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Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
DATA ANALYSIS-Spring Semester2+236
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseTurkish
Course LevelSecond Cycle (Master's Degree)
Course TypeElective
Course CoordinatorAssoc.Prof. İhsan EKEN
Name of Lecturer(s)Prof.Dr. Gökhan SİLAHTAROĞLU
Assistant(s)
AimThe aim of Data Analyses course is to comprehend the basic data of this field, data collection, data collection, data analysis, data analysis, practical and theoretical understanding of data visualization and open data relationship by using right to information.
Course ContentThis course contains; mid term exama,Definition / History of Data Journalism, Finding Story with Data - How-To,Data Scraping,Introduction to Data Visualization Tools,Basic Statistics and Working Practices in Excel,Request for Information, Digital Content Verification,Open Data Ethics,Social Media Data Analysis / Usage,Open Data Machine Readability,Data Research, Techniques,Group Project Homework,Solo Project,Project presentations.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
Defines the concepts of data journalism10, 13, 16, 17, 6, 8, 9A
Applies Open Data Creation Practice10, 13, 16, 17, 18, 6, 8A, F, H
Creates digital content10, 13, 16, 6, 8, 9A, E, H
Performs the basics of design and effective visual communication.10, 13, 14, 16, 17, 18, 6, 9A, E, F, H
Analyses the Freedom of Information and its Relationship with Open Data.10, 13, 14, 16, 6, 8, 9A, E, F
Teaching Methods:10: Discussion Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 17: Experimental Technique, 18: Micro Teaching Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task, H: Performance Task

Course Outline

OrderSubjectsPreliminary Work
0mid term exama
1Definition / History of Data Journalism
2 Finding Story with Data - How-To
3Data Scraping
4Introduction to Data Visualization Tools
5Basic Statistics and Working Practices in Excel
6Request for Information, Digital Content Verification
7Open Data Ethics
9Social Media Data Analysis / Usage
10Open Data Machine Readability
11Data Research, Techniques
12Group Project Homework
13Solo Project
14Project presentations
Resources
(1)Kalsın, Berrin. Tüm Boyutlarıyla İnternet Haberciliği, Gece Kitaplığı, 2017. (2)Open Data Institute / http://theodi.org/ (3)Getting Started with Data Journalism /Writing data stories in any size newsroom /by Claire Miller/https://leanpub.com/datajournalism (4)Data Journalism HandBook /Edited by Jonathan Gray,Lilliona Bounegry and Lucy Chambers /http://datajournalismhandbook.org/ (5)Data Journalism Heist /by Paul Bradshawhttps://leanpub.com/DataJournalismHeist Data Journalism: Mapping the Future

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Has advanced theoretical and practical knowledge in the fields of media history, news writing techniques, news types, applied journalism.
2
Knows the process of content production according to the characteristics of different communication environments.
3
To have knowledge about theories, methods, strategies and techniques related to the field.
4
Aware of the impact of media on people and society's thoughts, behaviors and values.
5
Use theoretical and practical knowledge specific to the field.
6
Develop critical thinking, analysis and synthesis skills.
7
Follows and uses new methods and technologies in the field.
8
Develops the ability to produce an original media content with the knowledge acquired.
9
Evaluates the visual and audio data and literary texts critically.
10
Identifies problems in the field, collects and analyzes data to solve these problems; comments and suggestions for solutions.
11
Acts in accordance with democracy, human rights, social, scientific and professional ethical values ​​in the content production process.
12
Takes responsibility in individual or group works related to the field and fulfills the task taken or executes independently.
13
Plans and manages activities for professional development as an individual and a team member.
14
Monitors at least one foreign language at the level of European Language Portfolio B2 General Level.
15
Transfers written solutions orally and verbally.
16
Evaluates his / her ideas and solutions for problems related to his / her field with his / her stakeholders by supporting them with quantitative and qualitative data.
17
Uses Turkish language fluently and accurately in scientific and professional works.
18
Knowledgeable about occupational health and safety and can use this information when necessary.
19
Sensitive to the environment, the universality of social rights and the protection of cultural values.

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 50
Rate of Final Exam to Success 50
Total 100
ECTS / Workload Table
ActivitiesNumber ofDuration(Hour)Total Workload(Hour)
Course Hours14342
Guided Problem Solving14228
Resolution of Homework Problems and Submission as a Report14228
Term Project000
Presentation of Project / Seminar14228
Quiz000
Midterm Exam14114
General Exam14228
Performance Task, Maintenance Plan000
Total Workload(Hour)168
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(168/30)6
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
DATA ANALYSIS-Spring Semester2+236
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseTurkish
Course LevelSecond Cycle (Master's Degree)
Course TypeElective
Course CoordinatorAssoc.Prof. İhsan EKEN
Name of Lecturer(s)Prof.Dr. Gökhan SİLAHTAROĞLU
Assistant(s)
AimThe aim of Data Analyses course is to comprehend the basic data of this field, data collection, data collection, data analysis, data analysis, practical and theoretical understanding of data visualization and open data relationship by using right to information.
Course ContentThis course contains; mid term exama,Definition / History of Data Journalism, Finding Story with Data - How-To,Data Scraping,Introduction to Data Visualization Tools,Basic Statistics and Working Practices in Excel,Request for Information, Digital Content Verification,Open Data Ethics,Social Media Data Analysis / Usage,Open Data Machine Readability,Data Research, Techniques,Group Project Homework,Solo Project,Project presentations.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
Defines the concepts of data journalism10, 13, 16, 17, 6, 8, 9A
Applies Open Data Creation Practice10, 13, 16, 17, 18, 6, 8A, F, H
Creates digital content10, 13, 16, 6, 8, 9A, E, H
Performs the basics of design and effective visual communication.10, 13, 14, 16, 17, 18, 6, 9A, E, F, H
Analyses the Freedom of Information and its Relationship with Open Data.10, 13, 14, 16, 6, 8, 9A, E, F
Teaching Methods:10: Discussion Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 17: Experimental Technique, 18: Micro Teaching Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task, H: Performance Task

Course Outline

OrderSubjectsPreliminary Work
0mid term exama
1Definition / History of Data Journalism
2 Finding Story with Data - How-To
3Data Scraping
4Introduction to Data Visualization Tools
5Basic Statistics and Working Practices in Excel
6Request for Information, Digital Content Verification
7Open Data Ethics
9Social Media Data Analysis / Usage
10Open Data Machine Readability
11Data Research, Techniques
12Group Project Homework
13Solo Project
14Project presentations
Resources
(1)Kalsın, Berrin. Tüm Boyutlarıyla İnternet Haberciliği, Gece Kitaplığı, 2017. (2)Open Data Institute / http://theodi.org/ (3)Getting Started with Data Journalism /Writing data stories in any size newsroom /by Claire Miller/https://leanpub.com/datajournalism (4)Data Journalism HandBook /Edited by Jonathan Gray,Lilliona Bounegry and Lucy Chambers /http://datajournalismhandbook.org/ (5)Data Journalism Heist /by Paul Bradshawhttps://leanpub.com/DataJournalismHeist Data Journalism: Mapping the Future

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Has advanced theoretical and practical knowledge in the fields of media history, news writing techniques, news types, applied journalism.
2
Knows the process of content production according to the characteristics of different communication environments.
3
To have knowledge about theories, methods, strategies and techniques related to the field.
4
Aware of the impact of media on people and society's thoughts, behaviors and values.
5
Use theoretical and practical knowledge specific to the field.
6
Develop critical thinking, analysis and synthesis skills.
7
Follows and uses new methods and technologies in the field.
8
Develops the ability to produce an original media content with the knowledge acquired.
9
Evaluates the visual and audio data and literary texts critically.
10
Identifies problems in the field, collects and analyzes data to solve these problems; comments and suggestions for solutions.
11
Acts in accordance with democracy, human rights, social, scientific and professional ethical values ​​in the content production process.
12
Takes responsibility in individual or group works related to the field and fulfills the task taken or executes independently.
13
Plans and manages activities for professional development as an individual and a team member.
14
Monitors at least one foreign language at the level of European Language Portfolio B2 General Level.
15
Transfers written solutions orally and verbally.
16
Evaluates his / her ideas and solutions for problems related to his / her field with his / her stakeholders by supporting them with quantitative and qualitative data.
17
Uses Turkish language fluently and accurately in scientific and professional works.
18
Knowledgeable about occupational health and safety and can use this information when necessary.
19
Sensitive to the environment, the universality of social rights and the protection of cultural values.

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 50
Rate of Final Exam to Success 50
Total 100

Numerical Data

Student Success

Ekleme Tarihi: 29/11/2023 - 14:26Son Güncelleme Tarihi: 29/11/2023 - 14:26