Students' passive listening to their teacher's reading is one of main
reasons behindtheir weakness in the reading skill which in its turn may
hinderachieving the in desired objectives.
When exploiting critical thinking, which will lead to deeper
understanding of the intellectual content, in learning and accurate and
correct students' outcomes.
Active listening allows paying attention to the speaker, asking him,
arguing with him, judging what he says, and making decision on what
he says. For this reason, the researcher felt the need for preforming a
study to identify the effect of critical listening on developing students'
critical thinking at reading in the Kurdish language department.
The researcher has chosen the second stage students at the
department of Kurdish language department, collage of education, Ibn-
Rushd for the academic year 2008-2009. The sample consists of 60
male/ female students distributing on 30 as the control group and 30 as
the experimental group. The researcher has matched the two groups
according to the variables of age, IQ, and the students' final marks in
their previous stage at reading.
The experiment lasted one semester during which the researcher
herself has taught both groups. The researcher has also prepared a test
on critical thinking which consists of fire sub-test, each contains some
situation. In the statistical treatment of the results, T-test for two
independent samples and person's correlational coefficients have been
used. It has been revealed that there is a statistically significance
difference at 0.05 level of significance infarour to the experimental
group which has been taught according to the critical listening strategy.
The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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... Show MoreMetal (III) and (II) coordination compounds of o- phenylenediamine, oxalic acid dihydrate and 8-hydroxyquinoline were synthesized for mixed ligand complexes and characterized using FT-IR, UV-Vis and mass spectra, atomic absorption, elemental analysis, electric conductance and magnetic susceptibility measurements. In addition, thermal behavior (TGA) of the metal complexes (1-6) showed good agreement with the formula suggested from the analytical data. The stoichiometric reaction between the metal (III) and (II) ions with three various ligands in molar ratio at aqueous ethyl alchol for (1:1:1:1) (M: O-PDA: OA: 8-HQ) [where M = Cr+3, Mn+2, Co+2, Ni+2. Cu+2 and Zn+2; O-PDA = O-Phenylenediamine; OA = Oxalic acid and 8-HQ = 8-Hydroxyquinoline]. R
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