The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)
DOI: 10.1109/wi.2005.155
|View full text |Cite
|
Sign up to set email alerts
|

User Navigational Behavior in e-Learning Virtual Environments

Abstract: In this paper we describe the navigational behavior of the students of a e-learning virtual environment, in order to determine whether such navigational patterns are related to the academic performance achieved by the students or not, and which behaviors can be identified as more successful . IntroductionWeb mining is becoming a useful and common tool for institutions, as more and more data is collected from the users browsing the increasing number of web pages with interesting content. The validity of web mi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
14
0

Publication Types

Select...
4
3
1

Relationship

0
8

Authors

Journals

citations
Cited by 17 publications
(14 citation statements)
references
References 10 publications
0
14
0
Order By: Relevance
“…The navigational behavior of the students of a e-learning virtual environment are described three levels of behavior analysis of students such as session level, where students perform a few actions in a single session logged to the virtual campus; course level, where all single sessions are joined to form a course navigational pattern; and lifelong learning level, to analyze how students evolve from the beginning of a degree until they successfully finish it each academic semester (Carbó et al 2005). Based on web browsing semantics, users' behaviors are classified (Bousbia et al 2010) and adapted navigation typology (Canter et al 1985).…”
Section: Learner Behavior Analysismentioning
confidence: 99%
“…The navigational behavior of the students of a e-learning virtual environment are described three levels of behavior analysis of students such as session level, where students perform a few actions in a single session logged to the virtual campus; course level, where all single sessions are joined to form a course navigational pattern; and lifelong learning level, to analyze how students evolve from the beginning of a degree until they successfully finish it each academic semester (Carbó et al 2005). Based on web browsing semantics, users' behaviors are classified (Bousbia et al 2010) and adapted navigation typology (Canter et al 1985).…”
Section: Learner Behavior Analysismentioning
confidence: 99%
“…Movement pattern is only one of these strategies. Though this scenario is an "open" system among organisms, it is a "closed" system among online learners, in a sense that every action they perform is related to the learning process, and with a set of previously established goals (Carbo, Mor, and Minguillion, 2005). In addition, it can be inferred that different students follow different navigational patterns, but these patterns are limited to a few, mostly because of course structure, and temporal and technological restrictions (Carbo, Mor, & Minguillion, 2005).…”
Section: Introductionmentioning
confidence: 99%
“…information coming from automatic control processes, the uploading of graphical and format elements, etc.). However, after this pre-processing, about 1.8 GB of potentially useful information corresponding to 3,500,000 of log entries in average still remains [11].…”
Section: Processing Log Files From An On-line Distance Learning Campusmentioning
confidence: 99%