show the significance of 'connect' as a role of an agent that depends on the rest of the factors. Based on the quantitative findings, it is recommended that the GUSC model is used to conceptualise an agent-based system, with cognitive enablers to determine the appropriate BDI structure for the system. � 2013 IEEE.