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Title Raspberry Pi And Role Of Iot In Education
ID_Doc 44170
Authors Mahmood S.; Palaniappan S.; Hasan R.; Sarker K.U.; Abass A.; Rajegowda P.M.
Year 2019
Published 2019 4th MEC International Conference on Big Data and Smart City, ICBDSC 2019
DOI http://dx.doi.org/10.1109/ICBDSC.2019.8645598
Abstract In this era of high and fast-moving technology, students are more demanding and willing to use innovative learning methods, also, they will be Seeing forward to living and surviving in the new environment of a smart classroom. This subject gives a framework to clarify how it can be utilized to institute a smart and innovative university campus life to improve the delivery and efficiency of everyday activities with consideration of the social and environmental interactions, and hence provide not only a smart but likewise, a sustainable campus. The use of the internet of things (IOT) is able to exchange and make use of information for students' participation and interaction with the class fellows and teachers in a very suitable way. For the educational assessment of a student's interaction, the measurement of student attentiveness is an indispensable component of it. The need for a high method for assessment also arises in the development of new technology in the mode of a new style of learning. The students experience in using the LMS Moodle for e-learning (electronic learning) so that the students get the full advantage by interacting of this technology and their learning skills increase to a high-level by using learning analytics as discussed in this report. The story explores the applicability of the Raspberry Pi development board or single board computer for teaching enhancement, IoT technologies and environments. The goal of this research is to identify and propose low-cost, efficient and flexible platform which can assist in introducing the IoT paradigm in the teaching process, as considerably as to offer the Provision to fellow students about social behavior and fellow's approachability by using Learning Management System (LMS). © 2019 IEEE.
Author Keywords Big Data; IoT; Learning Analytics; Learning Management System; Raspberry Pi; Smart Classroom


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