Educational Data Mining pp 411-439

Part of the Studies in Computational Intelligence book series (SCI, volume 524)

Data Mining and Social Network Analysis in the Educational Field: An Application for Non-Expert Users

  • Diego García-Saiz
  • Camilo Palazuelos
  • Marta Zorrilla
Chapter

Abstract

With the increasing popularity of social networking services like Facebook, social network analysis (SNA) has emerged again. Undoubtedly, there is an inherent social network in any learning context, where teachers, learners, and learning resources behave as main actors, among which different relationships can be defined, e.g., “participate in” among blogs, students, and learners. From their analysis, information about group cohesion, participation in activities, and connections among subjects can be obtained. At the same time, it is well-known the need of tools that help instructors, in particular those involved in distance education, to discover their students’ behavior profile, models about how they participate in collaborative activities or likely the most important, to know the performance and dropout pattern with the aim of improving the teaching–learning process. Therefore, the goal of this chapter is to describe our e-learning Web Mining tool and the new services that it provides, supported by the use of SNA and classification techniques.

Keywords

Data mining Educational data mining Social network analysis Learning analytics 

Abbreviations

API

Application programming interface

DM

Data mining

EDM

Educational data mining

ElWM

e-learning web miner

KDD

Knowledge discovery in databases

LA

Learning analytics

LMS

Learning management system

MOOC

Massive open online course

SNA

Social network analysis

SOA

Service-oriented architecture

SOAP

Simple object access protocol

UC

University of Cantabria

WSDL

Web services description language

WS

Web service

XML

eXtended Markup Language

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Diego García-Saiz
    • 1
  • Camilo Palazuelos
    • 1
  • Marta Zorrilla
    • 1
  1. 1.Department of Mathematics, Statistics, and Computer ScienceUniversity of CantabriaSantanderSpain

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