Paper Info
Title
The Effectiveness of Personalization in Delivering E-learning Classes
Abstract
In this paper we present an evaluation methodology of personalized delivery of multimedia resources in an e-learning platform that takes advantage of web 2.0 technologies and its standards, such as (i) streaming using RSS and Atom feeds, (ii) searching using meta-data search engine, (iii) delivering using ubiquitous computing and (iv) personalized learning. Our framework consists of the following phases: (1) tracking the preferred delivery mechanism for each student model, (2) measuring the effect of the semantic profile time window parameter, (3) clustering students models based on similarity metrics on the delivery preferences and (4) comparing the results between personalized and non-personalized delivery. One important aspect of our approach is the combination of personalization and the data driven extraction (via clustering) of the students models based on similarity metrics. Our experimental results show that personalized delivery increases the usage of e-learning materials and the percentage of reviewing multimedia resources if these materials are delivered in ways that fit students preferences.
Year
DOI
Venue
2009
10.1109/ACHI.2009.10
Cancun
Keywords
Field
DocType
non-personalized delivery,similarity metrics,fit students preference,personalized learning,delivery preference,personalized delivery,e-learning classes,multimedia resource,clustering students model,students model,preferred delivery mechanism,electronic learning,data mining,search engine,clustering,algorithms,clustering algorithms,personalization,internet,ubiquitous computing
Data-driven,User profile,Computer science,Personalized learning,Ubiquitous computing,Cluster analysis,RSS,Multimedia,Personalization,The Internet
Conference
ISBN
Citations 
PageRank 
978-0-7695-3529-6
2
0.55
References 
Authors
7
3
Name
Order
Citations
PageRank
Leyla Zhuhadar114617.53
Elizabeth Romero2323.43
Robert Wyatt362.03