Abstract
The new generation teaching-learning pedagogy has created a complete paradigm shift wherein the teaching is no longer confined to giving the content knowledge, rather it fosters the “how, when and why” of applying this knowledge in real world scenarios. By exploiting the advantages of deep learning technology, this pedagogy can be further fine-tuned to develop a repertoire of teaching strategies. This paper presents a secured and agile architecture of an Internet of Everything (IoE) based Educational Model and a Learning Analytics System (LAS) model using the concept of deep learning which can be used to gauge the degree of learning, retention and achievements of the learners and suggests improvements and corrective measures. The paper also puts forward the advantages, applications and challenges of using deep learning techniques for gaining insights from the data generated from the IoE devices within the educational domain for creating such learning analytics systems. Finally a feature wise comparison is provided between the proposed Learning Analytics (LA) based approach and conventional teaching-learning approach in terms of performance parameters like cognition, attention, retention and attainment of learners.
Highlights
Since the inception of ‘Internet of Everything (IoE)’ technology, the computing paradigm has totally transformed
This paper presents an IoE based Educational model and discusses the applications, advantages and challenges of using deep learning techniques to develop a learning analytics system by effectively using the IoE big data for taking better and efficient decisions within the educational domain
Apart from learning analytics, the general applications of proposed deep learning based IoE Architecture can be among the following (Yaron, 2017; MathWorks, 2017; Schmidhuber, 2015; Najafabadi et al, 2015): Text to speech and speech recognition system With effective deep learning techniques we can construct systems which are capable of recognizing the voice in a best possible way like never before
Summary
Since the inception of ‘Internet of Everything (IoE)’ technology, the computing paradigm has totally transformed. A typical IoE system is a collection of large number of devices which are wirelessly connected with each other and the base station These devices are embedded with micro-chip based sensors, actuators and transponders for performing the task of sensing, storing and forwarding the information about themselves and their surroundings (Jara et al, 2013; Ashton, 2009; Miraz et al, 2015). The sensors in these devices sense and capture the information about themselves and their surrounding environment and send it to the base station (or sink) for further processing These sensors produce a huge amount of data which travels from source to destination and vice versa using a wireless medium, in order to secure this data, we propose to encrypt the data using Twofish Cryptographic technique (Whiting & Schneier, 1998; Schneier et al, 1998; Schneier et al, 1999).
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