Abstract: In response to address different development challenges, Tanzania is striving to achieve its fourth attribute of the National Development Vision, i.e. to have a well educated and learned society by the year 2025. One of the most cost effective methods that can reach a large part of the society in a short time is to integrate ICT in education through e-learning initiatives. However, elearning initiatives are challenged by limited or lack of connectivity to majority of secondary schools, especially those in rural and remote areas. This paper has explores the possibility for rural secondary school to access online e-Learning resources from a centralized e- Learning Management System (e-LMS). The scope of this paper is limited to schools that have computers irrespective of internet connectivity, resulting in two categories schools; those with internet access and those without. Different connectivity configurations have been proposed according to the ICT infrastructure status of the respective schools. However, majority of rural secondary schools in Tanzania have neither computers nor internet connection. Therefore this is a challenge to be addressed for the disadvantaged schools to benefit from e-Learning initiatives.
Abstract: A learning management system (commonly
abbreviated as LMS) is a software application for the administration,
documentation, tracking, and reporting of training programs,
classroom and online events, e-learning programs, and training
content (Ellis 2009). (Hall 2003) defines an LMS as \"software that
automates the administration of training events. All Learning
Management Systems manage the log-in of registered users, manage
course catalogs, record data from learners, and provide reports to
management\". Evidence of the worldwide spread of e-learning in
recent years is easy to obtain. In April 2003, no fewer than 66,000
fully online courses and 1,200 complete online programs were listed
on the TeleCampus portal from TeleEducation (Paulsen 2003). In the
report \" The US market in the Self-paced eLearning Products and
Services:2010-2015 Forecast and Analysis\" The number of student
taken classes exclusively online will be nearly equal (1% less) to the
number taken classes exclusively in physical campuses. Number of
student taken online course will increase from 1.37 million in 2010 to
3.86 million in 2015 in USA. In another report by The Sloan
Consortium three-quarters of institutions report that the economic
downturn has increased demand for online courses and programs.
Abstract: One major issue that is regularly cited as a block to
the widespread use of online assessments in eLearning, is that of the
authentication of the student and the level of confidence that an
assessor can have that the assessment was actually completed by that
student. Currently, this issue is either ignored, in which case
confidence in the assessment and any ensuing qualification is
damaged, or else assessments are conducted at central, controlled
locations at specified times, losing the benefits of the distributed
nature of the learning programme. Particularly as we move towards
constructivist models of learning, with intentions towards achieving
heutagogic learning environments, the benefits of a properly
managed online assessment system are clear. Here we discuss some
of the approaches that could be adopted to address these issues,
looking at the use of existing security and biometric techniques,
combined with some novel behavioural elements. These approaches
offer the opportunity to validate the student on accessing an
assessment, on submission, and also during the actual production of
the assessment. These techniques are currently under development in
the DECADE project, and future work will evaluate and report their
use..
Abstract: The Information and Communication Technologies
(ICTs), and the Wide World Web (WWW) have fundamentally
altered the practice of teaching and learning world wide. Many
universities, organizations, colleges and schools are trying to apply
the benefits of the emerging ICT. In the early nineties the term
learning object was introduced into the instructional technology
vernacular; the idea being that educational resources could be broken
into modular components for later combination by instructors,
learners, and eventually computes into larger structures that would
support learning [1]. However in many developing countries, the use
of ICT is still in its infancy stage and the concept of learning object
is quite new. This paper outlines the learning object design
considerations for developing countries depending on learning
environment.
Abstract: This paper presents the results of the authors in designing, experimenting, assessing and transferring an innovative approach to energy education in secondary schools, aimed to enhance the quality of learning in terms of didactic curricula and pedagogic methods. The training is online delivered to youngsters via e-Books and portals specially designed for this purpose or by learning by doing via interactive games. An online educational methodology is available teachers.
Abstract: Despite the extensive use of eLearning systems, there
is no consensus on a standard framework for evaluating this kind of
quality system. Hence, there is only a minimum set of tools that can
supervise this judgment and gives information about the course
content value. This paper presents two kinds of quality set evaluation
indicators for eLearning courses based on the computational process
of three known metrics, the Euclidian, Hamming and Levenshtein
distances. The “distance" calculus is applied to standard evaluation
templates (i.e. the European Commission Programme procedures vs.
the AFNOR Z 76-001 Standard), determining a reference point in the
evaluation of the e-learning course quality vs. the optimal concept(s).
The case study, based on the results of project(s) developed in the
framework of the European Programme “Leonardo da Vinci", with
Romanian contractors, try to put into evidence the benefits of such a
method.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: Standards for learning objects focus primarily on
content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined
set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite
set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a
specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of
programs, is presented in this paper. The proposed definition includes
metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements
of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services
are also presented as a case study on the use of the proposed definition of programming problems as learning objects.
Abstract: Color categorization is shared among members in a
society. This allows communication of color, especially when using
natural language such as English. Hence sociable robot, to live
coexist with human in human society, must also have the shared
color categorization. To achieve this, many works have been done
relying on modeling of human color perception and mathematical
complexities. In contrast, in this work, the computer as brain of the
robot learns color categorization through interaction with humans
without much mathematical complexities.
Abstract: The technology usages of high speed Internet leads to
establish and start new era of online education. With the
advancement of the information technology and communication
systems new opportunities have been created. This leads universities
to have various online education channels to meet the demand of
different learners- needs. One of these channels is M-learning, which
can be used to improve the online education environment. With using
such mobile technology in learning both students and instructors can
easily access educational courses anytime from anywhere. The paper
first presents literature about mobile learning and to what extent this
approach can be utilized to enhance the overall learning system. It
provides a comparison between mobile learning and traditional elearning
showing the wide array of benefits of the new generation of
technology. The possible challenges and potential advantages of Mlearning
in the online education system are also discussed.
Abstract: In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.
Abstract: In this paper, we give an overview of an online elearning
tool which has been developed for kids aged from nine to
eleven years old in Mauritius for the self-study of Mathematics in
order to prepare them for the CPE examination. The software does
not intend to render obsolete the existing pedagogical approaches.
Nowadays, the teaching-learning process is mainly focused towards
the class-room model. Moreover, most of the e-learning platforms
that exist are simply static ways of delivering resources using the
internet. There is nearly no interaction between the learner and the
tool. Our application will enable students to practice exercises online
and also work out sample examination papers. Another interesting
feature is that the kid will not have to wait for someone to correct the
work as the correction will be done online and on the spot. Additional
feedback is also provided for some exercises.
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.