Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/2903

 Title: On Learning in a Smart City Environment Authors: Nikolov, RoumenShoikova, ElenaKrumova, MilenaKovatcheva, EugeniaDimitrov, VelianChikalanov, Alexander Keywords: Smart CitySmart Learning EnvironmentFull Context AwarenessBig Data and Learning AnalyticsAutonomous Decision-MakingSECILearning ScenarioForging Online Education Through FIRE Issue Date: 2015 Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences Citation: Serdica Journal of Computing, Vol. 9, No 3-4, (2015), 223p-240p Abstract: Advances in technology in recent years have changed the learning behaviours of learners and reshaped teaching methods and learning environments. This paper overviews a foundational framework and provides models for planning and implementing smart learning environments. Gartner’s 2015 Hype Cycle for Emerging Technologies identifies the computing innovations such as Internet of Things, Advanced Analytics, Machine Learning, Wearables, etc., that organisations should monitor. Learners and students, being the future drivers of these industries, are the main human resource to fulfil the vacancies of these work forces. Constant improvements and re-evaluation of the curriculum has to be done regularly to keep the learners up-to-date in meeting the requirements of these industries and corporations. Universities benefit from these thinking-outside-the-box practices by equipping students with work force experience that involves more hands-on tasks with real-life infrastructures. The introduction is focused on analysis of emerging industries and new types of jobs that require future personnel to be well equipped to meet the expansion requirements of these industries and keep up with their development needs. Section 2 looks at the future Internet domain landscape that comprises a great diversity of technology related topics involved in the implementation of Smart Learning Environments. The purpose of section 3 is to overview a foundational framework and major considerations for the planning and implementation of smart learning environments, behind which is the convergence of advances and developments in social constructivism, psychology, and technology. Section 4 introduces the smart learning models which are developed to reflect the dynamic knowledge conversion processes in technology enabled smart learning environments. The last section presents a case study of a learning scenario entitled “Monitoring the environmental parameters in a Smart City” as an illustration of experimental learning on Internet of Things, which proofs the power of the FORGE (Forging Online Education through FIRE) FP7 project methodology and infrastructure for building remote labs and delivering them to students. ACM Computing Classification System (1998): K.3.2. URI: http://hdl.handle.net/10525/2903 ISSN: 1312-6555 Appears in Collections: Volume 9 Number 3-4

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