The Effect of Cooperative Learning on Academic Achievement of Grade Nine Students in Mathematics: The Case of Mettu Secondary and Preparatory School
The aim of this study was to examine the effect of
cooperative learning method on student’s academic achievement and
on the achievement level over a usual method in teaching different
topics of mathematics. The study also examines the perceptions of
students towards cooperative learning. Cooperative learning is the
instructional strategy in which pairs or small groups of students with
different levels of ability work together to accomplish a shared goal.
The aim of this cooperation is for students to maximize their own
and each other learning, with members striving for joint benefit.
The teacher’s role changes from wise on the wise to guide on
the side. Cooperative learning due to its influential aspects is the
most prevalent teaching-learning technique in the modern world.
Therefore the study was conducted in order to examine the effect
of cooperative learning on the academic achievement of grade 9
students in Mathematics in case of Mettu secondary school. Two
sample sections are randomly selected by which one section served
randomly as an experimental and the other as a comparison group.
Data gathering instruments are achievement tests and questionnaires.
A treatment of STAD method of cooperative learning was provided
to the experimental group while the usual method is used in the
comparison group. The experiment lasted for one semester. To
determine the effect of cooperative learning on the student’s academic
achievement, the significance of difference between the scores of
groups at 0.05 levels was tested by applying t test. The effect size
was calculated to see the strength of the treatment. The student’s
perceptions about the method were tested by percentiles of the
questionnaires. During data analysis, each group was divided into
high and low achievers on basis of their previous Mathematics result.
Data analysis revealed that both the experimental and comparison
groups were almost equal in Mathematics at the beginning of the
experiment. The experimental group out scored significantly than
comparison group on posttest. Additionally, the comparison of mean
posttest scores of high achievers indicates significant difference
between the two groups. The same is true for low achiever students
of both groups on posttest. Hence, the result of the study indicates
the effectiveness of the method for Mathematics topics as compared
to usual method of teaching.
Cooperative learning, academic achievement,
experimental group, comparison group.
Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising
In seismic data processing, attenuation of random noise
is the basic step to improve quality of data for further application
of seismic data in exploration and development in different gas
and oil industries. The signal-to-noise ratio of the data also highly
determines quality of seismic data. This factor affects the reliability
as well as the accuracy of seismic signal during interpretation
for different purposes in different companies. To use seismic data
for further application and interpretation, we need to improve the
signal-to-noise ration while attenuating random noise effectively.
To improve the signal-to-noise ration and attenuating seismic
random noise by preserving important features and information
about seismic signals, we introduce the concept of anisotropic
total fractional order denoising algorithm. The anisotropic total
fractional order variation model defined in fractional order bounded
variation is proposed as a regularization in seismic denoising. The
split Bregman algorithm is employed to solve the minimization
problem of the anisotropic total fractional order variation model
and the corresponding denoising algorithm for the proposed method
is derived. We test the effectiveness of theproposed method for
synthetic and real seismic data sets and the denoised result is
compared with F-X deconvolution and non-local means denoising
Anisotropic total fractional order variation, fractional
order bounded variation, seismic random noise attenuation, Split