Abstract: With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. However, the acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect users- intention to use m-learning. Based on an updated information system (IS) success model, data collected from 350 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The data collected by questionnaire were analyzed to check the validity of constructs. Then hypotheses describing the relationships between the identified constructs and users- satisfaction were formulated and tested.
Abstract: Since after the historical moment of Malaysia
Independence Day on the year of 1957, the government had been trying hard in order to find the most efficient methods in learning.
However, it is hard to actually access and evaluate students whom will then be called an excellent student. It because in our realtime
student who excellent is only excel in academic. This evaluation
become a problem because it not balance in our real life interm of to get an excellent student in whole area in their involvement of curiculum and co-curiculum. To overcome this scenario, we
proposed a method called Student Idol to evaluate student through
three categories which are academic, co-curiculum and leadership.
All the categories have their own merit point. Using this method, student will be evaluated more accurate compared to the previously.
So, teacher can easily evaluate their student without having any emotion factor, relation factor and others. As conclustion this method will helps student evaluation more accurate and valid.
Abstract: The state of the art in instructional design for
computer-assisted learning has been strongly influenced by advances
in information technology, Internet and Web-based systems. The
emphasis of educational systems has shifted from training to
learning. The course delivered has also been changed from large
inflexible content to sequential small chunks of learning objects. The
concepts of learning objects together with the advanced technologies
of Web and communications support the reusability, interoperability,
and accessibility design criteria currently exploited by most learning
systems. These concepts enable just-in-time learning. We propose to
extend theses design criteria further to include the learnability
concept that will help adapting content to the needs of learners. The
learnability concept offers a better personalization leading to the
creation and delivery of course content more appropriate to
performance and interest of each learner. In this paper we present a
new framework of learning environments containing knowledge
discovery as a tool to automatically learn patterns of learning
behavior from learners' profiles and history.
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: This article discusses the concept of student ownership of knowledge and seeks to determine how to move students from knowledge acquisition to knowledge application and ultimately to knowledge generation in a virtual setting. Instructional strategies for fostering student engagement in a virtual environment are critical to the learner-s strategic ownership of the knowledge. A number of relevant theories that focus on learning, affect, needs and adult concerns are presented to provide a basis for exploring the transfer of knowledge from teacher to learner. A model under development is presented that combines the dimensions of knowledge approach, the teacher-student relationship with regards to knowledge authority and teaching approach to demonstrate the recursive and scaffolded design for creation of virtual learning environments.
Abstract: Possible advantages of technology in educational
context required the defining boundaries of formal and informal
learning. Increasing opportunity to ubiquitous learning by
technological support has revealed a question of how to discover
the potential of individuals in the spontaneous environments such as
social networks. This seems to be related with the question of what
purposes in social networks have been being used? Social networks
provide various advantages in educational context as collaboration,
knowledge sharing, common interests, active participation and
reflective thinking. As a consequence of these, the purpose of this
study is composed of proposing a new model that could determine
factors which effect adoption of social network applications for usage
in educational context. While developing a model proposal, the
existing adoption and diffusion models have been reviewed and they
are thought to be suitable on handling an original perspective instead
of using completely other diffusion or acceptance models because of
different natures of education from other organizations. In the
proposed model; social factors, perceived ease of use, perceived
usefulness and innovativeness are determined four direct constructs
that effect adoption process. Facilitating conditions, image,
subjective norms and community identity are incorporated to model
as antecedents of these direct four constructs.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.
Abstract: In the present paper some recommendations for the
use of software package “Mathematica" in a basic numerical analysis
course are presented. The methods which are covered in the course
include solution of systems of linear equations, nonlinear equations
and systems of nonlinear equations, numerical integration,
interpolation and solution of ordinary differential equations. A set of
individual assignments developed for the course covering all the
topics is discussed in detail.
Abstract: This paper discusses a curriculum approach that will
give emphasis on practical portions of teaching network security
subjects in information and communication technology courses. As
we are well aware, the need to use a practice and application oriented
approach in education is paramount. Research on active learning and
cooperative groups have shown that students grasps more and have
more tendency towards obtaining and realizing soft skills like
leadership, communication and team work as opposed to the more
traditional theory and exam based teaching and learning. While this
teaching and learning paradigm is relatively new in Malaysia, it has
been practiced widely in the West. This paper examines a certain
approach whereby students learning wireless security are divided into
and work in small and manageable groups where there will be 2
teams which consist of black hat and white hat teams. The former
will try to find and expose vulnerabilities in a wireless network while
the latter will try their best to prevent such attacks on their wireless
networks using hardware, software, design and enforcement of
security policy and etc. This paper will try to show that the approach
taken plus the use of relevant and up to date software and hardware
and with suitable environment setting will hopefully expose students
to a more fruitful outcome in terms of understanding of concepts,
theories and their motivation to learn.
Abstract: This paper is aimed to study the roles of leadership and innovation in the development of local people based ecotourism
services. The survey is conducted in Candirejo village, Borobudur District, Magelang Regency. The study of a descriptive approach is employed to identify people's behavior in ecotourism services. The results showed that ecotourism services have developed and provided benefits to the people. The roles of leadership and innovation interact positively with a cooperative to organize an ecotourism services management. The leadership is able to identify substances, to do the vision and missions of environmental and cultural conservation. The innovation provides alternative development efforts and increases the added value of ecotourism. The cooperative management was able to support a process to realize the goals of ecotourism, to build participation and communication, and to perform organizational learning. The phenomenon of the leadership in the Candirejo ecotourism enriches the studies of the ecotourism management. During this time, the ecotourism management is always associated
with the standard management of national park. The ecotourism management of Candirejo is considered successful even outside the national park management.
Abstract: Students often adopt routine practicing as learning
strategy for mathematics. The reason is they are often bound and
trained to solving conventional-typed questions in Mathematics in
high school. This will be problematic if students further consolidate
this practice in university. Therefore, the Department of Mathematics
emphasized and integrated the Discovery-enriched approach in the
undergraduate curriculum. This paper presents the details of
implementing the Discovery-enriched Curriculum by providing
adequate platform for project-learning, expertise for guidance and
internship opportunities for students majoring in Mathematics. The
Department also provided project-learning opportunities to
mathematics courses targeted for students majoring in other science or
engineering disciplines. The outcome is promising: the research
ability and problem solving skills of students are enhanced.
Abstract: This study is about an application of King Bhumibol
Adulyadej’s “Learn Wisely” (LW) concept in instructional design
and management process at the Faculty of Education, Suan Sunahdha
Rajabhat University. The concept suggests four strategies for true
learning. Related literature and significant LW methods in teaching
and learning are also reviewed and then applied in designing a
pedagogy learning module. The design has been implemented in
three classrooms with a total of 115 sophomore student teachers.
After one consecutive semester of managing and adjusting the
process by instructors and experts using collected data from minutes,
assessment of learning management, satisfaction and learning
achievement of the students, it is found that the effective SSRU
model of LW instructional method comprises of five steps.
Abstract: Graduate attributes have received increasing attention
over recent years as universities incorporate these attributes into the
curriculum. Graduates who have adequate technical knowledge only
are not sufficiently equipped to compete effectively in the work
place; they also need non disciplinary skills ie, graduate attributes.
The purpose of this paper is to investigate the impact of an eportfolio
in a technical communication course to enhance engineering
students- graduate attributes: namely, learning of communication,
critical thinking and problem solving and teamwork skills. Two
questionnaires were used to elicit information from the students: one
on their preferred and the other on the actual learning process. In
addition, student perceptions of the use of eportfolio as a learning
tool were investigated. Preliminary findings showed that most of the
students- expectations have been met with their actual learning. This
indicated that eportfolio has the potential as a tool to enhance
students- graduate attributes.
Abstract: As the Internet continues to grow at a rapid pace as
the primary medium for communications and commerce and as
telecommunication networks and systems continue to expand their
global reach, digital information has become the most popular and
important information resource and our dependence upon the
underlying cyber infrastructure has been increasing significantly.
Unfortunately, as our dependency has grown, so has the threat to the
cyber infrastructure from spammers, attackers and criminal
enterprises. In this paper, we propose a new machine learning based
network intrusion detection framework for cyber security. The
detection process of the framework consists of two stages: model
construction and intrusion detection. In the model construction stage,
a semi-supervised machine learning algorithm is applied to a
collected set of network audit data to generate a profile of normal
network behavior and in the intrusion detection stage, input network
events are analyzed and compared with the patterns gathered in the
profile, and some of them are then flagged as anomalies should these
events are sufficiently far from the expected normal behavior. The
proposed framework is particularly applicable to the situations where
there is only a small amount of labeled network training data
available, which is very typical in real world network environments.
Abstract: The purpose of this paper is to describe the process of
setting up a learning community within an elementary school in
Ontario, Canada. The description is provided through reflection and
examination of field notes taken during the yearlong training and
implementation process. Specifically the impact of teachers- capacity
on the creation of a learning community was of interest. This paper is
intended to inform and add to the debate around the tensions that
exist in implementing a bottom-up professional development model
like the learning community in a top-down organizational structure.
My reflections of the process illustrate that implementation of the
learning community professional development model may be
difficult and yet transformative in the professional lives of the
teachers, students, and administration involved in the change process.
I conclude by suggesting the need for a new model of professional
development that requires a transformative shift in power dynamics
and a shift in the view of what constitutes effective professional
learning.
Abstract: Information and communication technology (ICT) is
essential to the operation of business, and create many employment
opportunities. High volumes of students graduate in ICT however
students struggle to find job placement. A discrepancy exists between
graduate skills and industry skill requirements. To address the need
for ICT skills required, universities must create programs to meet the
demands of a changing ICT industry. This requires a partnership
between industry, universities and other stakeholders. This situation
may be viewed as a critical systems thinking problem situation as
there are various role players each with their own needs and
requirements. Jackson states a typical critical systems methods has a
pluralistic nature. This paper explores the applicability and suitability
of Maslow and Dooyeweerd to guide understanding and make
recommendations for change in ICT WIL, to foster an all-inclusive
understanding of the situation by stakeholders. The above methods
provide tools for understanding softer issues beyond the skills
required. The study findings suggest that besides skills requirements,
a deeper understanding and empowering students from being a
student to a professional need to be understood and addressed.
Abstract: Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.
Abstract: A novel biologically inspired controller for the autonomous
navigation of a mobile robot in an evasion task is
proposed. The controller takes advantage of the environment by
calculating a measure of danger and subsequently choosing the
parameters of a reinforcement learning based decision process.
Two different reinforcement learning algorithms were used: Qlearning
and Sarsa (λ). Simulations show that selecting dynamic
parameters reduce the time while executing the decision making
process, so the robot can obtain a policy to succeed in an escaping
task in a realistic time.
Abstract: Artificial Neural Network (ANN)s can be modeled for
High Energy Particle analysis with special emphasis on shower core
location. The work describes the use of an ANN based system which
has been configured to predict locations of cores of showers in the
range 1010.5 to 1020.5 eV. The system receives density values as
inputs and generates coordinates of shower events recorded for values
captured by 20 core positions and 80 detectors in an area of 100
meters. Twenty ANNs are trained for the purpose and the positions
of shower events optimized by using cooperative ANN learning. The
results derived with variations of input upto 50% show success rates
in the range of 90s.