CODING, SOCIAL DESIGN AND ANALYSIS

SOC337

Course Code: SOC337
Semester: -
Theory+Practice: 3 + 0
ECTS: 5

Course Type

Elective Course

Course Level

Bachelor's Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Discuss the social dimensions of technological developments.
Gain entry-level coding skills.
Develop research design and analysis skills.
Gain the ability to analyze and simulate social issues.
Gain knowledge about the study subjects of Computational Social Sciences.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

No.

Course Description

The developments of technology have stimulated the tools of making research, gathering knowledge and making analysis. In recent years, coding and programming have been used often in social researches. By dint of them, social scientists can gather large amount of data which increase the ability to make deeper analysis. In this course, students learn coding at introductory levels. Besides, they will design social problems and make simulations. So, they can make proper policy analysis.

Course Contents

WEEK	TOPICS
1^st Week	1st Week Technology and social life: Historical view.Creating working groups.
2^nd Week	2nd Week Work Groups 1: Social Problem Mapping
3^rd Week	3rd Week Work Groups 2: Developing recommendations
4^th Week	4th Week Coding: Basic languages and libraries
5^th Week	5th Week Coding: Low code/ no code tools- IFTTT
6^th Week	6th Week Coding: Web Scraping and Data cleaning
7^th Week	7th Week Coding: Tools for data analysis
8^th Week	8th Week Coding: Data visualisation
9^th Week	9th Week Design Sprint: Prototyping
10^th Week	10thWeek Complex adaptive systems
11^th Week	11thWeek Socio- technic systems
12^th Week	12thWeek Implementation of Case studies: Climate problems
13^th Week	13thWeek Implementation of Case studies: Virtual worlds
14^th Week	14thWeek Presentations

Recommended or Required Reading

Marres, N. (2017) Digital Sociology: the reinvention of social research, Cambridge: Polity.
Gillespie, T. & K. Foot et al. (2013) Media Technologies: Materiality, Technology, Society, Cambridge: MIT Press
Ruppert, E., Law, J., & Savage, M. (2013). Reassembling social science methods: The challenge of digital devices. Theory, culture & society, 30(4), 22-46.
Lupton, Deborah (2013) Digital Sociology. London.

Planned Learning Activities and Teaching Methods

Lecture
Questions/Answers
Practice
Presentation

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	20
Practice	1	50
Total(%)		70
Contribution of In-term Studies to Overall Grade(%)		70
Contribution of Final Examination to Overall Grade(%)		30
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam
Preparation for Quiz
Individual or group work	1	28	28
Preparation for Final exam
Course hours	14	3	42
Preparation for Midterm exam
Laboratory (including preparation)	1	30	30
Final exam
Homework	2	25	50
Total Work Load			150
Total Work Load / 30 (h)			5
ECTS Credit of the Course			5

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5
K1
K2
K3
K4
K5	X	X	X	X	X
K6
K7
K8
K9
K10
K11	X	X	X	X	X
K12