Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
COMPUTER I KİM0103 1. Semester 2 + 2 3.0 3.0

Prerequisites None

Language of Instruction Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Mode of delivery
Course Coordinator
Instructors Yahya DEMİRCAN
Assistants
Goals To give information on the basic computer concepts, MS Excel applications in Chemistry (Charts, regression, correlation analysis, ANOVA, logical operations, etc.), algorithm and flow chart, basic concepts of programming, BASIC as a programing language and algorithm applications that be useable in the upper grades.
Course Content Basic computer concepts, ecell, algorithm, BASIC programming, develop algorithm and application of developed algorithms with BASIC programming.
Learning Outcomes 1) Determines the basic components of computer and working principle.
2) Determines the basic concepts of MS Excel.
3) Associate the regression, correlation, ANOVA analysis with chemical problems
4) Determines the basic concepts of computer programming.
5) Determines the using of algorithm development and flow chart in chemical problems
6) Determines the BASIC programming language and using BASIC in chemistry problems

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Basic concepts of computer: Computer peripherals, software and hardware Lecture; Question Answer
Brainstorming
Problem Based Learning 		Homework
2. Week Basic concepts of computer: Computer peripherals, software and hardware Lecture; Question Answer; Discussion
Brainstorming
Problem Based Learning 		Homework
3. Week MS Excel: Basic concepts of Excel worksheet and functions. Using charts and calculation of activation energy of a chemical reaction by using Arrhenius equaiton and Excel Lecture; Question Answer; Discussion
Brainstorming
Problem Based Learning 		Homework
4. Week Logical functions in MS Excel (And, Or, If and etc.) and programming in MS Excel Lecture; Question Answer
Brainstorming
Problem Based Learning 		Homework
5. Week Logical functions in MS Excel (And, Or, If and etc.) and programming in MS Excel Lecture; Question Answer; Problem Solving
Brainstorming
Problem Based Learning 		Homework
6. Week Variance and analysis of variance in MS Excel. Introduction to statistical experimental design (Taguchi method) Lecture; Question Answer; Problem Solving; Discussion
Brainstorming
 Homework
7. Week Variance and analysis of variance in MS Excel. Introduction to statistical experimental design (Taguchi method) Lecture
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)
8. Week Algorithm and flow chart. Symbols in flow chart Lecture; Question Answer; Problem Solving; Discussion; Case Study
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)
9. Week Algorithm development for chemistry problems Lecture; Question Answer; Problem Solving
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)
10. Week Algorithm development for chemistry problems Lecture; Question Answer
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)
11. Week Introduction to programming and information about computer programming languages. Basic applications of BASIC language Lecture; Question Answer
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)
12. Week Introduction to programming and information about computer programming languages. Basic applications of BASIC language Lecture; Question Answer; Discussion
Brainstorming
Problem Based Learning 		Homework
13. Week Introduction to programming and information about computer programming languages. Basic applications of BASIC language Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework Presentation (Including Preparation Time)
14. Week Algorithm development and solutions in BASIC languages of chemical problems Lecture; Question Answer; Problem Solving
Brainstorming
Problem Based Learning 		Homework Presentation (Including Preparation Time)

Sources Used in This Course
Recommended Sources
Skoog, D. A., West, D. M., Holler, F. J., Crouch, S. R., Kılıç, E., & Yılmaz, H. (2009). Analitik kimya: temel ilkeler. Bilim Yayıncılık.
Winston, W. (2016). Microsoft Excel data analysis and business modeling. Microsoft press.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3DK4DK5DK6
PY15000000
PY25000000
PY35000000
PY45000000
PY55000000
PY115444444
PY175444444
PY195444444

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 4
Work Hour outside Classroom (Preparation, strengthening) 14 2
Midterm Exam 1 1
Time to prepare for Midterm Exam 1 4
Final Exam 1 1
Time to prepare for Final Exam 1 4
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload