The Educational Intelligent Economy – Lifelong Learning – A vision for the future

Almost every detail of our lives, where we go, what we do, and with whom is captured as digital data. Technological advancements in cloud computing, artificial intelligence, and data analytics offer the education sector new ways not only to improve policy and processes but also to personalize learning and teaching practice. However, these changes raise fundamental questions around who owns the data, how it might be used, and the consequences of use. The application of Big Data in education can be directed toward a wide range of stakeholders, such as educators, students, policy-makers, institutions, or researchers. It may also have different objectives, such as monitoring, student support, prediction, assessment, feedback, and personalization. This chapter presents the nuances and recent research trends spurred by technological advancements that ave influenced the education sector and highlights the need to look beyond the technical boundaries using a socio-semiotic lens. With the explosion of available information and digital technologies pervading cultural, social, political as well as economic spaces, being a lifelong learner is pivotal for success. However, technology on its own is not sufficient to drive this change. For technology to be successful, it should complement individual learning cultures and education systems. This chapter is broadly divided into two main sections. In the first section, we contemplate a vision for the future, which is deemed possible based on ongoing digital and computing advancements. The second section elaborates the technological, pedagogical, cultural, and political requirements to attain that vision

The history, evolution, and future of big data & analytics:A bibliometric analysis of its relationship to performance in organizations

Big data and analytics (BDA) are gaining momentum, particularly in the practitioner world. Research linking BDA to improved organizational performance seems scarce and widely dispersed though, with the majority focused on specific domains and/or macro-level relationships. In order to synthesize past research and advance knowledge of the potential organizational value of BDA, the authors obtained a data set of 327 primary studies and 1252 secondary cited papers. This paper reviews this body of research, using three bibliometric methods. First, it elucidates its intellectual foundations via co-citation analysis. Second, it visualizes the historical evolution of BDA and performance research and its substreams through algorithmic historiography. Third, it provides insights into the field's potential evolution via bibliographic coupling. The results reveal that the academic attention for the BDA-performance link has been increasing rapidly. The study uncovered ten research clusters that form the field's foundation. While research seems to have evolved following two main, isolated streams, the past decade has witnessed more cross-disciplinary collaborations. Moreover, the study identified several research topics undergoing focused development, including financial and customer risk management, text mining and evolutionary algorithms. The review concludes with a discussion of the implications for different functional management domains and the gaps for both research and practice.</p

Capturing the sounds of an urban greenspace

Acoustic data can be a source of important information about events and the environment in modern cities. To date, much of the focus has been on monitoring noise pollution, but the urban soundscape contains a rich variety of signals about both human and natural phenomena. We describe the CitySounds project, which has installed enclosed sensor kits at several locations across a heavily used urban greenspace in the city of Edinburgh. The acoustic monitoring components regularly capture short clips in real-time of both ultrasonic and audible noises, for example encompassing bats, birds and other wildlife, traffic, and human. The sounds are complemented by collecting other data from sensors, such as temperature and relative humidity. To ensure privacy and compliance with relevant legislation, robust methods render completely unintelligible any traces of voice or conversation that may incidentally be overheard by the sensors. We have adopted a variety of methods to encourage community engagement with the audio data and to communicate the richness of urban soundscapes to a general audience