Framework to Develop a Learning Analytics System for Smartphone Blended Learning Environment

Framework to Develop a Learning Analytics System for Smartphone Blended Learning Environment

Mazharuddin Syed Ahmed
DOI: 10.4018/978-1-5225-0256-2.ch004
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Abstract

Smartphones today are ubiquitous and universally influence our everyday life. Now, they are also creating a formidable impact as educational tools. The use of the smartphone specifically for mobile learning has exponentially increased the availability of big data in education. This data can be used for conducting Learning Analytics. Learning Analytics is a powerful tool that supports learners, instructors and institutions in better predicting and understanding a learner's performance and needs. The available tools and techniques used for Learning Analytics' are often not well-defined or well represented. This research proposes a four stage Learning Analytics framework which will aid in defining and understanding all the components of Learning Analytics in a smartphone-based blended learning environment. The proposed framework will be a useful guide for setting up Learning Analytics workflow or can be used to improve an existing system.
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Research Methodology

In this paper, we will discuss what Learning Analytics associated to smartphone is about, and propose an approach that comprises of proceeding successive steps, starting from the learning environment and ending with the appropriate interventions. This Learning Analytics life cycle was developed after gathering information about Learning Analytics taken from the literature review off scientific publications from the last four years. Furthermore, this research also explored at the current available frameworks and reference models claiming popularity in the fields of learning analytics. This motivated us to investigate further, in order to propose an approach that presents a framework as well as a life cycle. We took the idea of closing the cycle of the LA model, similar to the frameworks previously proposed by (Clow, 2012) and (Greller et al., 2012).

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