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~ Psalms 147:3
Dear visitor,
الذى فى الاعلى
Problem Solving is a process of overcoming difficulties that
appear to interfere with the attainment of a goal. It is the
procedure of making adjustments in spite of interference.
The Problem
The problem is often reintroduced in the body of the article.
The problem section is the part of the paper where the
writer shows that s/he shares readers’ concerns. This
section of the paper may describe a local situation in
sufficient detail to provide a context for the solution.
The description of the problem helps the reader identify
with the context described to the extent that s/he may feel
that the situation is actually very similar to his/her own.
It is important to note that all the paragraphs and even
the sentences normally work to serve the larger
organization of the text.
Solution
At some point in this type of article, one expects a switch
from problem to solution.
The change in orientation from problem to solution is
indicated not only by the heading, which is the inverse of
the problem section, but by the beginning of the sentences,
which substitute passive students for active problem-solving
teachers and by a switch from synonyms of problem or
words of negation to synonyms of solution or the agents of
change (teachers).
Problem-solving behavior occurs in a novel or difficult
situations in which a solution is not obtainable by the
habitual methods of applying concepts and principles
derived from experience in very similar situations.
Problem-solving is a process of overcoming difficulties that
procedure of making adjustments in spite of interference
AI-driven problem-solving uses artificial intelligence (AI) to
analyze data, identify patterns, and provide effective solutions
to complex problems. It involves training AI models with
relevant data, generating solutions based on analysis, and
validating their effectiveness. This approach complements
human decision-making by offering data-driven insights.
However, ethical considerations and transparency are
vital for responsible AI implementation.
AI-driven problem-solving works by leveraging various
AI techniques and algorithms to process data, analyze
patterns, and generate solutions.
Data that carries essence is compiled from a pack of
sources, including databases, sensors, and online platforms.
This data can be structured (e.g., numerical data) or
unstructured (e.g., text, images, videos).
The collected data is cleaned, transformed, and organized
to ensure its quality and compatibility with AI models. This
step involves clearing noise, handling missing values, and
standardizing the data format.
The preprocessed data is used to train AI models, which
can include machine learning algorithms like neural
networks, decision trees, or support vector machines.
During training, the models learn to recognize patterns
and connections within the data.
Once the AI models have undergone training, they can
examine fresh data by leveraging the acquired patterns
to make predictions or decisions. This analysis contains
various tasks, including classification, regression,
clustering, and natural language processing.
The AI models develop solutions to the given problem
based on the analysis and inference performed.
These solutions encompass a range of outputs such as
recommendations, optimizations, predictions, and more,
tailored to the specific problem domain.
The generated solutions are evaluated and validated to
assess their accuracy and effectiveness. If necessary,
the AI models can be refined by retraining them with
updated data or adjusting their parameters to enhance
their performance.
After validating the AI models, the next step involves
deploying and integrating the generated solutions into
existing systems or processes. This may require the
development of user interfaces, APIs, or other mechanisms
to ensure that the AI-driven solutions are accessible and
usable by stakeholders.
AI-driven problem-solving is an iterative process.
The deployed solutions are continuously monitored to
ensure they perform as expected and remain up-to-date.
Feedback from users and ongoing data collection can be
used to refine and improve the AI models over time.
It’s important to note that the specific details of how
AI-driven problem-solving works can vary depending
on the problem domain, the available data, and the chosen
AI techniques. Additionally, ethical considerations,
transparency, and interpretability should be taken into
account throughout the entire process to ensure
responsible and trustworthy AI implementations.
In everyday life, man faces varieties of problems.
There are needs and motives that are to be satisfied.
For this , purposes definite goals or aims are set.
In an attempt for the realization of the goals, one
experiences obstacles and interference in an attempt
to achieve them. This creates problems. Serious
and deliberate efforts have to be made to overcome
these impediments.
Problem-Solving has been regarded as a form of
complex learning. In problem situations, a response
is not always readily available to overcome the
obstacles and reach the goal. Recognizing and
adapting our perceptual, cognitive, verbal and motor
responses are necessary to arrive at the correct
response which will solve the problem. In other
words, modification of our behavior is necessary to
arrive at the solution.
Revising:
After writing the first draft, one needs to see how the
text looks to an uninitiated reader.
One way of revising is to try to read the article as if
one were unfamiliar with the text.
One should also give the article t o a colleague who
may have many comments or suggestions and may
find points which are unclear.
One of the most important points would be to insure
that the article actually includes the content and
structure promised in the introduction.
Conclusion
The conclusion can be seen as a mirror image of the
introduction.Whereas the introduction starts from general
and moves to specific, the conclusion starts with the
specific study or technique described in the article and
moves to the general.
If we consider the conclusion to be some sort of inverse
of the introduction, we might expect the conclusion to
evaluate a technique positively, and then move on to a
more general situation.
In the conclusion the writer can use the specific example
described in detail in the article as a launching point for
further study or to remind readers that s/he is treating a
general problem or has found a solution to additional,
more general problems.
A method of problem-solving in which a problem is
compared to similar problems in nature or other
settings, providing solutions that could potentially
be applied.
A technique used to encourage creative thinking in
which the parts of a subject, problem, or task are
listed, and then ways to change those component
parts are examined.
listed, and then options for changing or improving
each part are considered.
which the parts of a subject, problem or task listed
and then the problem solver uses analogies to other
contexts to generate and consider potential solutions.
A technique used to encourage creative problem
solving which extends on attribute transferring. A
matrix is created, listing concrete attributes along the
x-axis, and the ideas from a second attribute along
with the y-axis, yielding a long list of idea combinations.
SCAMPER stands for Substitute, Combine, Adapt,
Modify-Magnify-Minify, Put to other uses, and Reverse
or Rearrange. It is an idea checklist for solving design
problems.
A problem-solving technique in which an individual is
asked to consider the ways problems of this type are
solved in nature.
challenged to become part of the problem to view it
from a new perspective and identify possible solutions.
A problem-solving process in which participants are
asked to consider outlandish, fantastic or bizarre
solutions which may lead to original and ground-
breaking ideas.
A problem-solving technique in which participants are
challenged to generate a two-word phrase related to
the design problem being considered and that
appears self-contradictory. The process of
brainstorming this phrase can stimulate design ideas.
An activity in which problem solvers are asked to
identify the next steps to implement their creative
ideas. This step follows the idea generation stage
and the narrowing of ideas to one or more feasible
solutions. The process helps participants to view
implementation as a viable next step.
Skills aimed at aiding students to be critical, logical,
and evaluative thinkers. They include analysis,
comparison, classification, synthesis, generalization,
discrimination, inference, planning, predicting, and
identifying cause-effect relationships.
View Other Resources:
1-The Conversation Class
2-Good Teaching is Timeless.
3-Puns, puzzles and Riddles.
4-Curiosity and Comprehension.
5-A Classroom Language Journal.
6- Twenty Testing mistakes to avoid.
7-Creating a storytelling Classroom.
8-Story Theater in Teaching English.
Lighter Slides:
1-Lighter slides: 1, 2, 3, 4.
2-Funny Stories.
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