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.
New data on jumping spiders (Salticidae) and tangle-web spiders (Theridiidae) of Armenia are provided on the basis of recently collected specimens in various regions of Armenia. One species, Ballus rufipes (Simon, 1868) is recorded as new to the Caucasus Region, in addition to the following species: Neon reticulatus (Blackwall, 1853), Pellenes brevis (Simon, 1868), Salticus scenicus (Clerck, 1757) and Synageles dalmaticus (Keyserling, 1863) that belong to a family Salticidae, are recorded in Armenia for the first time.
A further 7 species of Theridiidae are recorded in Armenia for the first time Kochiura aulica (C. L. Koch, 1838), Steatoda albomaculata (De Geer, 1778), Steatoda bipunctata (Linnaeus, 1758), Steatoda castanea Clerk, 175
The current study aims to investigate the effect of the interaction between the use of the improve strategy in teaching mathematics and the level of academic achievement on the acquisition of algebraic concepts and habits of mind among tenth-grade students in Oman. The study adopted the experimental method, based on a quasi-experimental design with two groups: experimental and control groups and pre-post-measurement. The study sample consisted of (28) 10th-grade students as an experimental group and 26 of 10th-grade students as a control group in Al-Tufail bin Amr School in South Al Batinah. The differences in the pretest and posttest gains were analyzed using mean, standard deviation, ANCOVA, t-test, effect size (eta-square), and two-wa
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... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of
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