E-mail: bbayraktar@uludag.edu.tr, İş Tel: +90(224) 294 22 98. Adres: UÜ, Eğitim Fakültesi, İlköğretim Bölümü, Matematik Eğitimi Anabilim Dalı, 16059 Görükle / BURSA
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Website:
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Objective of the Course:
Know the bases of algorithm concept and apply it in computer environment. To produce the algorithms of applications in mathematics courses. To understand the basics of software languages.
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Contribution of the Course to Professional Development
Creates and develops the knowledge base of the prospective teacher. Comprehends the concepts related to the field and the relations between concepts based on the competencies gained in secondary education. Have defines and analyzes problems related to his field, and develops solutions based on evidence and research.
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Learning Outcomes:
1
To be able to analyze the problem in terms of establishing a mathematical model.;
2
To be able to create a mathematical model of some problems in our daily life and to apply solution methods.;
3
Simple linear mat. Be able to create models;
4
To be able to introduce the concept of Algorithm and Algorithm. Know the features that should be in the algorithm.;
5
To be able to draw the flow diagram and know how to test the algorithm.;
6
To be able to develop algorithms software on arrays and matrices;
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To be able to produce algorithms and software of numerical methods he / she has seen in mathematics courses.;
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Course Content:
Week
Theoretical
Practical
1
Modeling concept. Model types and classification.
2
Model types and classification.
Classification of mathematical models. Principles of creating a mathematical model.
3
Principles of creating a mathematical model.
Linear mathematical model. Business problems and mathematical model. A mathematical model of an enterprise.
4
A mathematical model of an enterprise.
Analysis of linear mathematical models. Examples.
5
A mathematical model of an enterprise.
Analysis of linear mathematical models. Examples.
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Examples.
Nonlinear mathematical models and solution methods.
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Nonlinear mathematical models and solution methods.
Sample mathematical models and solution methods.
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Sample mathematical models and solution methods.
Algorithm concept and introduction of algorithm. Features that should be in the algorithm. Algorithm design.
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Algorithm design.
Flowchart diagrams and basic structures of algorithms Complex algorithms and functions. Algorithm applications.
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Algorithm applications.
Software languages. The structure of a computer language (alphabet, special words, expressions, rules, appearance). Software Applications.
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Software Applications.
Algorithms and software on arrays and matrices.
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Software Applications.
Algorithms and software on arrays and matrices.
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Algorithms and software on arrays and matrices.
Approximate solution of nonlinear equations (Algebra, Simple iteration and Newton method (tangent method) algorithms and software.
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Algorithms and software on arrays and matrices.
Approximate solution of nonlinear equations (Algebra, Simple iteration and Newton method (tangent method) algorithms and software.
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Textbooks, References and/or Other Materials:
1. http://www.matematiktutkusu.com/forum/matematik-ogretmenleri-dokumanlari/112-matematik-ogretiminde-modelleme-matematiksel-modelleme-nedir.html 2. http://www.bilkent.edu.tr/~kadiri/mat/mat.donem.odev/aykutaydin.matematiksekmodelleme.pdf 3. http://web.firat.edu.tr/kimmuh/eskiweb/kimya/model.htm 4. http://www.hakankör.com.tr/Algoritma.pdf 5. Genel Matematik. Editör Prof. Dr. Orban ÖZER 6. Prof. Dr. Ahmet A. KARADENİZ Yüksek Matematik. Cilt 1, 2. 4. Baskı, 1985. 7. Ders notları.
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Assesment
TERM LEARNING ACTIVITIES
NUMBER
PERCENT
Midterm Exam
1
40
Quiz
0
0
Homeworks, Performances
0
0
Final Exam
1
60
Total
2
100
Contribution of Term (Year) Learning Activities to Success Grade
40
Contribution of Final Exam to Success Grade
60
Total
100
Measurement and Evaluation Techniques Used in the Course
Techniques such as lecture, discussion, question-answer, 3E are used in the teaching of the course. Midterm and final exams are taken into consideration in the measurement and evaluation of the course.
Information
Results are determined with the letter grade determined by the student automation system.
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ECTS / WORK LOAD TABLE
Activites
NUMBER
TIME [Hour]
Total WorkLoad [Hour]
Theoretical
14
2
28
Practicals/Labs
0
0
0
Self Study and Preparation
10
3
30
Homeworks, Performances
0
5
20
Projects
0
0
0
Field Studies
0
0
0
Midtermexams
1
20
20
Others
0
0
0
Final Exams
1
20
20
Total WorkLoad
138
Total workload/ 30 hr
3,93
ECTS Credit of the Course
4
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CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
