Open Access   Article Go Back

Modeling the Learning Disabilities in Student Population

R. Jamuna1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-9 , Page no. 158-161, Sep-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i9.158161

Online published on Sep 30, 2019

Copyright © R. Jamuna . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: R. Jamuna, “Modeling the Learning Disabilities in Student Population,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.9, pp.158-161, 2019.

MLA Style Citation: R. Jamuna "Modeling the Learning Disabilities in Student Population." International Journal of Computer Sciences and Engineering 7.9 (2019): 158-161.

APA Style Citation: R. Jamuna, (2019). Modeling the Learning Disabilities in Student Population. International Journal of Computer Sciences and Engineering, 7(9), 158-161.

BibTex Style Citation:
@article{Jamuna_2019,
author = {R. Jamuna},
title = {Modeling the Learning Disabilities in Student Population},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2019},
volume = {7},
Issue = {9},
month = {9},
year = {2019},
issn = {2347-2693},
pages = {158-161},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4867},
doi = {https://doi.org/10.26438/ijcse/v7i9.158161}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i9.158161}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4867
TI - Modeling the Learning Disabilities in Student Population
T2 - International Journal of Computer Sciences and Engineering
AU - R. Jamuna
PY - 2019
DA - 2019/09/30
PB - IJCSE, Indore, INDIA
SP - 158-161
IS - 9
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
357 365 downloads 187 downloads
  
  
           

Abstract

The paper analyzes many learning disabilities prevalent in male and female sample student population which describes how the significance of the problems can be used to pinpoint the existence of educational problems related to health. A learning problem or disability can be seen as spanning a continuum from mild to severe. We will use the term “learning disability” to define the milder educational problems. The severity of the learning problem depends on the number and severity of processes affected. Statistics show that a large number of students are academically inhibited that they have trouble in holding their professional status also in later years. Many students all over the world suffer from some form of learning disability like arithmetic difficulties, verbal disability, memory retention disorders etc. Personal characteristics like introvert nature, inferiority complex, attention deficiency etc reduce their academic progresss. The social factors trigger these problems that they do not fit into their peer groups. They also exhibit learning disabilities due to biological factors like parents to sibling disorders, chromosomal disorders etc. It can also be due to psychological factors like lack of self confidence, lack of motivation, not adaptability etc. To model this problem we use Chi-square variate to find the independence of two attributes male students and female students category which forms two groups with the different number of students affected by the different disability causing factors. We assume the null hypothesis that the disabilities of two categories of students are independent of number of students affected by different factors. The calculated Chi-square value is less than the table value at 5 % level of significance. Hence the null hypothesis can be accepted. We can therefore conclude that male and female categories of students in the sample population taken are independent of the disability causing factors in each level.

Key-Words / Index Term

learning disabilities, null hypothesis, significance level, hereditary factors, Personal traits, Psychological factors, Social factors.

References

[1] Jain et al, “Computational Diagnosis of Learning Disability”, International Journal of Recent Trends in Engineering , Vol 2, No. 3, November 2009.
[2] H. Selvi, M.S. Saravanan on “Diagnosis of Dyslexia Students Using Classification Mining Techniques” , International Journal of Computer Sciences and Engineering Vol.-7, Issue-5, May 2019,
[3] Huntington D.D., Bender W.N. (1993) Adolescents with learning disabilities at risk? Emotional well being, depression, suicide. Journal of Learning Disabilities. 26, 159-166.
[4] A Survey on ADHD using Data Mining Techniques by M. Lalithambigai, A. Hema, online at: www. ijcse online.org
[5] Blumsack J., Lewandowski L., Waterman B. (1997) Neuro developmental precursors to learning disabilities: a preliminary report from a parent survey. Journal of Learning Disabilities. 30, 228 –237.
[6] Publication Manual. 5th. Washington, DC: American Psychological Association; 2006. American Psychological Association.
[7] Altman DG, Gore SM, Gardner MJ, Pocock SJ. Statistical guidelines for contributors to Medical journals. Br Med Journ. 1983; 286:1989–93. [PMC free article]
[8] Goodman SN. Toward evidence-based medical statistics: the P-value fallacy. Ann intern Med. 1999; 130:995–1004. Dr.R.Jamuna "Data Analytics and Predictions in Cell Phone usage" , International Journal in IT & Engineering (IJITE),Volume 6 Issue 1, page 22-27 ,January 2018 ISSN: 2321-1776 Impact Factor: 6.341, International Journal in IT & Engineering
[9] Dr.R.Jamuna "Data Analytics and Predictions in Cell Phone usage" , International Journal in IT & Engineering (IJITE),Volume 6 Issue 1, page 22-27 ,January 2018 ISSN: 2321-1776 Impact Factor: 6.341, International Journal in IT & Engineering.