TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| INDUSTRIAL ENGINEERING PR. | |
| Code | ENM107 |
| Name | Computer Programming I |
| Term | 2021-2022 Academic Year |
| Semester | 1. Semester |
| Duration (T+A) | 1-1 (T-A) (17 Week) |
| ECTS | 2 ECTS |
| National Credit | 1.5 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Uzaktan Öğretim |
| Catalog Information Coordinator | Öğr. Gör. Dr. İRFAN MACİT |
| Course Instructor |
Öğr. Gör. Dr. İRFAN MACİT
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
In Computer Programming course, Mathematics Department aims to acquire the ability of basic mathematical processes that students meet with programming language.
Course Content
In the course, laboratory applications will be carried out in order to write computer programs and gain the ability to develop these programs and algorithms. The theoretical part of the course will be reinforced by practicing with laboratory applications.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | They learn basic concepts of computer programming, responsibility and professional ethics. |
| LO02 | They learn the basic concepts of algorithms. |
| LO03 | They learn algorithm development processes. |
| LO04 | They learn the use of algorithms related tools. |
| LO05 | They ave knowledge about designing related processes in Algorithm. |
| LO06 | They can develop algorithms individually. |
| LO07 | They learn basic concepts of computer programming. |
| LO08 | They learn data structures. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Adequate knowledge in mathematics, science and related engineering discipline; ability to use theoretical and practical knowledge in these areas in complex engineering problems. | 5 |
| PLO02 | - | An ability to identify, formulate, and solve complex industrial engineering problems; the ability to select and apply appropriate analysis and modeling methods for this purpose. | 5 |
| PLO03 | - | An ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; the ability to apply modern design methods for this purpose. | 5 |
| PLO04 | - | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications; ability to use information technologies effectively. | 5 |
| PLO05 | - | Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or discipline-specific research topics. | 5 |
| PLO06 | - | Ability to work effectively in disciplinary and multidisciplinary teams; self-study skills. | 4 |
| PLO07 | - | Ability to communicate effectively in Turkish presentation and in writing; knowledge of at least one foreign language; Ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give clear and understandable instruction and receiving skills. | 2 |
| PLO08 | - | Awareness of the necessity of lifelong learning; the ability to access information, follow developments in science and technology, and constantly renew oneself. | 4 |
| PLO09 | - | To act in accordance with ethical principles, professional and ethical responsibility awareness; information about standards used in engineering applications. | 4 |
| PLO10 | - | Information on business practices such as project management, risk management and change management; awareness about entrepreneurship and innovation; information on sustainable development. | 1 |
| PLO11 | - | Information about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems reflected in the engineering field of the age; awareness of the legal consequences of engineering solutions. | 1 |
| PLO12 | - | Ability to make use of the power of effective communication in professional life, to interpret the developments correctly and to make decisions. | 5 |
| PLO13 | - | Ability to design, develop, implement and improve integrated systems including machinery, time, information and money. | 5 |
| PLO14 | - | Ability to design, develop, implement and improve complex product, process, business, system design by applying modern design methods under realistic conditions and constraints such as cost, environment, sustainability, productivity, ethics, health, safety and political issues. | 1 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic Concepts and introduction. | None | |
| 2 | Introduction to Algorithm. | Definition research. | |
| 3 | Introduction to algorithm analysis. | Definition research. | |
| 4 | Algorithm analysis cases | Research in library | |
| 5 | Algorithm development processes and analysis results. | Research in library | |
| 6 | Clarification of analysis results by means of algorithm development tools. | Research in library | |
| 7 | Algorithm design and analysis with algorithms development tools. | Research in library | |
| 8 | Mid-Term Exam | none | |
| 9 | Basic concepts in programming. | Prepairing laboratory examination. | |
| 10 | Programming data structures. | Prepairing laboratory examination. | |
| 11 | Data entrering in the program. | Prepairing laboratory examination. | |
| 12 | Data outputs in programming. | Prepairing laboratory examination. | |
| 13 | Setup and analysis of conditioanls in programming. | Prepairing laboratory examination. | |
| 14 | Analysis of the setting up of conditionals in computer programming. | Prepairing laboratory examination. | |
| 15 | Functional analysis in programming. | Prepairing laboratory examination. | |
| 16 | Term Exams | none | |
| 17 | Term Exams | none |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 12 | 1 | 12 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 4 | 4 |
| Final Exam | 1 | 6 | 6 |
| Total Workload (Hour) | 50 | ||
| Total Workload / 25 (h) | 2,00 | ||
| ECTS | 2 ECTS | ||