Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Prediction of Key Symptoms of Learning Disabilities in School-Age Children Using Rough Sets

This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

Evaluación de la psicopatología del preescolar mediante el Early Childhood Inventory-4 (ECI-4): concordancia entre padres y maestros.= Assessment of psychopathology in preschool age children through the Early Childhood Inventory-4 (ECI-4): Agreement among parents and teachers

El objetivo principal de este estudio es conocer la concordancia entre informantes, padres y maestros, en cada una de las dimensiones o categorías diagnósticas del Early Childhood Inventory-4 (ECI-4). Además, se pretende analizar la influencia de la presencia de problemas de salud en los padres en la descripción y valoración de la conducta de una muestra de 204 alumnos de preescolar (3 a 6 años) de perfiles socioeconómicos diferentes. Los resultados indican que los padres tienden a valorar con mayor severidad los síntomas, observándose una mayor concordancia entre informantes en los relativos a los trastornos del desarrollo

Participle Preposing and Other Related Phenomena in Old Spanish and Old Catalan

El participi i altres fenòmens relacionats en el Castellà i el Català antic

Noise exposure in school-age children

This paper discusses a study to determine the average level of noise exposure for school children on a typical school day.

Strategies to prevent falls and fractures in hospitals and care homes and effect of cognitive impairment: systematic review and meta-analyses

OBJECTIVES: To evaluate the evidence for strategies to prevent falls or fractures in residents in care homes and hospital inpatients and to investigate the effect of dementia and cognitive impairment. DESIGN: Systematic review and meta-analyses of studies grouped by intervention and setting (hospital or care home). Meta-regression to investigate the effects of dementia and of study quality and design. DATA SOURCES: Medline, CINAHL, Embase, PsychInfo, Cochrane Database, Clinical Trials Register, and hand searching of references from reviews and guidelines to January 2005. RESULTS: 1207 references were identified, including 115 systematic reviews, expert reviews, or guidelines. Of the 92 full papers inspected, 43 were included. Meta-analysis for multifaceted interventions in hospital (13 studies) showed a rate ratio of 0.82 (95% confidence interval 0.68 to 0.997) for falls but no significant effect on the number of fallers or fractures. For hip protectors in care homes (11 studies) the rate ratio for hip fractures was 0.67 (0.46 to 0.98), but there was no significant effect on falls and not enough studies on fallers. For all other interventions (multifaceted interventions in care homes; removal of physical restraints in either setting; fall alarm devices in either setting; exercise in care homes; calcium/vitamin D in care homes; changes in the physical environment in either setting; medication review in hospital) meta-analysis was either unsuitable because of insufficient studies or showed no significant effect on falls, fallers, or fractures, despite strongly positive results in some individual studies. Meta-regression showed no significant association between effect size and prevalence of dementia or cognitive impairment. CONCLUSION: There is some evidence that multifaceted interventions in hospital reduce the number of falls and that use of hip protectors in care homes prevents hip fractures. There is insufficient evidence, however, for the effectiveness of other single interventions in hospitals or care homes or multifaceted interventions in care homes.

Polymorphisms in the apolipoprotein L1 gene and their effects on blood lipid and glucose levels in middle age males

Apolipoprotein L1 in plasma is associated with high- density lipoprotein. Novel APOL1 polymorphisms are investigated along with the association of two common haplotypes (Lys166Glu, Ile244Met, Lys271Arg) with circulating lipid and glucose levels. Although the amino acid substitutions occur in the amphipathic alpha helices region involved in lipid binding, these substitutions were found not to independently account for variability in circulating lipid and glucose levels in 149 middle age males.

Shaping literacy in the secondary school: policy, practice and agency in the age of the national literacy strategy

This article examines the definitions of literacy in operation in secondary schools, and the relationship between official literacy policy and the practices of the agents responsible for implementing this policy. We trace the history of national policy back to the Language Across the Curriculum movement of the 1970s as it provides an illustrative point of comparison with the first five years of the National Literacy Strategy. Drawing on empirical data which illuminate the views, perceptions and practices of key agents on a number of levels, we critically review the concept of 'school literacy' promoted in government policy, defining it as 'school-centric literacy' and question its ability to facilitate participation in the practices associated with the media and technological literacies which are increasingly a feature of school life. There is evidence of some unplanned effects of the current national policy but also that levels of agency, for literacy teachers in particular, may be rapidly diminishing.

Language, education and ethnicity: whose rights will prevail in an age of globalisation?

Education and ethnicity cannot be discussed without taking language into account. This paper will argue that any discussion of ethnic minorities cannot ignore the question of language, nor can any discussion of human rights ignore the question of language rights. Unfortunately, in today's globalised world, governments and minorities are faced with conflicting pressures: on the one hand, for the development and use of education in a global/international language; on the other for the use and development of mother tongue, local or indigenous languages in education. Language complexity and ethnic plurality were largely brought about as a result of the creation of nation-states, which were spread around the world as a result of European colonialism. European languages and formal education systems were used as a means of political and economic control. The legacy that was left by the colonial powers has complicated ethnic relations and has frequently led to conflict. While there is now greater recognition of the importance of language both for economic and educational development, as well as for human rights, the forces of globalisation are leading towards uniformity in the languages used, in culture and even in education. They are working against the development of language rights for smaller groups. We are witnessing a sharp decline in the number of languages spoken. Only those languages which are numerically, economically and politically strong are likely to survive. As a result many linguistic and ethnic groups are in danger of being further marginalised. This paper will illustrate this thesis both historically and from several contemporary societies, showing how certain policies have exacerbated ethnic conflict while others are seeking to promote harmony and reconciliation. Why this should be so will be explored. (c) 2006 Elsevier Ltd. All rights reserved.