Automatic Detection Techniques to Detect E-Learners on E-Learning System: A Comparative Analysis

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J. U. F. RAJPER
S. RAJPER
S. JALBANI
B.BALOCH

Abstract

: E-learning is an Information and Communication technology (ICT) weaved distance education. Users of e-learning systems have now paved into the era of web 3.0 after web 1.0 and web 2.0. But, still the e-learners’ user modeling is a research demanding dimension. From personalized e-learning systems to Recommender e-learning systems, user modeling is required. For user modeling, elearners’ detection on web based learning systems are required. The objective of this study is to review the research studies in this most demanding research dimension of e-learning. This survey of research studies will be conducted to review past research studies from 2000-2016. The survey will be helpful to compare and classify the ADLS (Automatic learning styles’ detecting techniques) and detect most robust techniques. Because it is revealed that to identify a robust technique for starting research study by researchers, scholars is very tedious and time taken job. This research study will contribute to scholars, academicians and e-learning community

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How to Cite
J. U. F. RAJPER, S. RAJPER, S. JALBANI, & B.BALOCH. (2017). Automatic Detection Techniques to Detect E-Learners on E-Learning System: A Comparative Analysis . Sindh University Research Journal - SURJ (Science Series), 49(3). https://doi.org/10.26692/surj.v49i3.1513
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