How social and semantic technologies can sustain employability through knowledge development and positive behavioral changes. (May 2017)

• Record Type: Journal Article
• Authors: Dascalu, Maria-Iuliana; Bodea, Constanta-Nicoleta; Tesila, Bianca; Moldoveanu, Alin; Ordoñez de Pablos, Patricia
• Is Part Of: Computers in human behavior. Volume 70(2017)
• Page Start: 507
• Page End: 517
• Publication Date: 2017-05
• Subjects: Employability -- Ontology-based recommendation -- Social connectors -- Virtual communities; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2017.01.026
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: The paper proposes an approach of enhancing knowledge workers'employability by inducing positive behavioral changes with the aid of current social and semantic technologies. Employability is seen as a psycho-social construct, connected to the development of knowing-how competencies and knowing-whom competencies, by continous learning and a rich social environment. The central element of the approach is a web-based platform - EmployLeaP, which facilitates adults' leap towards a better professional life and gives them the opportunity to find suitable professional e-communities, in which they can learn from their peers and feel appreciated. The recommendation algorithm for finding e-communities is ontology-driven and exploits information retrieved from social connectors anchored in the existent online learning ecosystem. In the same time, during learning within EmployLeaP communities, users' professional visibility is enhanced, by recommending them to job recruiters who also join the platform, in searching competent workers. The badge system used to reward exceptional behaviour within e-communities is the one ensuring users' visibility to recruiters and, in the same, increasing their self-confidence. Preliminary data related to experimental exploitation and perceived usefulness of the platform show promising results of using recent technologies in assisting individuals who want to increase their employability, as well as other stakeholders of knowledge society – recruiters or knowledge organizations. Highlights: We propose a platform to enhance knowledge workers'employability. The web platform targets both learners and recruiters. We use an ontology-based recommendation mechanism for learning communities. The platform was experimentally exploited and positive feedback was registered. An online survey of 391 students showed a high degree of perceived usefulness.