Summary of the Chapter - Ayad knowledge base

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Nov 25, 2013 (3 years and 11 months ago)

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Knowledge Management Approach for Predictive Analytics in HEI Student IT
-
Skill using Data
Mining techniques

2.1


Introduction


This chapter introduces the direction of our work,
background of

the research,

employability
and ICT skills, the need for ICT
-
skills
,

I
C
T skills barriers
, Literature survey and the Summary
of the chapter.



Fig
ure
1
:

D
irection of work

2.2

Research Background


The technological revolution has promoted a new society marked by global changes and
innovation in the information technologies,
all of which influences the economy, politics, the
competitive aspects, the labor market, the educational strategies, and the new learning
structures , as well as the new forms of recreation and immediate, permanent and real
-
time
interaction among people
worldwide, Therefore, a new paradigm is being built by the global
society through the ICTs, which cross transversally all the communication fields, by
connecting people with information, products and ideas, and operating both individually and
in communitie
s worldwide ,To face these changes ICT competencies have become part of the
requirements dem
anded by many working positions
(
de Guadalupe Arras
-
Vota, Torres
-
Gastelú et al. 2011
)
.

To succeed in today’s information
-
driven academic environment and
organizations, students
need to know how to find, use, manage, evaluate and convey
information efficiently and effectively. Organizations of all sorts have a consistent need for
individuals at every level that can effectively use information and communication technology.

ICT in
e
ducation institute (
EDI
)

will help the student to increase
knowledge of school
subjects, improved attitudes about learning, and acquisition of new skills that are needed for a
developing economy. Beyond learning outcomes, ICT may help close the gender gap,

and
help
students with special needs
(
Choueiri, Choueiri et al. 2012
)
.

The skills that graduates require increasingly revolve around knowledge creation
and
information sharing, insight and analysis, and collaboration and advanced communications
skills
(
Miliszewska 2008
)
.

With growing rates of retirements of ICT workers expected over the next 10
-
15 years,
industry representatives are concerned that the shortfall in replacement workers will have a
significant detrimental impact on business. Various authors and panels have ci
ted the need to
attract more students to ICT
skills
(
Babin, Grant et al. 2010
)
.

Universities
is

the source for the
skills that can be delivering to the peop
le, then the organization can obtain the employers with
good skills from the universities outcome, in that cause the high education institute focus to
enhance the way of the study since the organization rely
on

the new graduates student to
overtake job ins
tead of the retired staff, the high
er

education institute play very important
effect on the country’s economy
.

The purpose of this study is to investigate the factors
that effecting
the ICT skills in the
education filed
,

and
to build the predictive model
to predict

students
ICT

skills which is will
help the organization to select the right employer for the right
vacancy
,

and to alert about the
student
s

which is less

skills and they need more attention
in order to enhance their skills
.

Predictive Analytics

Predictive Analytics
is the process of dealing with variety of data and apply various

mathematical formulas to discover the best decision

for a given situation. Predictive analytics
gives company a competitive edge. It is the decision science that removes
guesswork out of
the decision
-
making process and applies proven scientific guidelines to find right solution in
the shortest time possible. Predictive analytics is a solution used by many

businesses today to
gain more value out of

large amounts of raw data

by applying techniques that

are used to
predict future behaviors within an organization. Predictive analytics encompasses a variety of
techniques from data mining, statistics and game theory that analyze current and historical
facts to make predictions ab
out future events.

Predictive

analytics provides the marketer something beyond standard

business reports and
sales forecasts: actionable predictions for each customer. These predictions encompass all
channels, both online and off, foreseeing which customer
s will buy, click, respond, convert or
cancel. The customer predictions generated by predictive analytics deliver more relevant
content to each customer, improving response rates, click rates, buying behavior, retention
and overall profit

(Predictive Data
Mining: Promising Future and Applications)

Predictive analytics connects data to effective action by drawing reliable conclusions about
current conditions and future events
,
is both a business process and a set of related
technologies. Predictive analytic
s leverages an organization’s business knowledge by
applying sophisticated analysis techniques to enterprise data. The resulting insights can lead
to actions that demonstrably change how people behave as customers, employees, patients,
students, and citize
ns
,
technologies that uncovers relationships and patterns within large
volumes of data that can be used to predict
,
predictive analytics is forward
-
looking, using
past events to anticipate the future

behavior and events

(Analytics in Higher Education
Esta
blishing a Common Language)

In general, analytics is a newer name for data mining. Predictive

analytics indicate
s a focus on
making
predictions (
Predictive analytics and data mining)

Predictive analytics using data mining tools and technique to predict the

future success event
and decrease the fails

Predictive

analytics stages (Automated self
-
service modeling: predictive analytics

as a service)



Define the problem



Build data mining database



Explore the data



Prepare data for modeling



Data mining model buildin
g



Evaluation and interpretation



Deploy the model and result





Educational Data Mining (EDM)

EDM has the potential to help HEIs understand the dynamics and patterns of a variety of
learning environments and to provide insightful data for rethinking and
improving students’
learning experiences.

Educational

data mining (EDM) has emerged as a new field of research
capable of exploiting the abundant data generated by various systems for use in decision
making. The enthusiastic adoption of data mining tools b
y higher education has the potential
to improve some aspects of the quality of education, while it lays the foundation for a more
effective understanding of the learning process
,
EDM, when

integrated into an iterative cycle

in which mined knowledge is inte
grated into the loop of the system not only to facilitate and
enhance learning as a whole,

but also to filter mined knowledge for decision making

or even
to create intelligence upon which students, instructors, or administrators can build, can
notably chan
ge academic
behavior (
Using Data Mining for Predicting Relationships between
Online Question Theme and Final Grade
)

Is concerned with developing, researching, and applying computerized methods to detect
patterns in large collections of educational data patterns that would otherwise be hard or
impossible to analyze due to the enormous volume of data they exist within. Da
ta of interest is
not restricted to interactions of individual students with an educational system (e.g.,
navigation behavior, input to quizzes and interactive exercises) but might also include data
from collaborating students (e.g., text chat) administra
tive data (e.g., school, school district
teacher), and demographic data (e.g., gender, age, school grades). EDM uses methods and
tools from the broader field of data mining
(
Scheuer and McL
aren 2011
)
.

Apply data mining (DM) in education is a merging interdisciplinary research field also known
as educational data mining (EDM). It is concerned with developing methods for exploring the
unique types of data that come from educational environm
ents. Its goal is to better understand
how students learn and identify the settings in which they learn to improve educational
outcomes and to gain insights into and explain educational phenomena. Educational
information systems can store a huge amount of
potential data from multiple sources coming
in different formats and at different granularity levels. Each particular educational problem
has a specific objective with special characteristics that require a different treatment of the
mining problem. The is
sues mean that traditional DM techniques cannot be applied directly to
these types of data and problem. As consequence the knowledge discovery process has to be
adopted and some specific DM techniques are needed
(
Romero and Ventura 2013
)
.




Data mining

Data mining (also called data or knowledge discovery) is the method of analyzing data from
different perspectives to discover interesting and helpful information. The information gained
through data mining has been effectively used in various sectors rangi
ng from finance,
agriculture to health and education. There are many data mining tools, available that allow
users to analyze data from many different aspects, categorize it, and discover the identified
relationships.

Technically, data mining is a techniqu
e of finding correlations or patterns
among many fields in large databases. Educational data mining is fast becoming an interesting
research area which allows researcher to extract useful, previously unknown patterns from the
educational databases for bett
er understanding, improved educational performance and
assessment of the student learning process
(
Anwar and Ahmed 2011
)

With the enormous amount of data stored in files, databases, and other repositories, it is
increasingly important, if not necessary, to develop powerful means for analysis and perhaps

interpretation of such data and for the extraction of interesting knowledge that could help in
decision
-
making. Data Mining, also popularly known as Knowledge Discovery in Databases

(KDD), refers to the nontrivial extraction of implicit, previously unknow
n and potentially

useful information from data in databases. While data mining and knowledge discovery in

databases (or KDD) are frequently treated as synonyms, data mining is actually part of the
The actual data mining task is the automatic or semi
-
automa
tic analysis of large quantities of
data to extract previously unknown interesting
patterns such as
groups of data records (cluster
analysis), unusual records (anomaly detection) and dependencies (association rule mining).
This usually involves using datab
ase techniques such as spatial indices. These patterns can
then be seen as a kind of summary of
the

input data, and may be used in further analysis or,
for example, in machine learning and predictive analytics. For example, the data mining step
might ident
ify multiple groups in the data, which can then be used to obtain more accurate
prediction results by a decision support system. Neither, the data collection and data
preparation nor result interpretation and

knowledge discovery process

(
DATA MINING
APPROA
CH TO STUDENT RETENTION)





2.3

WHAT is Information and Communications Technology?


Information Technology (IT) or Information and Communications

Technology (ICT) is a
broad industry that deals with technology and

other aspects of managing and processing
information, especially in

large organizations
(
Unwin 2009
)
.

Information and communications technology incl
udes:



The hardware (network equipment and personal computers)



The software (applications and programs) and



Management of the data and information within these networks and systems

2.4

ICT in Malaysia


Small and medium enterprises (SMEs) play a vital role in
the Malaysian economy and

are
considered to be the backbone of industrial development in the country
,
Small and medium
sized enterprises

are defined as firms employing full
-
time employees 150 or with annual sales
turnover not exceeding RM25 million

and pla
y

a significant role in the country’s economic
development, particularly in the manufacturing sectors

Malaysian businesses, most SMEs in
Malaysia realize that ICT is critical to the productivity and performance of their companies.
But, implementation and m
aintenance of these ICT systems is restricted due to inability to
handle, owing to high staff turnover and lack of I
CT project management expertise
(
Malaysia
2007
)
.

The rapid expansion of ICT in
Malaysia saw the launching of Multimedia Super Corridor
(MSC), in 1996, to accelerate its entry into the Information Age. Putrajaya functions as the
new seat for government and federal administrative capital becoming the center for the
introduction of the
concept of

Electronic Government (EG). EG, one of the seven MSC
flagships is aimed at reinventing the public sector’s view of the needs of citizens and the
private sector. Simultaneously, information flow and processes within the government are

streamlined
. Exploitation of ICT in government is expected to improve internal effectiveness
and provide citizens with better information and services
(
Salamat, Hassan et al. 2011
)
.

The issue of graduate employability is one of great concern to institutes of higher learning
(IHLs), particularly in the face of the current global financial crisis. Faced with a contracting
and fiercely competitive job market, IHLs are under increasing pr
essure to ensure that their
graduates are employable. One of the challenges in producing such graduates is to ensure that
they have the relevant knowledge, skills and attributes required by industry. Complaints from
industry about graduates not being ready

for the workplace is a global phenomenon, and one
of the best ways to bridge the gap between class and work is to engage with industry. In
Malaysia, there has been a push towards university
-
industry
collaboration and the need
for
such collaboration is rei
terated in
Malaysia’
s National Higher Education Action Plan and the
setting up of industry linkage centers on campus. At the Univ
ersity of Malaya (UM),
industry’
s input and collaboration are ever present in teaching and learning (e.g. on
curriculum advisor
y boards, as guest or visiting lecturers), research and innovation (e.g. joint
research projects, consultancy, commercialization of research output), and the

training of staff
and students
(
Pillai 2009
)






2.5

Employability and ICT Skills


Information communication technology (ICT) is very vital in today’s life. All Individuals
regardless of gender in our society must at least acquire basic ICT skills
to function
successfully and efficiently, in order to develop, advance and succeed in their professional
lives. This is because there exist unprecedented career opportunities for ICT profession
around the world
(
Hashim 2008
)
.
In today's technological environment, innovation almost
always involves embracing ICTs, which in turn allows for optimization of business processes,
efficiency gains and impro
ved knowledge management processes and, c
onsequently bigger
market share
(
Act 2005
)
.

The demand for ICT professionals continues to grow whilst other jobs are disappearing. ICTs
help improve business development and growth across all sectors thus creating further
employment
(
Act 2005
)
.

Workers

with stronger IT skills are more likely to be employed
despite controlling for

other

individual
-

and household
-
level va
riables (such as age, education,
gender, household

computer and Internet access) and skill bias that might a

affect their
employment op
portunities. This positive relationship between IT skills and employment is
primarily

due to skills obtained by on
-
the
-
jo
b training
(
Atasoy, Banker et al. 2012
)
.
Information technology (IT), especially internet
technologies, improves the matching of
workers with firms by making more information accessible to both firms and workers; IT
reduces traditional geographic barriers to job search and the cost of employment applications.
IT also can provide education and
training opportunities for workers at a lower cost than
traditional alternatives. As IT becomes an essential business investment, workers with IT
skills become more attractive on the job market

Employability Skills act as a pinpoint to build up candidates‟

self
-
developments and

personalities, hence it helps in their future competence and sociality. Besides, community

colleges should
continue update themselves for
latest elements of Employability Skills that

favor by companies as the syllabus carry out inter
nal may meet the external requirements

Instructors may also build a connection with companies in order to obtain a trusty and direct

flow of information about
elements of Employability Skills. On the other hand, companies

may work closely with ministry to
help develop trainings for instructors about elements of

Employability Skills as for win
-
win situation. Instructors receive direct information about

requirements and favors or elements will then deliver to students

(
Ahmad Rizal and Yahya
2011
)
.

The relationship between different kinds of

ICT
, Figure 2
shown

that ICT skills for IT jobs,
derived from a partial subset of those needed for enhanced living and employment
opportunities; and ICT skills for enhanced living and employment opportunities is derived
from subset of those ICT skills which are needed for le
arning

in all curriculum areas
(
Kumar
2008
)
.

It can also be noted that through the use of ICTs in education, students are acquiring new in

Abilities such as: a) greater collaboration, b) team work, and c) project management. These

Competencies are increasingly closer to the needs of the labor market and productivity and,

perhaps, less and less focused on the curricula
(
de Guadalupe Arras
-
Vota, Torres
-
Gastelú et
al.
)
.


Fig
ure

2
:
Relationship between different kinds of ICT
(
Kumar 2008
)

2.6

Need for ICT


Skills


It is generally accepted that there is worldwide shortage of people with the ICT skills
necessary to boost the economies of 21 Century, e
-
skills vary from low level, computer
literacy skills
needed by individual members of society to access services to high level
technology skills needed by specialist ICT professionals. A further important group of skills
are those required by managers and leaders within non
-

ICT sectors of the economy that al
low
them to use ICT effectively and innovatively
(
Lotriet, Matthee et al.
2010
)
.

In every filed of the life the ICT is needed, according to
(
Babu, Vinayagamoorthy et al. 2007
)

the ICT skills required in library services, but they need to concentrate more on the network
-
based services and digital library services.

Information and Communication Technologies
(IC
Ts) have the potential to improve the lives of people in rural communities. According to
the United Nations Development Program
(
Ruxwana, Herselman et al. 2010
)


I
ncreased use of ICTs enhances service delivery by:



delivering economies of scale to improve access to basic services



optimizing se
rvice delivery



providing incentives for development and transfer of new technologies and products



increasing efficiency through enhanced connectivity and exchange of knowledge



enabling regions to focus on delivering services where they have a comparative
a
dvantage



providing access to digital development for continuous improvement

ICTs are changing rapidly, as are businesses surrounding their implementation
, t
he need to
develop and organize new ways to provide efficient healthcare services has thus been
acc
ompanied by major technological advances, resulting in a dramatic i
ncrease in the use of
ICT appli
cations in healthcare and e
-
health
(
Ruxwana, Herselman et al. 2010
)
.

The ICT use in teaching it is
interactive
,
ICT has had relatively little

impact on attainment and
how its
contribution might be increased,
whole
-
class
teaching has stimulated greater pupil
motivation and attention
,
the relatively superficial improvements in clarity of information
provided to pupils,

and in pupil involvement in act
ivity at the front of the class
(
Beauchamp
and Kennewell 2008
)


Information and communication technology (ICT) is an increasingly important tool in dental
education and practice
,
benefit the students’
personal and professional development.

ICT

was
helpful in finding information
,
motivating them to be more productive in their study
,
They
also perceived they have general skills on installation of software packages
,
e
-
mail for
communication
,
and interacti
on between applications
,
Their attitudes and perceptions towards
ICT in their learning may have encouraged the students in their learning processes and
experience. They were independent in finding knowledge, information, improving skills and
communication
(
Mohamed, Aik et al. 2011
)
.

2.7

ICT skills barriers


Students identified lack of training as the most important factor in inhibiting

computer use.
Although most valued learning about computers, they claimed

that the training offered to
them was largely inadequate. In contrast, staff

believed that they provided sufficient initial
training for students to continue

to develop their own computer skills. However in some
instances, anxiety and

lack of confidence interacted to prevent students from adopting this
self
-
help

approach
(
McMahon, Gardner et al. 1999
)
.

Those students who had not elected to
study an ICT subject

in their senior years of secondary school made their decision mainly
based on their lack of interest in this area those students who had elected to study ICT during
their final two years at secondary school. These students had a positive outlook of their
experiences in their past ICT studies as well as a positive view of the industry
, there

are
is
few
differences in the opinions of students who elected to study ICT at senior years of secondary
school; therefore both males

and females view the ICT industry, ICT studies, computers, and
technology in a similar way to each other.

These students found their ICT studies to be
challenging and interesting, although not difficult or boring, but despite this, fewer females
are actua
lly undertaking this course of study. Females were less confident than males when it
came to technology, and the many students who appear to have incorrect perceptions of what
employment in the ICT industry entails. The career information relating to ICT t
hat is
received by schools does not seem to be filtering down to those who need it. Today’s young
people are independent thinkers making career choices by themselves, rather than with
assistance from others. By

the time students enter university the decisi
on whether or not to
study ICT has been made.

The ICT barriers is not interesting with ICT, not
familiar

with ICT,
not confident with ICT
(
McLachlan, Craig et al. 2010
)

there is many factors effected the student to not study ICT, the shrinking number of women
in computing, motivations behind conducting intervention programs, inadequate information
provided to student
s on computing courses, experiences in Computer Science
(
McLachlan,
BIS et al. 2011
)
.

Anxiety and lack of confidence in using computers is more prevalent among
women than men. Even amongst experienced users, It is suggested that current ICT curricula
that are focused on
technology
-
centered topics are biased towards male students
(
Koppi,
Roberts et al. 2012
)
.

Nursing and ICT,
Poor equipment is a significant aspect affecting student

nurses use of ICT and their skills development. The

number and position
of computer
terminals are influ
ential
(
Willmer 2007
)
.

Among attitudes towards technology, security is an
important factor that influences the use of the technology.

security as a threat
which creates
“circumstances, condition, or event with the potential to cause economic hardship to data or
network resources in the form of destruction, disclosure, modification of data, denial of
service and/or fraud, waste and abuse. Perceived security i
s about the self
-
belief that a user
has in the system to conclude a transaction securely and to maintain the p
rivacy of personal
information

security was found to be significant obstacles to the adoption o
f ICT
(
Selamat,
Jaffar et al. 2011
)
.

According to
(
Hamzah, Ismail et al. 2009
)
, study conducted in Malaysia
Islamic Education
smart school,
study found that the use of computers was the core feature of the chang
e
phenomenon in Smart Schools. Islamic
Education teachers and students were hardly coping
with the task of incorporating the use of new technology in their teaching and learning. Many
barriers and obstacles in using new technology were reported by Islamic
Education teachers
and students. The most important barriers identified in this study are the lack of computers
and available resources, lack of training, shortage of time and the pressure of a heavy syllabus
and examination
-
centered learning
.

Same previou
s barriers also mentioned by
(
Ismail, Azizan
et al. 2011
)

which
were lack of time,

insufficient training, inadequate technical support, lack
of knowledge, difficulty in using different tools and unavailability of resources
.

There were two factors relating to students that discouraged educators from using IT or
developing IT skills in
their teaching. One of the factors was low participation of students in
IT
-
based activities. For example, many students did not take advantage of the initiative and
access course documents provided through the online Blackboard system. Some educators
also
experienced low participation from students in terms of completing IT
-
based class
exercises

(
Senik and Broad 2011
)



2.8

Factors En
courage ICT skills


According to
(
Babin, Grant et al. 2010
)

one of the important factors that affect ICT and
encourage to the
student toward ICT is
“opportunity to earn above average income”

There is another few factors which is
encounter

the student to ICT skills, such as computer
enjoyment,

computer importance and computer anxiety

(
Teo 2008
)

, Table

1
showing

the
details

of the current factors

Table 1:
ICT encouragement factors

Encourage factor

Explanation

Computer enjoyment



I enjoy doing things on a computer



I concentrate on a computer when I use one



I enjoy computer
games very much



I enjoy lessons on the computer


Computer importance



I will be able to get a good job if I learn how
to use a computer



I would work harder if I could use computers
more often



I know that computers give me opportunities
to learn many things



I can learn many things when I use a
computer



I believe that the more often teachers use
computers, the more I will enjoy school



I believe that it is very important for me to
learn how to use a computer

Computer anxiety



I feel comfortable using a compute
r



Computers do not scare me at all


Among the factors that directly influence personal computer acceptance were

perceived ease
of use and perceived usefulness. The findings indicate that perceived ease of use is a
dominant factor in explaining perceived u
sefulness and system usage and it was also found
that perceived usefulness is a strong antecedent of system usage
(
Selamat, Jaffar et al. 2011
)
.

There is other factor mentioned by
(
Ismail, Azizan et al. 2011
)

t
eachers’ confidence is a major
factor which determines teachers’ and students’ engagement with ICT
,
it had been suggested
that when teachers’ confidence increases, not only students will use

the technology more, but
they also will become confident users of technology as well.



2.9

ICT and students’ performance


The life of a tertiary student is now quite different from that experienced by students one or
two decades ago. There have been many
changes in the tertiary educational environment as
universities adapt to an increasingly diverse student population. Arguably, the most
significant change has been the increased use and reliance on technology
(
Sheard, Carbone et
al. 2010
)

The direct link between ICT use and students’ performance has been the focus of extensive
literature during the last two decades.

Several studies have tried to explain the role and the
added value of these technologies in classrooms and on student’s performances
(
Ben Youssef
and Dahmani 2008
)
.

The first body of literature explored the impact of computer uses. Since
the Internet revolution, there has been a shift in the literature that focuses more on the impact
of online activities: use of Internet, use of educative online platforms, digital dev
ices, use of
blogs and wikis
(
Ben Youssef and Dahmani 2008
)
.

Most students have expressed much
appreciation towards ICTs as tools for permanent learning and as a means of social
communication and collaboration, in line with the results of other investigations. Digital tools
are pr
imarily used by students for obtaining information and working online. Students claim
to make a legal and responsible use of information obtained through ICT
(
Torres
-
Gastelú and
García
-
Valcárcel
-
Muñoz
-
Repiso 2011
)
.

the ICT experiences and knowledge t
hat students
brought into their degrees had little influence on their performance and progression at
university
(
Sheard, Carbone et al. 2008
)

According to ICT Usage and Student Perceptions in Cambodia and Japan, Students from both
countries indicated that school was the primary place where they
learned about computers
(suggesting government policy has succeeded to some extent), whereas they learned the better
part of cell phone usage by themselves. Students in both countries expressed little anxiety
when using technology
(
Elwood and MacLean 2009
)
. The ICT and computer impact students
study habits, student use the computer daily to facilitate learning, computers can be

used as a
supplement but cannot fully replace the teacher’s job, thus students use computers to
download and save relevant information from the internet so as to facilitate learning
(
Mbah
2010
)
.

2.10

ICT
Knowledge transfer to work place


There is few factors

identifies
the

influence
of
the

transferability of ICT from university to the
workplace and the

related consequences.
Figure 3

showing
the conceptual framework
consist

of the three

main phases: pre
-
transfer, transition, and post
-
transfer
,
The pre
-
transfer phase, the
factors that enabled the transition of

ICT skills from university to the workplace are identified
as

educational and individ
ual factors. Through their experiences at

university the new
graduate developed three key attributes

that facilitated the transition phase: ICT skills,
knowledge, and self
-
efficacy
(
Nurses’ICT 2010
)
.

The

transition phase, new graduate are influenced

by organizational and contextual factors

which impacted on both their

feelings of self
-
efficacy and the transferability of their ICT
skills. The

results of transferability become evident in the post
-
transfer p
hase

either with
positive or negative personal and professional outcomes.

This phase illustrates the
consequences of successful or unsuccessful

transfer and is identified in this framework in
terms of patient

outc
omes and workplace satisfaction, the study
conducted on the nursing
students and graduates
(
Nurses’ICT 2010
)
.


Figure 3 :
Conceptual Framework for Transferability of ICT skills from University to the
Workplace
(
Nurses’ICT 20
10
)



2.11

ICT A
cceptance


There are several factors contribute to the adoption of ICTs in the organization
(
Selamat,
Jaffar et al. 2011
)
.



Perceived ease of use will have a positive effect on perceived usefulness of ICT



Perceived usefulness of ICT is positively related to the intent to use such technologies.



Perceived ease of use of ICT is positively related to the intent to use such technologies



Perceived Complexity will positively influence the intention to use ICT



Perceived Security will positively influence the intention to use ICT



Organizational readin
ess and competence will positively influence the intention to use
ICT


2.12

Literature Survey of IT skills


T
able
1, show

the Literature survey for the ICT skills,
and the standard of the skills that used
by most of the organizations employer to evaluate
the

applicant for job.

Table
2:

Literature survey for ICT skills

Author

What IT skills

Note

(
Hakkarainen, Ilomäki et al. 2000
)



Operating System usage



Computer memory



File

formats



www publishing


(
Ilomäki and Rantanen 2007
)



Operating system



Text processing



Internet application



Paint program



Multimedia

program


(
Haywood, Haywood et al. 2004
)



Chat program



Online bibliographic
database



Web
browser



Presentation manager



Web authoring

The evolution done by asking the
student if they ( can do work on the
mention list alone, or need help
from someone, or never done that
before)



Graphic program



Database



Email program



Spread sheet



Word processor


(
Stoner 2009
)



Using windows



Spreadsheets



Word pressing



Email



World wide web



(
Edgar, Johnson et al. 2012
)



Internet



Electronic email



Spreadsheets



Word processing



Computer graphics



Database



Miscellaneous



(
Alston, Cromartie et al. 2009
)



Spread sheets



Word processing



Internet access and use



Accounting systems



Presentation graphics



Database


respondents felt that presentation
graphics, accounting systems, and
internet

access and use were extremely
important when entering the work
force. Employers also felt that

word

processing and spreadsheets
skills were very important.
Moreover, the following skills

were just important: database and
CAD.

(
van Deursen and van Diepen
2012
)

Internet
skills



Information internet skills

a
-

Choosing a web site
or a search system to
seek information

b
-

Defining search
options or queries

c
-

Selecting information
( on web sites or in
search results)

d
-

Evaluating
informational sources



Strategic internet skills

a
-

Developing an
orientation toward a
particular goal

b
-

Taking the right
decision to reach this
goal

c
-

Making the right
decision to reach this
goal

d
-

Gaining the benefits
resulting from this
goal


(
Eley, Fallon et al. 2008
)



Keyboard skills



File management



Word processing

ICT skills for nursing



Spreadsheets



Databases



Email



Library searches



Internet



Patient management



Administration systems



Information management

(
Taleb 2012
)

First priority



Familiarity

with data
security



Basic concept of internet
and using browser



Using the word
processor



Working with icons



Navigation

of web pages



Searching the web



Basic concepts of the
electronic

communication



Entering text



File management



Format text



Familiarity

with the copy
right and data protection



Bookmark

webpage



Text editing with software





Second
priority




Send email



Familiarity with computer
performance



Receiving email



Working with
presentations



Familiarity

with the
computer soft
ware



Famili
a
rity

with hardware
of computer



Familiarity

with
internet



Print docum
en
ts



Developing presentation


Third

priority




Checking and printing
slides



Email management



Working with graph and
charts



Putting data in a spread
sheet cell



Familiarity

with networks



Advance word processor



Delivering showing


presentation



Handling and formatting
text



Familiarity with memory
and storage


Fourth
priority




Understanding

database



Create

a report



Advanced spreadsheet
features



Retrieving information





(
Calzarossa, Ciancarini et al. 2007
)

Module 1: Basic concepts of
Information Technology (IT)

Module 2: Using the computer and
managing files

Module 3: Word processing

Module 4:
Spread sheets


Module 5: Database

Module 6: Presentation

Module 7: Information and
communication

The European C
omputer Driving
Licence is a standard qualification
recognised throughout the EU. Its
syllabus covers key practical skills
and basic understanding of
computer systems needed for you
to operate effectively in today's
technology
-
equipped study and
work envir
onments. This syllabus
is increasingly being taught on
undergraduate programmes at
universities across Britain.

(
Dawson 2008
)



Nature of ICT in
teaching



Word
documents



Internet research



Email communication



Data
projector



PowerPoint



Excel sheets



Online
learning



CDs of science concept



Digital camera



Database/storage



Simulations



Electronics

text books



Virtual experience
/dissections



Online assessment



Data probes/loggers



E
-
Journals

/
portfolios



Discussion groups online



Virtual excursions



Web page design



Personal digital assistants


(
Li
-
Tsang, Lee et al. 2007
)

ICT
-
skills used for
intellectual disabilities




Use the mouse



Use of the keyboard



Browse the internet

This study to teach the intellectual
disabilities ICT skills for
entertainment and leisure

(
Umar and Jalil 2012
)

Basic ICT skills





Word processor



Developing portfolio



Searching info from CD
-
ROM



Creating slide presentation



Creating electronic
spreadsheet



Creating bulletin /

newsletter


Advance ICT skills




Producing graphics and
animation



Producing multimedia
using authoring
-
tools eg.
Flash,
Author ware



Internet application for
information access




Searching info from the
web



Recording and uploading
document on web (eg:
Youtube)



Using search engine (eg:
Google)



Internet application for
communication




Using web camera for
communication



Using social network sites
(e.g.: Facebook)



Sending and receiving
emails



Using chat rooms



Conducting tele
-
conference (e.g. Skype)




(
Adetimirin 2012
)




Word processing



Electronic communication
( email and internet)



Online searches



This was to ensure that when they
graduate they would be
able to
meet several proficiencies related
to writing, speaking, and using
information technology.

(
A
tasoy, Banker et al. 2012
)


Basic ICT skills



Copy and transfer files or
folders



Using copy paste
command



Zip file folder

These IT skills are ranked based on
how advanced they are. We have
classi
ed these

skills into three groups: basic IT
skills, medium
-
level IT skills, and
advanced IT skills




Medium skills



Formulate in spread sheet



Connecting device to
computer



Connecting computer to
network



Advance skills



Programming language



Problem solving involving
the internet and computers

(
Miliszewska 2008
)

First year




Develop word processing
spread sheet
, PowerPoint,
and


Paintbrush skills;




Access information
through the

Web and CD
ROM;



Use email;



Become familiar with
etiquette

of electronic
communication;




Use printers; download
and


Upload

data using a
variety of

data storage
devices (flash

drives,
memory sticks, CD

ROMs).





Second year




Import and export data


Between
Word documents
and Excel

spread sheets
;
Use digital

devices
and
DVD players;




Use online discussion
groups, blogs, wikis;



Participate in virtual
environ
ments;



Become familiar with
security

Mechanisms

of software
applications

including
communication

across the
Internet.


Third year




Install and configure
software

The specification of the ICT
core
graduate attribute for computer
science (CGA)


For 3 ears, each year the student
what will learn about the ICT

including firewalls and
anti
-
virus software;




Set up simple computer
net
-
works including
modems, mo
bile devices,
and wireless con
nections;



Develop multimedia
applications

including
production of

CD ROMs;



Use electronic
communication

in an optimal and sensitive
way

(create mailing lists,
refrain

from attaching big
documents

or sending global emails,
etc.).

(
Hashim, Razak et al. 2011
)




On and off the computer



Identify interface features



Use keyboard



Microsoft Word program



Power Point program



Microsoft

Excel program



Multimedia (Adobe
Photoshop) program



Web design


Women basic ICT skills

in
Malaysia

(
Miliszewska 2008
)


Called general



the use of software and
hardware tools
(Windows, word
processing,
spreadsheet
applications,
presentation software,
database applications,
Web app
lications,
mobile applications





the responsible use of
internet services (e
-
mail, Web browsing,
digital authoring,
elect
ronic

databases, principles of
digital communication).



According to the literature T
able

1
, the most ICT skills that mentioned by the researcher in the
previous studies is (operating system using, word press, excel sheet, spreadsheet, internet,
database, and graphic software)

Those skills is required by the organization and companies, in order for the student to get job
,
must

be qualified
and experience

with those skills, it is consider the basic ICT skills

or the
general skills for IT and no IT
students
, but it is important for all the organization whether IT
organization or non IT
organization,

T
able
3

showing the details about the ICT skills

Table
3
: summary of the literature survey

ICT Skills

What included

OS (operating System)



On and off the

computer



Install software



Copy files, transfer files and delete files




Word press

Using Microsoft work for create and write a
documents ,or edit text

Internet



Browse the internet



Search about information in the internet



Using the social networks



Open o
nline news



Online chat


Email



Send and receive email



Attachment email


Spreadsheet


Do spreadsheet for presentation


Database



Create database



Create table in the database



Remove or add row and
column

from the
database


Excel



Create table



Calculate using excel sheet



Do chart using excel

Graphic



Using Photoshop for photo edit



Using paint program



Transfer and download images from external
devices




skills regarding information and communication technologies (ICTs) have gained
utmost Importance for education, for employment and for everyday life use in the 21st
century. The ability

to use ICTs with confidence and efficiency is demanded from most
employers
.

While the basic skills that the researcher extracted it from the literatu
re, there is also advanced
skills, In the previous literature survey the researcher identified the basic ICT skills, so the
researcher conducted another round of research, the conclude of the latest study is obtaining
the advance computer science skills
(
Gallagher, Kaiser et al. 2010
;
Ayalew, Mbero et al.
2011
)
,
below is the details of the advance skills


1
-

Researches
problem, plan solutions and coordinates development to meet business
requirements , the skills can be list under system analysis job

2
-

Operating systems (Windows, Linux), security and networking , these skills
consider under the system administrator job

3
-

DBM
S (Oracle/MS SQL server/Mysql) SQL security, Works with the
administrative component of databases. The role includes developing and
designing the database strategy, monitoring and improving database performance
and capacity, and planning for future expansi
on requirements. The skills can be
listed under the database administrators job

4
-

HTML, XML, JvaScripts, Ajax, Java, ASP, SQL, PHP ,
Web application
development using a variety of programming languages and tools
, theses skills can
be under web developer job

5
-

Programming such as C/C++ , C#, .NET , java, OOP and software development ,
involved in the specification, designing, and implementation of a software system
and work with different languages and associated tools, these skills will consider
under software

developer job

6
-

Team working

Teamwork is the actions of individuals, brought together for a common purpose or
goal, which subordinate the needs of the individual to the needs of the group.

In

essence, each person on the team puts aside his or her individual

needs to

work
towards the larger group objective

The best approach to achieve teamwork ability is
project
-
based learning, which places greater emphasis on targeting the learning of
complex

experiences, geared to a specific goal or objective, in place of t
he traditional
academic approach strongly focusing on rote memorization of multiple information
items alienated from their practical, real
-
world uses
(
Jun 2010
)

Since the capability to work in teams has become

a key requirement on computer
science graduates, computer education not only embraces technical skills of computer
development but also
n
ecessitates communication and interaction among learne
rs
.


And normally the different between the advance ICT skills and the basic skills, the
advance
consider
under the computer science skills, and the basic consider under the
ICT skills. C
omputer Science is the study of the foundational principles and practices
of computation and computational thinking, and their application in the design and
development of

computer systems.

Information
and communication technology (ICT)
focuses on the creative and
productive use and application of technology and computer syste
ms, especially in
organizations. We take ICT to also include Information Technology, Applied ICT,
Digital Literacy and

Skills,
and e
-
safety, across the curriculum.


The two overlap, of course, especially in the early and primary years: an education in
Comp
uter Science includes aspects of the use and application of computers, and an
education in ICT covers

aspects of programming and understanding of computing
devices. But as learners progress to specialized subjects, differing characteristics
emerge which de
fine ICT and Computer Science as separate subjects with their own
qualifications
(
Kim and Lee 2013
)
:






The
different between the computer science
and the ICT is

ICT

Computer science

The study of computer systems and how they

are used

The study of how computer systems are built

and work

Human need is central to the subject

Computation is central to the subject

Concerned with the design, development and

evaluation of systems, with particular
emphasis

on the data, functional and usability

requirements of end users

Concerned with algorithmic thinking, and the

ways in which a real
-
world problem can be

decomposed in order to construct a working

solution

Focuses on building or programming a
solution

by using a combination of currently available

Solves problems and develops new systems
by

writing new software and developing

devices and software.

Inno
vative

computational approaches.

Emphasis on selecting, evaluating, designing

and configuring appropriate software and

devices. Programming is one method of

creating desired outcomes

Emphasis on principles and techniques for

building new software and d
esigning new

hardware. Programming and coding is a
central

technique to create outcomes

ICT supports, enhances and empowers human

activity and informs future developments.

Computation is a “lens” through which we
can

understand the natural world, and the nature
of

thought itself, in a new way.

Tending towards the higher level study and

application of ICT in a range of contexts,
from

academic to vocational.

Tending towards higher level academic study
of

Computing
and Computer Science



2.13

Methods of Selection


There are many techniques used for analysis the raw data in order to get the knowledge, and
that knowledge which is extracted from the data can be used for the problems solving in all
the fields of our life, th
e methods that used to extract the knowledge from the information
called data mining, d
ata mining, sometimes also called Knowledge Discovery in databases
(KDD),
Knowledge Discovery and Data Mining is a multidisciplinary area focusing upon
methodologies fo
r extracting useful knowledge from data and there are several useful KDD
tools to extracting the knowledge. The data mining has attracted a great deal of attention in
the information technology industry; due to availability of large volume of data which is

stored in various formats like files, texts, records, images, sounds, videos, scientific data and
many new data formats. There is imminent need for turning such huge data into meaningful
information and knowledge. The data collected from various applicati
ons require a proper
data mining technique to extract the knowledge from large repositories for decision making,
Data mining and knowledge discovery in databases are treated as synonyms, but data mining
is actually a step in the process of knowledge discov
ery.
(
Sachin and Vijay 2012
)
. The
sequences of steps identified in extracting knowledge from data are shown in Fig

4


Figure 4: step of extracting knowledge
from data
(
Sachin and Vijay 2012
)

The
field of study is to use the dat
a mining in the education, the
knowledge that extracted
from the education data can be
used to increase the quality of education. Data mining can be
used for decision making in educational
(
Yadav, Bharadwaj et al. 2012
)
.

When the data mining apply in the education wil
l call it as education data mining, educational
Data Mining (EDM) is an emerging discipline, concerned with developing methods for
exploring the unique types of data that come from educational settings, and using those
methods to better understand students
, and the settings which they learn in. Educational Data
Mining, concern with developing new methods to discover knowledge from educational
database. Lack of deep and enough knowledge in higher educational system may prevent
system management to achieve qu
ality objectives, data mining methodology can help this
knowledge gaps in higher education
(
Pandey and Pal 2011
)
.

Within the KDD process, there can be used different means of data mining analysis that allow
getting important in
formation from the database such as: classification, clustering,
association, decision tree, neural network etc.
(
Pandey and Pal 2011
)


Classification

2.13.1

Classification is a predictive data mining technique, makes predication
about values of data
using know results found from different data. Classification maps data into predefined groups
are classes. It is often referred to as supervised learning because the classes are determined
before examining the data. They often describ
e these classes by looking at the characteristic
of data already known to belong to the classes
(
Pandey and Pal 2011
)
.

Classification or discriminant analysis is used to predict class labels

(
describes future
situation).
Classification is supervised technique which is used to label newly encountered
(still unlabeled) patterns from a collection of labeled (pre
-
classified) patterns. Some popular
classification methods include logistic regression, support vector machines and

decision
trees
(
Sachin and Vijay 2012
)



Decision Tree

2.13.2

A decision tree is a flow
-
chart
-
like tree structure, where each internal node is denoted by
rectangles,

and leaf nodes are denoted by ovals. All internal nodes have two or more child
nodes. All internal nodes contain splits, which test the value of an expression of the attributes.
Arcs from an internal node to its children are labeled with distinct outcomes

of the test. Each
leaf node has a class label associated with it The decision tree classifier has two
phases
(
Bhardwaj and Pal 2012
)
.




Clustering

2.13.3

Clustering analysis is a common unsupervised learning technique. Its aim

is to group

objects
into different categories. That is, a collection of data objects that are similar to

one another are
grouped into the same cluster and the objects that are dissimilar are

grouped into other
clusters
,
It is an important technique in dat
a mining to analyse high
-
dimensional data and
large scale databases.

Clustering algorithms can be classified into

hierarchical and non
-
hierarchical

algorithms
;
the
hierarchical procedure produces a tree
-
like

structure, which is able to
see the relationship

among entities.

The hierarchical

clustering procedure can be agglomerative or divisive

The
non
-
hierarchical methods do not possess tree
-
like structures but assign some cluster seeds

to central places, also called k
-
means clustering.



K
-
means

2.13.4

The k
-
means

algorithm is one of the best known and simplest clustering algorithms

It

was
proposed over 50 years ago and still widely used
, t
his is due to its ease of implementation,
simplicity, and superior

feasibility and efficiency in dealing with a large amount o
f data
.









Summary

of the Chapter


The literature review was carried out thoroughly by viewing ICT skills, and ICT usage in
many failed of this life, the
study highlights several ICT factors, and in which field of o
ur
life
that ICT play important
effect, the needed of ICT skills, and the barriers
.

There is many researchers in the literature mentioned about the ICT standard factors that
required by most of the organizations, companies and higher education institutes.

In this
research

extracted

the i
mportant ICT factors from sever
al

research journal and paper, those
factors can be
used

as
standard

ICT factors which is may use for the student ICT skills
evaluation
.

The researchers
depend

on those factors because the factors extracted from the
employability ICT skills needed for most of the organization nowadays
, by comparing

the
ICT skills that extract from the previous studies, it is almost similar to the ECDL (
European
Computer Driving

License
) or ICDL (International
Computer Driving
License
).

The I
CDL
or ECDL
certificate proves that its recipient possesses some basic skills in using a
computer,

such as editing a document with a word processor, preparing a table using a
spreadsheet, que
rying

a database, browsing the Web. The ECDL syl
labus consists of seven
modules, b
asic con
cepts of information technology, u
sing the computer and managing file
s,
word processing, spreadsheets, database, presentation and
Information

and
communication
(
Calzarossa, Ciancarini et al. 2007
)
.

The current skills
are considered general skills or standard skills for all the organization and
the HEI
(
Miliszewska 2008
)
,
the level of students skills can b
e measure according to the
student experience with the above mentioned skills in Table 3.


While there is basic skills, there is also advance skills, which is consider computer science
advance skills, such as

system analysis, system administrator

, database administrator

skills,
web developer , software developer,
and
team work skills
, all those skills are advanced
computer science skills, if the student or employ has those skills will be under the advance
computer science skills, so in the curren
t research literature, it is concluded that there is basic
ICT skills, and advance computer science skills.

Since this research is dealing with student
data, so will titled as EDM , will deal with student information and extract the knowledge
from the info
rmation to predict the good student and more sufficient student for the
appropriate job.














References







Act, S. M. (2005). "COMMUNICATION FROM THE COMMISSION TO THE COUNCIL, THE EUROPEAN
PARLIAMENT, THE EUROPEAN ECONOMIC
AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE
REGIONS."



Adetimirin, A. E. (2012). "ICT literacy among undergraduates in Nigerian universities."
Education and
Information Technologies

17
(4): 381
-
397.



Ahmad Rizal, M. and B. Yahya (2011). "Elements of emp
loyability skills among students from
community colleges Malaysia."
Journal of Technical, Vocational & Engineering Education

4
: 1
-
11.



Alston, A. J., D. Cromartie, et al. (2009). "The importance of employability skills as perceived by the
employers of uni
ted states’ land
-
Grant College and university graduates."
Journal of Southern
Agricultural Education Research

59
(1): 59
-
72.



Anwar, M. and N. Ahmed (2011).
Knowledge Mining in Supervised and Unsupervised Assessment
Data of Students’ Performance
. 2011 2nd
International Conference on Networking and Information
Technology IPCSIT vol.



Atasoy, H., R. Banker, et al. (2012). "IT Skills and Employment Opportunities of Workers."



Ayalew, Y., Z. Mbero, et al. (2011). "Computing knowledge and skills demand: A cont
ent analysis of
job adverts in Botswana."



Babin, R., K. Grant, et al. (2010). "Identifying influencers in high school student ICT career choice."
Information Systems Educational Journal

8
: 26.



Babu, B. R., P. Vinayagamoorthy, et al. (2007). "ICT skills among librarians in engineering educational
institutions in Tamil Nadu."
DESIDOC Journal of Library & Information Technology

27
(6): 55
-
64.



Beauchamp, G. and S. Kennewell (2008). "The influence o
f ICT on the interactivity of teaching."
Education and Information Technologies

13
(4): 305
-
315.



Ben Youssef, A. and M. Dahmani (2008). "The Impact of ICT on Student Performance in Higher
Education: Direct Effects, Indirect Effects and Organisational Chan
ge."
Revista de Universidad y
Sociedad del Conocimiento, RUSC

5
(1): 13.



Bhardwaj, B. K. and S. Pal (2012). "Data Mining: A prediction for performance improvement using
classification."
arXiv preprint arXiv:1201.3418
.



Calzarossa, M. C., P. Ciancarini, e
t al. (2007). "The ECDL programme in italian universities."
Computers & Education

49
(2): 514
-
529.



Choueiri, E. M., G. M. Choueiri, et al. (2012).
ICT capacity building and higher education
. Interactive
Mobile and Computer Aided Learning (IMCL), 2012 Inte
rnational Conference on, IEEE.



Dawson, V. (2008). "Use of information communication technology by early career science teachers
in Western Australia."
International Journal of Science Education

30
(2): 203
-
219.



de Guadalupe Arras
-
Vota, A. M., C. A. Torr
es
-
Gastelú, et al. "Students’ perceptions about their
competencies in Information and Communication Technologies (ICTs)."
Revista Latina de
Comunicación Social

66
.



de Guadalupe Arras
-
Vota, A. M., C. A. Torres
-
Gastelú, et al. (2011). "Students’ perception
s about
their competencies in Information and Communication Technologies (ICTs)."
Revista Latina de
Comunicación Social

66
.



Edgar, L. D., D. M. Johnson, et al. (2012). "A 10
-
year assessment of information and communication
technology tasks required in undergraduate agriculture courses."
Computers & Education
.



Eley, R., T. Fallon, et al. (2008). "The status of training and edu
cation in information and computer
technology of Australian nurses: a national survey."
Journal of clinical nursing

17
(20): 2758
-
2767.



Elwood, J. and G. MacLean (2009). "ICT usage and student perceptions in Cambodia and Japan."
International Journal of E
merging Technologies and Society

7
(2): 65
-
82.



Gallagher, K. P., K. M. Kaiser, et al. (2010). "The requisite variety of skills for IT professionals."
Communications of the ACM

53
(6): 144
-
148.



Hakkarainen, K., L. Ilomäki, et al. (2000). "Students’ skills and practices of using ICT: Results of a
national assessment in Finland."
Computers & Education

34
(2): 103
-
117.



Hamzah, M., A. Ismail, et al. (2009). "The impact of technology change in Malays
ian Smart Schools on
Islamic education teachers and students."
World Academy of Science, Engineering and Technology

49
: 379
-
391.



Hashim, F., N. A. Razak, et al. (2011). "Empowering rural women entrepreneurs with ict skills: An
impact study of 1nita proje
ct in Malaysia."
Procedia
-
Social and Behavioral Sciences

15
: 3779
-
3783.



Hashim, J. (2008). "Learning barriers in adopting ICT among selected working women in Malaysia."
Gender in Management: An International Journal

23
(5): 317
-
336.



Haywood, J., D. Hayw
ood, et al. (2004). "A comparison of ICT skills and students across Europe."
Journal of eLiteracy

1
(2): 69
-
81.



Ilomäki, L. and P. Rantanen (2007). "Intensive use of ICT in school: Developing differences in
students’ ICT expertise."
Computers & Education

48
(1): 119
-
136.



Ismail, I., S. N. Azizan, et al. (2011). "Internet as an Influencing Factor of Teachers’ Confidence in
Using ICT."
Malaysian Journal of Distance Education

13
(61): 1
-
74.



Jun, H. (2010).
Improving undergraduates' teamwork skills by adapti
ng project
-
based learning
methodology
. Computer Science and Education (ICCSE), 2010 5th International Conference on, IEEE.



Kim, J. and W. Lee (2013). "Meanings of criteria and norms: Analyses and comparisons of ICT literacy
competencies of middle school
students."
Computers & Education

64
: 81
-
94.



Koppi, T., M. Roberts, et al. (2012). "Perceptions of a gender
-
inclusive curriculum amongst Australian
information and communications technology academics."



Kumar, R. (2008). "Convergence of ICT and Education
."
World Academy of Science, Engineering and
Technology

40
.



Kumar, R. (2008). "Convergence of ICT and Education."
World Academy of Science, Engineering and
Technology

40
(2008): 556
-
559.



Li
-
Tsang, C. W., M. Y. Lee, et al. (2007). "A 6
-
month follow
-
up of

the effects of an information and
communication technology (ICT) training programme on people with intellectual disabilities."
Research in developmental disabilities

28
(6): 559
-
566.



Lotriet, H. H., M. Matthee, et al. (2010). "Challenges in ascertaining
ICT skills requirements in South
Africa."



Malaysia, M. (2007). "ICT adoption in Malaysian SMEs from services sectors: preliminary findings."
Journal of Internet Banking and Commerce

12
(3).



Mbah, T. B. (2010). "The impact of ICT on students’ study habit
s. Case study: University of Buea,
Cameroon."
Journal of Science and technology education research

1
(5): 107
-
110.



McLachlan, C., A. Craig, et al. (2010).
Student perceptions of ICT: a gendered analysis
. Proceedings of
the Twelfth Australasian Conference
on Computing Education
-
Volume 103, Australian Computer
Society, Inc.



McLachlan, M. C. A., B. H. BIS, et al. (2011). "Interpretation and Delivery of ICT Curricula in Secondary
Schools."



McMahon, J., J. Gardner, et al. (1999). "Barriers to student comput
er usage: staff and student
perceptions."
Journal of Computer Assisted Learning

15
(4): 302
-
311.



Miliszewska, I. (2008). "ICT skills: An essential graduate skill in today’s global economy."
Journal of
Issues in Informing Science and Information Technology

5
: 101
-
109.



Mohamed, A. M., T. C. Aik, et al. (2011). "Dental Students’ Attitudes and Perceptions towards ICT
Resources and Skills."
Procedia
-
Social and Behavioral Sciences

18
: 400
-
403.



Nurses’ICT, S. (2010). "THE TRANSFERABILITY OF INFORMATION AND CO
MMUNICATION
TECHNOLOGY SKILLS FROM UNIVERSITY TO THE WORKPLACE: A QUALITATIVE DESCRIPTIVE STUDY."
HNE
: 34.



Pandey, U. K. and S. Pal (2011). "Data Mining: A prediction of performer or underperformer using
classification."
arXiv preprint arXiv:1104.4163
.



Pillai, S. (2009). "Enhancing Graduate Employability through University
-
Industry Partnerships."



Romero, C. and S. Ventura (2013). "Data mining in education."
Wiley Interdisciplinary Reviews: Data
Mining and Knowledge Discovery

3
(1): 12
-
27.



Ruxwana, N.

L., M. E. Herselman, et al. (2010). "ICT applications as e
-
health solutions in rural
healthcare in the Eastern Cape Province of South Africa."
Health Information Management Journal

39
(1): 17
-
30.



Sachin, R. B. and M. S. Vijay (2012).
A Survey and Future
Vision of Data Mining in Educational Field
.
Advanced Computing & Communication Technologies (ACCT), 2012 Second International Conference
on, IEEE.



Salamat, M. A., S. Hassan, et al. (2011). "Electronic Participation in Malaysia."
Journal of e
-
Government S
tudies and Best Practices

11
.



Scheuer, O. and B. M. McLaren (2011). "Educational data mining."
The Encyclopedia of the Sciences
of Learning. New York, NY: Springer
.



Selamat, Z., N. Jaffar, et al. (2011). "ICT Adoption in Malaysian SMEs."



Senik, R. and M. Broad (2011). "Information Technology Skills Development for Accounting
Graduates: Intervening Conditions."
International Education Studies

4
(2): p105.



Sheard, J., A. Carbone, et al. (2010). "Student engagement in first year of an ICT de
gree: staff and
student perceptions."
Computer Science Education

20
(1): 1
-
16.



Sheard, J., A. Carbone, et al. (2008).
Performance and progression of first year ICT students
.
Proceedings of the tenth conference on Australasian computing education
-
Volume 78
, Australian
Computer Society, Inc.



Stoner, G. (2009). "Accounting Students' IT Application Skills over a 10
-
year Period."
Accounting
Education

18
(1): 7
-
31.



Taleb, Z. (2012). "Information and Communication Technology Skills Ranking in Secondary School
Curriculum."
Procedia
-
Social and Behavioral Sciences

69
: 1093
-
1101.



Teo, T. (2008). "Assessing the computer attitudes of students: An Asian perspective."
Computers in
Human Behavior

24
(4): 1634
-
1642.



Torres
-
Gastelú, C.
-
A. and A.
-
M. García
-
Valcárcel
-
Muñ
oz
-
Repiso (2011). "Students’ perceptions about
their competencies in Information and Communication Technologies (ICTs)."



Umar, I. N. and N. A. Jalil (2012). "ICT Skills, Practices and Barriers of Its Use Among Secondary School
Students."
Procedia
-
Social
and Behavioral Sciences

46
: 5672
-
5676.



Unwin, T. (2009).
ICT4D: Information and communication technology for development
, Cambridge
University Press.



van Deursen, A. and S. van Diepen (2012). "Information and strategic Internet skills of secondary
students: a performance test."
Computers & Education
.



Willmer, M. (2007). "How nursing leadership and management interventions could facilitate the
effectiv
e use of ICT by student nurses."
Journal of nursing management

15
(2): 207
-
213.



Yadav, S. K., B. Bharadwaj, et al. (2012). "Data mining applications: A comparative study for
predicting student's performance."
arXiv preprint arXiv:1202.4815
.