Application of Artificial Neural Network to the identification of students with learning disabilities

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Due to the implicit characteristics of learning disabilities (ID), the identification or diagnosis of students with learning disabilities has long been a difficult issue. In fact, there is little consensus about what is the best procedure to identify a person with LD. Instead, the procedures are based on empirical findings from scholarly research. In this paper, we try to adopt Artificial Neural Network technique, which has been applied successfully to solve problems in numerous fields, to the ID identification and diagnosis problem. The preliminary results are satisfactory and can be provided as second opinion to the ID evaluation personnel. But it still requires many efforts to make the model more accurate and to make the idea practically feasible, which is what we will be working on.

Original languageEnglish
Title of host publicationProceedings of the 2006 International Conference on Artificial Intelligence, ICAI'06
Pages162-168
Number of pages7
Publication statusPublished - 2006 Dec 1
Event2006 International Conference on Artificial Intelligence, ICAI'06 - Las Vegas, NV, United States
Duration: 2006 Jun 262006 Jun 29

Publication series

NameProceedings of the 2006 International Conference on Artificial Intelligence, ICAI'06
Volume1

Other

Other2006 International Conference on Artificial Intelligence, ICAI'06
CountryUnited States
CityLas Vegas, NV
Period06-06-2606-06-29

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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  • Cite this

    Wu, T. K., Meng, Y. R., & Huang, S. C. (2006). Application of Artificial Neural Network to the identification of students with learning disabilities. In Proceedings of the 2006 International Conference on Artificial Intelligence, ICAI'06 (pp. 162-168). (Proceedings of the 2006 International Conference on Artificial Intelligence, ICAI'06; Vol. 1).