have shown no interest in engineering careers and
are no need of the chances provided by the
engineering education. The most important thing in
this field will be needed learners to change ways for
taking part in the basic ways of formal searching and
the application of key engineering words, as well as
changing searching of ethnicity, gender, and others.
Data mining technology are increasingly used in
education and teaching, and in particular, in public
safety fields. Person working in different companies
are increasingly want to know that “what do social
safety data means” and think that the results of data
oriented analysis and results to improve public
service safety, payment effectiveness, and others.
This paper is trying to show the discussion on how
teachers and learners of engineering education can
build methods and tools to attract, inform, and use
engineering words and queries in university learners.
The proposed work of engineering education
consists of educational interfaces and other
techniques for engineering education and learning.
2 THE RELATED WORK
One of the basic problems to presentation is which
engineering words are needed to teach university
learners who lack the basic skills needed to take part
in many of the lessons of a university level
engineering lessons? Some papers have issued these
questions (A. Begel and E. Kopler, 2005; B.S.
Bloom, 1964; P.C. Blumenfeld, 2006). Merril et al.
think key engineering words as concepts
representing optimization, constraints, and
prediction analysis. Besides basic knowledge of key
engineering words, the usage of basic skills such as
the ability to mining and analyzing systems and their
mode, show some experiments and evaluate training
set that can accurately provide the fulfillment of
product requirements are needed (G. Campbell, R.
Denes, and C. Morrison, 2000). Furthermore, Custer
et al. defined a set of 14 core engineering concepts
(design, modeling, constraints, innovation, systems,
optimization, experimentation, prototyping,
tradeoffs, analysis, problem solving, functionality,
visualization, and efficiency) that are coherent with
the aforementioned propositions. The cognitive
domain in the Bloom Taxonomy includes six levels
of learning activities (H. Christensen et al., 2009).
Each level is related to a number of words that
describe core frameworks in the learning process.
Information maintaining and change of learning is
needed for teaching and learning. Thus, a cover of
the concepts is expected in any engineering lessons.
3 SOCIAL SAFTY MINING
In China, a number of social safety functions and
social data are given by the government to help
person to be efficient and to provide related work.
Fig. 1 shows a basic relationship between teachers
and learners in the engineering education process. A
learner begins a related function, which is evaluated
by the teacher. Lessons are arranged on the
interactive of learner entitlement and profiles. The
learner is required to represent and transfer that may
interact the learner entitlement and profiles. Once a
learner representation is begun, it will be evaluated
by the teacher. As a result, learners are further
evaluated and changed if necessary. In other words,
teachers to the learner can happen for reasons such
as wrong representations. The teacher will try to
recover the need, and the learner will be required to
turn back such needs through replacement between
the teacher and the learner.
Figure 1: A cause–effect relationship in the social welfare
business.
Similar to other field, data mining technologies
in social safety are put by needs and related data. It
has three parts: the data part, the learner part, and the
data mining goal part. The data layer includes the
main aims and expectations for the usage of social
safety functions. For example, the main function,
including learner function improvement, learner
function correctness enhancement, learner function
integrity enhancement, learner function management
and prevention, learner function cause identification,
learner function transparency improvement, learner
function performance enhancement, learner function
delivery enhancement, learner function profiling,
learner function need satisfaction, learner function
assurance, learner function detection, learner
function process optimization, and learner function
indicator enhancement.
The Data Mining on Social Safety Data for Engineering Education
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