Strategies and Techniques for Teaching Children with Learning Disabilities: A Case Study of the Spring Reading Program

This case study explored strategies and techniques in order to assist individuals with learning disabilities in their academic achievement. Of particular focus was how a literacy-based program, titled The Spring Reading Program, utilizes effective tactics and approaches that result in academic growth. The Spring Reading Program, offered by the Learning Disabilities Association of Niagara Region (LDANR) and partnered with John McNamara from Brock University, supports children with reading disabilities academically. In addition, the program helps children increase their confidence and motivation towards literacy. I began this study by outlining the importance of reading followed by and exploration of what educators and researchers have demonstrated regarding effective literacy instruction for children with learning disabilities. I studied effective strategies and techniques in the Spring Reading Program by conducting a qualitative case study of the program. This case study subsequently presents in depth, 4 specific strategies: Hands-on activities, motivation, engagement, and one-on-one instruction. Each strategy demonstrates its effectiveness through literature and examples from the Spring Reading Program.

The FCLT with Dependent Errors: an Helicopter Tour of the Quality of the Approximation

This note investigates the adequacy of the finite-sample approximation provided by the Functional Central Limit Theorem (FCLT) when the errors are allowed to be dependent. We compare the distribution of the scaled partial sums of some data with the distribution of the Wiener process to which it converges. Our setup is purposely very simple in that it considers data generated from an ARMA(1,1) process. Yet, this is sufficient to bring out interesting conclusions about the particular elements which cause the approximations to be inadequate in even quite large sample sizes.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

New method of learning to read write and speak the spanish language; with an appendix : y M. Velazquez and T. Simonne

UANL

Bodies, stories, cities : learning to read and write (in) Montréal with Gail Scott

Cette lecture, tant critique, comparative, et théorique que pédagogique, s’ancre dans le constat, premièrement, qu’il advient aux étudiantEs en littérature de se (re)poser la question des coûts et complicités qu’apprendre à lire et à écrire présuppose aujourd’hui; deuxièmement, que nos pratiques littéraires se trament au sein de lieux empreints de différences, que l’on peut nommer, selon le contexte, métaphore, récit, ville; et, troisièmement, que les efforts et investissements requis sont tout autant couteux et interminable qu’un plaisir et une nécessité politique. Ces conclusions tendent vers l’abstrait et le théorique, mais le langage en lequel elles sont articulées, langage corporel et urbain, de la dépendance et de la violence, cherche d’autant plus une qualité matérielle et concrète. Or, l’introduction propose un survol des lectures et comparaisons de Heroine de Gail Scott qui centre ce projet; identifie les contextes institutionnels, historiques, et personnels qui risquent, ensuite, de décentrer celui-ci. Le premier chapitre permet de cerner le matérialisme littéraire qui me sert de méthode par laquelle la littérature, à la fois, sollicite et offre une réponse à ces interrogations théoriques. Inspirée de l’œuvre de Gail Scott et Réjean Ducharme, premièrement, et de Walter Benjamin, Elisabeth Grosz, et Pierre Macherey ensuite, ‘matérialisme’ fait référence à cette collection de figures de pratiques littéraires et urbaines qui proviennent, par exemple, de Georges Perec, Michel DeCerteau, Barbara Johnson, et Patricia Smart, et qui invitent ensuite une réflexions sur les relations entre corporalité et narrativité, entre la nécessité et la contingence du littéraire. De plus, une collection de figures d’un Montréal littéraire et d’une cité pédagogique, acquis des œuvres de Zygmunt Bauman, Partricia Godbout, et Lewis Mumford, constitue en effet un vocabulaire nous permettant de mieux découvrir (et donc enseigner) ce que lire et apprendre requiert. Le deuxième chapitre propose une lecture comparée de Heroine et des romans des auteures québécoises Anne Dandurand, Marie Gagnon, et Tess Fragoulis, dans le contexte, premièrement, les débats entourant l’institutionnalisation de la littérature (anglo)Québécoise et, deuxièmement, des questions pédagogiques et politiques plus larges et plus urgentes que nous pose, encore aujourd’hui, cette violence récurrente qui s’acharna, par exemple, sur la Polytechnique en 1989. Or, cette intersection de la violence meurtrière, la pratique littéraire, et la pédagogie qui en résulte se pose et s’articule, encore, par le biais d’une collection de figures de styles. En fait, à travers le roman de Scott et de l’œuvre critique qui en fait la lecture, une série de craques invite à reconnaître Heroine comme étant, ce que j’appelle, un récit de dépendance, au sein duquel se concrétise une temporalité récursive et une logique d’introjection nous permettant de mieux comprendre la violence et, par conséquent, le pouvoir d’une pratique littéraire sur laquelle, ensuite, j’appuie ma pédagogie en devenir. Jetant, finalement, un regard rétrospectif sur l’oeuvre dans son entier, la conclusion de ce projet se tourne aussi vers l’avant, c’est-à-dire, vers ce que mes lectures dites matérialistes de la littérature canadienne et québécoise contribuent à mon enseignement de la langue anglaise en Corée du Sud. C’est dans ce contexte que les propos de Jacques Rancière occasionnent un dernier questionnement quant à l’historique des débats et des structures pédagogiques en Corée, d’une part, et, de l’autre, les conclusions que cette lecture de la fiction théorique de Gail Scott nous livre.

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

Test for basis-set errors in relativistic Dirac-Fock-Slater calculations with a numerical AO-DFS-basis

A fully relativistic four-component Dirac-Fock-Slater program for diatomics, with numerically given AO's as basis functions is presented. We discuss the problem of the errors due to the finite basis-set, and due to the influence of the negative energy solutions of the Dirac Hamiltonian. The negative continuum contributions are found to be very small.

Integration of adults with learning dificulties in educational centres. 'Integraci??n de adultos con dificultades de aprendizaje en centros educativos'

Esta gu??a ha contado con el apoyo del Programa S??crates de la Comisi??n Europea y es una traducci??n al ingl??s editada separadamente de la versi??n espa??ola

Teaching an Old Robot New Tricks: Learning Novel Tasks via Interaction with People and Things

As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.

Evaluating Greek primary school textbooks used to teach students with learning disabilities

Evaluaci??n de los libros de texto de Educaci??n Primaria griegos utilizados en la ense??anza de los estudiantes con dificultades de aprendizaje. La evaluaci??n de los libros de texto en cuanto a su cumplimiento de las normas basadas en la evidencia de dise??o instruccional, y en cuanto a su idoneidad para acomodar las diversas necesidades educativas de los diversos grupos de la poblaci??n escolar, se considera un medio importante de mejorar la calidad de los servicios educativos incluyendo a estudiantes con discapacidades de aprendizaje. En el presente trabajo, se explican los resultados de las evaluaciones de los libros de texto de Lengua y Matem??ticas que se utilizan en los tres primeros grados de la escuela griega primaria para ense??ar a los estudiantes con y sin dificultades de aprendizaje. La evaluaci??n se bas?? en los siguientes criterios: claridad de objetivos de instrucci??n, el examen de conocimientos previos, explicitaci??n de las explicaciones de instrucci??n, la suficiencia de los ejemplos de ense??anza, la introducci??n de conceptos adicionales y capacidades, la adecuaci??n de la pr??ctica guiada, la eficacia de la pr??ctica independiente, y la adecuaci??n de los conocimientos. Seg??n los resultados, los libros de texto no cumplen en cuatro de los ocho criterios revisados, en concreto los criterios de la claridad de los objetivos de instrucci??n, la explicitud de las explicaciones de instrucci??n, la introducci??n de conceptos adicionales y habilidades, y la conveniencia de revisar los conocimientos. Bas??ndose en estos resultados, el punto de vista puede considerarse que los libros de texto evaluados presentan considerables deficiencias e insuficiencias, lo que exige la aplicaci??n de modificaciones sustanciales en varios par??metros de dise??o de la instrucci??n cuando se utilizan para ense??ar a los estudiantes con dificultades de aprendizaje. Se discuten los efectos de estas deficiencias.

Attention, memory and verbal learning and their relation to schizotypal traits in unaffected parents of schizophrenic patients

The main objective of this ex post facto study is to compare the differences in cognitive functions and their relation to schizotypal personality traits between a group of unaffected parents of schizophrenic patients and a control group. A total of 52 unaffected biological parents of schizophrenic patients and 52 unaffected parents of unaffected subjects were assessed in measures of attention (Continuous Performance Test- Identical Pairs Version, CPT-IP), memory and verbal learning (California Verbal Learning Test, CVLT) as well as schizotypal personality traits (Oxford-Liverpool Inventory of Feelings and Experiences, O-LIFE). The parents of the patients with schizophrenia differ from the parents of the control group in omission errors on the Continuous Performance Test- Identical Pairs, on a measure of recall and on two contrast measures of the California Verbal Learning Test. The associations between neuropsychological variables and schizotpyal traits are of a low magnitude. There is no defined pattern of the relationship between cognitive measures and schizotypal traits

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed