Abstract: The purpose of this study is to evaluate the English
version and a Malay translation of the 21-item Learner Awareness
Questionnaire for its application to assess student learning in higher
education. The Learner Awareness Questionnaire, originally written
in English, is a quantitative measure of how and why students learn.
The questionnaire gives an indication of the process and motives to
learn using four scales: survival, establishing stability, approval and
loving to learn. Data in the present study came from 680 university
students enrolled in various programmes in Malaysia. The Malay
version of the questionnaire supported a similar four factor structure
and internal consistency to the English version. The four factors of
the Malay version also showed moderate to strong correlations with
those of the English versions. The results suggest that the Malay
version of the questionnaire is similar to the English version.
However, further refinement to the questions is needed to strengthen
the correlations between the two questionnaires.
Abstract: This paper will seek to clarify important key terms
such as home schooling and home education as well as the legalities
attached to such terms. It will reflect on the recent proposed changes
to terminology in NSW, Australia. The various pedagogical
approaches to home education will be explored including their
prominence in the Australian context. There is a strong focus on
literature from Australia. The historical background of home
education in Australia will be explained as well as the difference
between distance education and home education. The future of home
education in Australia will be discussed.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: In light of the technological development and its
introduction into the field of education, an online course was
designed in parallel to the 'conventional' course for teaching the
''Qualitative Research Methods''. This course aimed to characterize
learning-teaching processes in a 'Qualitative Research Methods'
course studied in two different frameworks. Moreover, its objective
was to explore the difference between the culture of a physical
learning environment and that of online learning. The research
monitored four learner groups, a total of 72 students, for two years,
two groups from the two course frameworks each year. The courses
were obligatory for M.Ed. students at an academic college of
education and were given by one female-lecturer. The research was
conducted in the qualitative method as a case study in order to attain
insights about occurrences in the actual contexts and sites in which
they transpire. The research tools were open-ended questionnaire and
reflections in the form of vignettes (meaningful short pictures) to all
students as well as an interview with the lecturer. The tools facilitated
not only triangulation but also collecting data consisting of voices
and pictures of teaching and learning. The most prominent findings
are: differences between the two courses in the change features of the
learning environment culture for the acquisition of contents and
qualitative research tools. They were manifested by teaching
methods, illustration aids, lecturer's profile and students' profile.
Abstract: The literature on language teaching and second
language acquisition has been largely driven by monolingual
ideology with a common assumption that a second language (L2) is
best taught and learned in the L2 only. The current study challenges
this assumption by reporting learners' positive perceptions of tertiary
level teachers' code switching practices in Vietnam. The findings of
this study contribute to our understanding of code switching practices
in language classrooms from a learners' perspective.
Data were collected from student participants who were working
towards a Bachelor degree in English within the English for Business
Communication stream through the use of focus group interviews.
The literature has documented that this method of interviewing has a
number of distinct advantages over individual student interviews. For
instance, group interactions generated by focus groups create a more
natural environment than that of an individual interview because they
include a range of communicative processes in which each individual
may influence or be influenced by others - as they are in their real
life. The process of interaction provides the opportunity to obtain the
meanings and answers to a problem that are "socially constructed
rather than individually created" leading to the capture of real-life
data. The distinct feature of group interaction offered by this
technique makes it a powerful means of obtaining deeper and richer
data than those from individual interviews. The data generated
through this study were analysed using a constant comparative
approach. Overall, the students expressed positive views of this
practice indicating that it is a useful teaching strategy. Teacher code
switching was seen as a learning resource and a source supporting
language output. This practice was perceived to promote student
comprehension and to aid the learning of content and target language
knowledge. This practice was also believed to scaffold the students'
language production in different contexts. However, the students
indicated their preference for teacher code switching to be
constrained, as extensive use was believed to negatively impact on
their L2 learning and trigger cognitive reliance on the L1 for L2
learning. The students also perceived that when the L1 was used to a
great extent, their ability to develop as autonomous learners was
negatively impacted.
This study found that teacher code switching was supported in
certain contexts by learners, thus suggesting that there is a need for
the widespread assumption about the monolingual teaching approach
to be re-considered.
Abstract: Native American communities are struggling with unemployment and depressed economies. A major cause is a lack of business knowledge, education, and cultural desire. And yet, in the history of the American West, Native Americans were considered the best traders and negotiators for everything from furs to weapons to buffalo. To improve these economies, there has been an effort to reintroduce that heritage to todays and tomorrows generation of tribal members, such Crow, Cheyenne, and Blackfeet. Professors at the College of Business Montana State University-Billings (MSUB) teach tribal students in Montana to create business plans. These plans have won national small business plan competitions. The teaching and advising method used at MSUB is uniquely successful as theses business students are now five time national champions. This article reviews the environment and the method of learning to achieve a winning small business plan with Native American students. It discusses the five plans that became national champions. And it discusses the problems and solutions discovered in the process of achieving results. Students who participated in this endeavor have graduated and become CPAs, MBAs, and gainfully employed in their chosen professions. They have also worked to improve the economies of their native lands and homes. By educating members of these communities with business strategy and plan development, they are better able to impact their own economies.
Abstract: Today, there is a large number of political transcripts
available on the Web to be mined and used for statistical analysis,
and product recommendations. As the online political resources are
used for various purposes, automatically determining the political
orientation on these transcripts becomes crucial. The methodologies
used by machine learning algorithms to do an automatic classification
are based on different features that are classified under categories
such as Linguistic, Personality etc. Considering the ideological
differences between Liberals and Conservatives, in this paper, the
effect of Personality traits on political orientation classification is
studied. The experiments in this study were based on the correlation
between LIWC features and the BIG Five Personality traits. Several
experiments were conducted using Convote U.S. Congressional-
Speech dataset with seven benchmark classification algorithms. The
different methodologies were applied on several LIWC feature sets
that constituted by 8 to 64 varying number of features that are
correlated to five personality traits. As results of experiments,
Neuroticism trait was obtained to be the most differentiating
personality trait for classification of political orientation. At the same
time, it was observed that the personality trait based classification
methodology gives better and comparable results with the related
work.
Abstract: The purpose of this study is to determine whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard. It is found that online assessment by using selective types of questions like multiple choices, true or false and final answer questions don’t reflect the actual understanding of students in solving the problems and teachers can’t determine the weakness points of students. In addition, it is showed that OBMCQs are a very good tool for self-assessment and when teachers are testing for knowledge and facts. But when it comes to the skills, OBMCQs are poor tools for measuring the ability to apply knowledge to complex math problem.
Abstract: Aim of this research study is to investigate and
establish the characteristics of brain dominances (BD) and multiple
intelligences (MI). This experimentation has been conducted for the
sample size of 552 undergraduate computer-engineering students. In
addition, mathematical formulation has been established to exhibit
the relation between thinking and intelligence, and its correlation has
been analyzed. Correlation analysis has been statistically measured
using Pearson’s coefficient. Analysis of the results proves that there
is a strong relational existence between thinking and intelligence.
This research is carried to improve the didactic methods in
engineering learning and also to improve e-learning strategies.
Abstract: Academicians at the Arab Open University have
always voiced their concern about the efficacy of the blended
learning process. Based on 75% independent study and 25% face-toface
tutorial, it poses the challenge of the predisposition to
adjustment. Being used to the psychology of traditional educational
systems, AOU students cannot be easily weaned from being spoonfed.
Hence they lack the motivation to plunge into self-study. For
better involvement of AOU students into the learning practices, it is
imperative to diagnose the factors that impede or increase their
motivation. This is conducted through an empirical study grounded
upon observations and tested hypothesis and aimed at monitoring and
optimizing the students’ learning outcome. Recommendations of the
research will follow the findings.
Abstract: By the evolvement in technology, the way of
expressing opinions switched direction to the digital world. The
domain of politics, as one of the hottest topics of opinion mining
research, merged together with the behavior analysis for affiliation
determination in texts, which constitutes the subject of this paper.
This study aims to classify the text in news/blogs either as
Republican or Democrat with the minimum number of features. As
an initial set, 68 features which 64 were constituted by Linguistic
Inquiry and Word Count (LIWC) features were tested against 14
benchmark classification algorithms. In the later experiments, the
dimensions of the feature vector reduced based on the 7 feature
selection algorithms. The results show that the “Decision Tree”,
“Rule Induction” and “M5 Rule” classifiers when used with “SVM”
and “IGR” feature selection algorithms performed the best up to
82.5% accuracy on a given dataset. Further tests on a single feature
and the linguistic based feature sets showed the similar results. The
feature “Function”, as an aggregate feature of the linguistic category,
was found as the most differentiating feature among the 68 features
with the accuracy of 81% in classifying articles either as Republican
or Democrat.
Abstract: In this paper, we are interested in the problem of
finding similar images in a large database. For this purpose we
propose a new algorithm based on a combination of the 2-D
histogram intersection in the HSV space and statistical moments. The
proposed histogram is based on a 3x3 window and not only on the
intensity of the pixel. This approach overcome the drawback of the
conventional 1-D histogram which is ignoring the spatial distribution
of pixels in the image, while the statistical moments are used to
escape the effects of the discretisation of the color space which is
intrinsic to the use of histograms. We compare the performance of
our new algorithm to various methods of the state of the art and we
show that it has several advantages. It is fast, consumes little memory
and requires no learning. To validate our results, we apply this
algorithm to search for similar images in different image databases.
Abstract: Image segmentation and color identification is an
important process used in various emerging fields like intelligent
robotics. A method is proposed for the manipulator to grasp and place
the color object into correct location. The existing methods such as
PSO, has problems like accelerating the convergence speed and
converging to a local minimum leading to sub optimal performance.
To improve the performance, we are using watershed algorithm and
for color identification, we are using EPSO. EPSO method is used to
reduce the probability of being stuck in the local minimum. The
proposed method offers the particles a more powerful global
exploration capability. EPSO methods can determine the particles
stuck in the local minimum and can also enhance learning speed as
the particle movement will be faster.
Abstract: This paper participates in giving new vision and
explains the learning and acquisition processes of English language
by analyzing a certain context. Five important factors in English
language acquisition and learning are discussed and suitable solutions
are provided. The factors are compared with the learners' linguistic
background at Bisha College of Technology BCT attempting to link
the issues faced by students and the research done on similar
situations. These factors are phonology, age of acquisition,
motivation, psychology and courses of English. These factors are
very important; because they interfere and affect specific learning
processes at BCT context and general English learning situations.
Abstract: This article presents our prototype MASET (Multi
Agents System for E-Tutoring Learners engaged in online
collaborative work). MASET that we propose is a system which
basically aims to help tutors in monitoring the collaborative work of
students and their various interactions. The evaluation of such
interactions by the tutor is based on the results provided by the
automatic analysis of the interaction indicators. This system is
predicated upon the middleware JADE (Java Agent Development
Framework) and e-learning Moodle platform. The MASET
environment is modeled by AUML which allows structuring the
different interactions between agents for the fulfillment and
performance of online collaborative work. This multi-agent system
has been the subject of a practical experimentation based on the
interactions data between Master Computer Engineering and System
students.
Abstract: Cerebellar ataxia is a steadily progressive
neurodegenerative disease associated with loss of motor control,
leaving patients unable to walk, talk, or perform activities of daily
living. Direct motor instruction in cerebella ataxia patients has limited
effectiveness, presumably because an inappropriate closed-loop
cerebellar response to the inevitable observed error confounds motor
learning mechanisms. Could the use of EEG based BCI provide
advanced biofeedback to improve motor imagery and provide a
“backdoor” to improving motor performance in ataxia patients? In
order to determine the feasibility of using EEG-based BCI control in
this population, we compare the ability to modulate mu-band power
(8-12 Hz) by performing a cued motor imagery task in an ataxia
patient and healthy control.
Abstract: Software fault prediction models are created by using
the source code, processed metrics from the same or previous version
of code and related fault data. Some company do not store and keep
track of all artifacts which are required for software fault prediction.
To construct fault prediction model for such company, the training
data from the other projects can be one potential solution. Earlier we
predicted the fault the less cost it requires to correct. The training
data consists of metrics data and related fault data at function/module
level. This paper investigates fault predictions at early stage using the
cross-project data focusing on the design metrics. In this study,
empirical analysis is carried out to validate design metrics for cross
project fault prediction. The machine learning techniques used for
evaluation is Naïve Bayes. The design phase metrics of other projects
can be used as initial guideline for the projects where no previous
fault data is available. We analyze seven datasets from NASA
Metrics Data Program which offer design as well as code metrics.
Overall, the results of cross project is comparable to the within
company data learning.
Abstract: The Speexx results revealed four main factors
affecting the success of 190 Thai sophomores as follows: 1) Future
English training should be pursued in applied Speexx development.
2) Thai students didn’t see the benefit of having an Online Language
Training Program. 3) There is a great need to educate the next
generation of learners on the benefits of Speexx within the
community. 4) A great majority of Thai Sophomores didn't know
what Speexx was.
A guideline for self-reliance planning consisted of four aspects: 1)
Development planning: by arranging groups to further improve
English abilities with the Speexx Language Training program and
encourage using Speexx into every day practice. Local communities
need to develop awareness of the usefulness of Speexx and share the
value of using the program among family and friends. 2) Humanities
and Social Science staff should develop skills using this Online
Language Training Program to expand on the benefits of Speexx
within their departments. 3) Further research should be pursued on
the Thai Students progression with Speexx and how it helps them
improve their language skills with Business English. 4) University’s
and Language centers should focus on using Speexx to encourage
learning for any language, not just English.
Abstract: In educational technology, the idea of innovation is
usually tethered to contemporary technological inventions and
emerging technologies. Yet, using long-known technologies in ways
that are pedagogically or experimentially new can reposition them as
emerging educational technologies. In this study we explore how a
subtle pivot in pedagogical thinking led to an innovative education
technology. We describe the design and implementation of an online
writing tool that scaffolds students in the evaluation of their own
informational texts. We think about how pathways to innovation can
emerge from pivots, namely a leveraging of longstanding practices in
novel ways has the potential to cultivate new opportunities for
learning. We first unpack Infowriter in terms of its design, then we
describe some results of a study in which we implemented an
intervention which included our designed application.
Abstract: While emerging technologies continue to emerge,
research into their use in learning contexts often focuses on a subset
of educational practices and ways of using technologies. In this study
we begin to explore the extent to which educational designs are
influenced by larger societal and education-related factors not usually
explicitly considered when designing or identifying technology-supported
education experiences for research study. We examine
patterns within and between factors via a content analysis across ten
years and 19 different journals of published peer-reviewed research
on technology-supported writing. Our findings have implications for
how researchers, designers, and educators approach technology-supported
educational design within and beyond the field of writing
and literacy.