Statistical analysis of performance of learning disabled students
dc.contributor.committeeChair | Matis, Timothy I. | |
dc.contributor.committeeMember | Smith, Milton L. | |
dc.creator | Jain, Sonal | |
dc.date.available | 2012-06-01T14:22:49Z | |
dc.date.issued | 2006-12 | |
dc.degree.department | Industrial and Systems Engineering | |
dc.description.abstract | Learning disabilities and attention-deficit/hyperactivity disorder are characterized to be the most common problems seen by child neurologists, neuropsychologists and developmental pediatricians, comprising a major percentage of referrals from parents and teachers. College students with learning disabilities and attention-deficit/hyperactivity have average or above levels of intellectual functioning despite the inability to learn specific academic skills. For learners of different needs tutoring proves to be the most beneficial with the individualization it offers. Peer tutoring has proved to be such technique providing educational benefits to both the tutor and the tutee. Regression analysis proves to be an effective technique to determine the combined effects of parameters affecting the performance of college students. The study involves cognitive analysis of students' accomplishment in academics with documented learning disability and/or attention deficit/hyperactivity disorder from Texas Tech University. Performance parameters are considered over four consecutive semesters concentrating on long semesters of fall and spring. | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | http://hdl.handle.net/2346/8849 | |
dc.language.iso | eng | |
dc.rights.availability | Unrestricted. | |
dc.subject | Attention deficit hyperactivity disorder (ADHD) | |
dc.subject | Learning disability | |
dc.subject | Analysis | |
dc.subject | Regression | |
dc.title | Statistical analysis of performance of learning disabled students | |
dc.type | Thesis | |
thesis.degree.department | Industrial and Systems Engineering | |
thesis.degree.department | Industrial Engineering | |
thesis.degree.discipline | Industrial and Systems Engineering | |
thesis.degree.grantor | Texas Tech University | |
thesis.degree.level | Masters | |
thesis.degree.name | Master of Science |
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