Socioculture and Cognitivist Perspectives on Language and Communication Barriers in Learning

It is believed that major account on language diversity must be taken in learning, and especially in learning using ICT. This paper-s objective is to exhibit language and communication barriers in learning, to approach the topic from socioculture and cognitivist perspectives, and to give exploratory solutions of handling such barriers. The review is mainly conducted by approaching the journal Computers & Education, but also an initially broad search was conducted. The results show that not much attention is paid on language and communication barriers in an immediate relation to learning using ICT. The results shows, inter alia, that language and communication barriers are caused because of not enough account is taken on both the individual-s background and the technology.

Teaching English under the LMD Reform: The Algerian Experience

Since its independence in 1962, Algeria has struggled to establish an educational system tailored to the needs of the population it may address. Considering the historical connection with France, Algeria has always looked at the French language as a cultural imperative until late in the seventies. After the Arabization policy of 1971 and the socioeconomic changes taking place worldwide, the use of English as a communicating vehicle started to gain more space within globalized Algeria. Consequently, disparities in the use of French started to fade away at the cross-roads leaving more space to the teaching of English as a second foreign language. Moreover, the introduction of the Bologna Process and the European Credit Transfer System in Higher Education has necessitated some innovations in the design and development of new curricula adapted to the socioeconomic market. In this paper, I will try to highlight the important historical dimensions Algeria has taken towards the implementation of an English language methodology and to the status it acquired from second foreign language, to first foreign language to “the language of knowledge and sciences". I will also propose new pedagogical perspectives for a better treatment of the English language in order to encourage independent and autonomous learning.

The SAFRS System : A Case-Based Reasoning Training Tool for Capturing and Re-Using Knowledge

The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.

A Computer Model of Language Acquisition – Syllable Learning – Based on Hebbian Cell Assemblies and Reinforcement Learning

Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.

The Design of English Materials to communication the Identity of Amphawa District, Samut Songkram Province, for Sustainable Tourism

The main purpose of this research was to study how to communicate the identity of the Amphawa district, Samut Songkram province for sustainable tourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: 1. The identity of the Amphawa District, Samut Songkram province is the area controlled by Amphawa sub district (submunicipality). The working unit which runs and looks after Amphawa sub district administration is known as the Amphawa mayor. This establishment was built to be a resort for normal people and tourists visiting the Amphawa district near the Maekong River consisting of rest accommodations. Along the river there is a restaurant where food and drinks are served, rich mangrove forests, a learning center, fireflies and cork trees. The Amphawa district was built to honor and commemorate King Rama II and is where the greatest number of fireflies and cork trees can be seen in Thailand from May to October each year. 2. The communication of the identity of Amphawa District, Samut Songkram Province which the researcher could find and design to present in English materials can be summed up in 5 items: 1) The history of the Amphawa District, Samut Songkram province 2) The history of King Rama II Memorial Park 3) The identity of Amphawa Floating Market 4) The Learning center of Ecosystem: Fireflies and Cork Trees 5) How to keep Amphawa District, Samut Songkram Province for sustainable tourism.

The Efficacy of Neurological Impress Method and Repeated Reading on Reading Fluency of Children with Learning Disabilities in Oyo State, Nigeria

The purpose of this study was to find out the effectiveness of neurological impress method and repeated reading technique on reading fluency of children with learning disabilities. Thirty primary four pupils in three public primary schools participated in the study. There were two experimental groups and a control. This research employed a 3 by 2 factorial matrix and the participants were taught for one session. Two hypotheses were formulated to guide the research. T-test was used to analyse the data gathered, and data analysis revealed that pupils exposed to the two treatment strategies had improvement in their reading fluency. It was recommended that the two strategies used in the study can be used to intervene in reading fluency problems in children with learning disabilities.

Learning and Teaching in the Panopticon:Ethical and Social Issues in Creating a Virtual Educational Environment

This paper examines ethical and social issues which have proved important when initiating and creating educational spaces within a virtual environment. It focuses on one project, identifying the key decisions made, the barriers to new practice encountered and the impact these had on the project. It demonstrates the importance of the 'backstage' ethical and social issues involved in the creation of a virtual education community and offers conclusions, and questions, which will inform future research and practice in this area. These ethical issues are considered using Knobel-s framework of front-end, in-process and back-end concerns, and include establishing social practices for the islands, allocating access rights, considering personal safety and supporting researchers appropriately within this context.

BIDENS: Iterative Density Based Biclustering Algorithm With Application to Gene Expression Analysis

Biclustering is a very useful data mining technique for identifying patterns where different genes are co-related based on a subset of conditions in gene expression analysis. Association rules mining is an efficient approach to achieve biclustering as in BIMODULE algorithm but it is sensitive to the value given to its input parameters and the discretization procedure used in the preprocessing step, also when noise is present, classical association rules miners discover multiple small fragments of the true bicluster, but miss the true bicluster itself. This paper formally presents a generalized noise tolerant bicluster model, termed as μBicluster. An iterative algorithm termed as BIDENS based on the proposed model is introduced that can discover a set of k possibly overlapping biclusters simultaneously. Our model uses a more flexible method to partition the dimensions to preserve meaningful and significant biclusters. The proposed algorithm allows discovering biclusters that hard to be discovered by BIMODULE. Experimental study on yeast, human gene expression data and several artificial datasets shows that our algorithm offers substantial improvements over several previously proposed biclustering algorithms.

Goal Based Episodic Processing in Implicit Learning

Research has suggested that implicit learning tasks may rely on episodic processing to generate above chance performance on the standard classification tasks. The current research examines the invariant features task (McGeorge and Burton, 1990) and argues that such episodic processing is indeed important. The results of the experiment suggest that both rejection and similarity strategies are used by participants in this task to simultaneously reject unfamiliar items and to accept (falsely) familiar items. Primarily these decisions are based on the presence of low or high frequency goal based features of the stimuli presented in the incidental learning phase. It is proposed that a goal based analysis of the incidental learning task provides a simple step in understanding which features of the episodic processing are most important for explaining the match between incidental, implicit learning and test performance.

Stereotype Student Model for an Adaptive e-Learning System

This paper describes a concept of stereotype student model in adaptive knowledge acquisition e-learning system. Defined knowledge stereotypes are based on student's proficiency level and on Bloom's knowledge taxonomy. The teacher module is responsible for the whole adaptivity process: the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. The adaptation of courseware is realized according to student-s knowledge stereotype.

Addressing Data Security in the Cloud

The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Understanding E-Learning Satisfaction in the Context of University Teachers

The present study was designed to test the influence of confirmed expectations, perceived usefulness and perceived competence on e-learning satisfaction among university teachers. A questionnaire was completed by 125 university teachers from 12 different universities in Norway. We found that 51% of the variance in university teachers- satisfaction with e-learning could be explained by the three proposed antecedents. Perceived usefulness seems to be the most important predictor of teachers- satisfaction with e-learning.

Online Brands: A Comparative Study of World Top Ranked Universities with Science and Technology Programs

University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.

Architecting a Knowledge Theatre

This paper describes the architectural design considerations for building a new class of application, a Personal Knowledge Integrator and a particular example a Knowledge Theatre. It then supports this description by describing a scenario of a child acquiring knowledge and how this process could be augmented by the proposed architecture and design of a Knowledge Theatre. David Merrill-s first “principles of instruction" are kept in focus to provide a background to view the learning potential.

Endogenous Fantasy – Based Serious Games: Intrinsic Motivation and Learning

Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.

An Exact Solution to Support Vector Mixture

This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.

Bayes Net Classifiers for Prediction of Renal Graft Status and Survival Period

This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Online Learning: Custom Design to Promote Learning for Multiple Disciplines

Today-s Wi Fi generation utilize the latest technology in their daily lives. Instructors at National University, the second largest non profit private institution of higher learning in California, are incorporating these new tools to modify their Online class formats to better accommodate these new skills in their distance education delivery modes. The University provides accelerated learning in a one-course per month format both Onsite and Online. Since there has been such a significant increase in Online classes over the past three years, and it is expected to grow even more over the over the next five years, Instructors cannot afford to maintain the status quo and not take advantage of these new options. It is at the discretion of the instructors which accessory they use and how comfortable and familiar they are with the technology. This paper explores the effects and summarizes students- comments of some of these new technological options which have been recently provided in order to make students- online learning experience more exciting and meaningful.

Virtual Speaking Head for Hearing Impaired Students

Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software tools will perform the translation of the regular speech into SL, after which it will be transferred to the student. On the other side, the questions of the student (in SL) will be translated and transferred to the lecturer in text or speech. One of those tools is presented tool. It-s too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.

Analysis of a Population of Diabetic Patients Databases with Classifiers

Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.