Sign up & Download
Sign in

Automatic Website Comprehensibility Evaluation

by Ping Yan, Zhu Zhang, Ray Garcia
WI 07 Proceedings of the IEEEWICACM International Conference on Web Intelligence (2007)

Abstract

The Web provides easy access to a vast amount of informational content to the average person, who may often be interested in selecting websites that best match their learning objectives and comprehensibility level. Web content is generally not tagged for easy determination of its instructional appropriateness and comprehensibility level. Our research develops an analytical model, using a group of website features, to automatically determine the comprehensibility level of a website. These features, selected from a large pool of website features quantitatively measured, are statistically shown to be significantly correlated to website comprehensibility based on empirical studies. The automatically inferred comprehensibility index may be used to assist the average person, interested in using web content for self-directed learning, to find content suited to their comprehension level and filter out content which may have low potential instructional value.

Cite this document (BETA)

Sign up today - FREE

Mendeley saves you time finding and organizing research. Learn more

  • All your research in one place
  • Add and import papers easily
  • Access it anywhere, anytime

Start using Mendeley in seconds!

Already have an account? Sign in

Readership Statistics

6 Readers on Mendeley
by Discipline
 
by Academic Status
 
33% Student (Master)
 
33% Ph.D. Student
 
17% Student (Postgraduate)
by Country
 
33% Germany
 
33% United States
 
17% United Kingdom