New trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teaching is an intended activity. Education is the
process of acquiring knowledge, skills and trends by the person who wants to learn
himself / herself. Accordingly, learning is a principal branch of teaching, because it is
considered one of the varied methods in carrying out the teaching process. From this
fact did the need to use a good theory as a guide to the later researches come. Its value
depends highly on the studies and researches it produces to help the researcher find a
way that direct him to discover new aspects.
* The Research purpose:
This research aims at knowing the new trends and methods in the theory of
teaching and learning.
* The Research Boundary:
This research is limited to: finding out the theory of teaching and learning and
putting a balance between them. In addition to discovering the features and methods
of building the teaching theory. Moreover, it aims at putting a limit to the role played
by the theory in the teaching and learning process.
Specifying terminology:
Terms concerning teaching and learning are specified in the research itself.
In probability theory generalizing distribution is an important area. Several distributions are inappropriate for data modeling, either symmetrical, semi-symmetrical, or heavily skewed. In this paper, a new compound distribution with four parameters called Marshall Olkin Marshall Olkin Weibull (MOMOWe) is introduced. Several important statistical properties of new distribution were studied and examined. The estimation of unknown four parameters was carried out according to the maximum likelihood estimation method. The flexibility of MOMOWe distribution is demonstrated by the adoption of two real datasets (semi-symmetric and right-skewed) with different information fitting criteria. Su
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