Abstract:

The global socio-economic challenges place demands on the 21st Century higher education to use advancements in digital technologies and big data analytics to enable personalized learning experiences under value-added smart educational models. The campus-based education is morphing into a more virtual collaborative learning environment where learners are empowered to select the best model compatible with their preferred learning style, and to connect to social communities where they can build cumulative knowledge and advance their professional skills. The emergence of Industry 4.0 concept brings together Edge/Fog Computing, Cyber-Physical Systems (CPS(, the Internet of Things (IoT), the Internet of Services (IoS), and Big Data to synthesize intelligent applications and adaptive services for smarter environments. This paper proposes an architectural model that integrates Industry 4.0 technologies with social and behavioral analytics to unite likeminded learners with common career prospects and expert mentors for collaborative cognitive attainment. The proposed model collects various types of data about learners and learning settings from different sources. This collected data is aggregated and analyzed to profile learners and identify learning-related dispositions, performance, and long term career objectives of individual learners. The analytical results are used to design and deliver proactive services to address diagnosed deficiencies and advance performance. The model also captures socio-demographic features and interests of individual learners and use these properties to model behaviors and discover common patterns in order to augment a dynamic social network structure. This social framework creates a virtual community of learners who share implicit and explicit experiences to constitute new knowledge and expand their creative thinking capabilities. The proposed model is extended with social influence mining and persuasive approaches to increase the diffusion of desired learning behaviors and facilitate communication between learners and market environments about career prospects. The paper also discusses the challenges and key factors for a successful realization of the model in higher education settings.

Keywords:

4.0 Technologies, Higher Education, Smart Learning, Social and Behavioral Analysis.