ECON 1112 - Research Methods in Social Sciences

Basic Information

Course Code:

ECON 1112

Course Name:

Research Methods in Social Sciences

Language of Instruction:

English

Course Type:

Class

Course Level:

Bachelor

ECTS:

4.00

Instructor:

Dr. Öğr. Üyesi FIRAT YILMAZ

Course Objectives

The primary objective of this course is to comprehensively teach students the processes of designing, conducting, and reporting scientific research in the social sciences. The course aims to enhance students' critical thinking skills by teaching them how to formulate a research question, select the appropriate methodology, and present findings within the framework of academic ethics. Students will master basic paradigms such as positivism, interpretivism, and critical theory, and gain expertise in qualitative and quantitative data collection techniques (surveys, interviews, content analysis, etc.).

Course Content

The course begins with the philosophy of science, the nature of the scientific method, and ethical principles. Subsequent weeks cover literature review strategies, definition of the research problem, hypothesis development, and operationalization of concepts. Within the scope of quantitative methods, survey design, sampling techniques, and validity-reliability analyses are detailed; qualitative methods cover in-depth interviews, focus group studies, and ethnographic observations. The final part of the course concludes with data analysis and academic writing rules (APA format).

Prerequisites / Corequisites

None

Course Books / Materials / Recommended Resources

Neuman, W. L. (2014). Social Research Methods: Qualitative and Quantitative Approaches. Pearson.Babbie, E. R. (2020). The Practice of Social Research. Cengage Learning.Gerring, J. (2012). Social Science Methodology: A Unified Framework. Cambridge University Press.

Learning Outcomes

Code	Description
LO1	Defines and formulates clear research problems and research questions.
LO2	Conducts literature reviews using academic sources and identifies methodological biases.
LO3	Distinguishes among qualitative, quantitative, and mixed research methods and carries out coding processes.
LO4	Designs basic research studies, develops sampling strategies, and analyzes advanced quantitative models.
LO5	Understands ethical considerations in research, plagiarism rules, and institutional approval processes.

Weekly Course Content

Week	Content
1	Scientific Method and Social Sciences
2	Research Topic and Problem Definition
3	Research Ethics and Academic Integrity
4	Literature Review Techniques
5	Variables and Hypothesis Formulation
6	Research Designs (Descriptive, Experimental)
7	Qualitative Research Methods
8	Midterm Exam
9	Quantitative Research Methods and Surveys
10	Sampling Theory and Techniques
11	Data Preparation and Descriptive Analysis
12	Content Analysis and Interview Techniques
13	Interpretation of Findings and Discussion
14	Academic Report Writing and Presentation
15	Review

Workload Calculation

Activity	Count	Duration (Hours)	Total
Attendance	15	3.00	45.00
Pre-Class Individual Study	15	4.00	60.00
Midterm Exam/Preparation	1	15.00	15.00
Final Exam/Preparation	1	30.00	30.00
Total Workload (Hours)			150
ECTS Credit (Workload / 25)			5

Assessment

#	Assessment Type	Contribution (%)
1	Midterm Exam	%40
2	Final Exam	%60
TOTAL		%100

PO - LO Matrix

PO \ LO	LO1	LO2	LO3	LO4	LO5
PO-1
PO-2
PO-3
PO-4
PO-5
PO-6
PO-7
PO-8
PO-9
PO-10
PO-11
PO-12

1

Low Contribution

2

Medium Contribution

3

High Contribution

Teaching and Learning Methods

#	Method Name	Description	Tools
1	Lecture (expository teaching), interactive discussion	Listening and taking notes.	Standard classroom technologies, multimedia tools (projector, computer, digital presentations)

Academic Integrity and Artificial Intelligence

Students are expected to comply with the principles of academic integrity in all examinations, coursework, and other academic activities. Information, data, tables, figures, and ideas obtained from external sources must be properly acknowledged. Plagiarism, manipulation of data or results, completing work on behalf of another student, and unauthorized collaboration are considered violations of academic integrity. Artificial intelligence tools may be used, when permitted by the course instructor, to clarify concepts, explore current labor market issues, or support the interpretation of data. Students are responsible for verifying the accuracy of information and interpretations generated by AI. AI tools may not replace students' own economic analysis, critical evaluation, or academic responsibility.

Sustainable Development Goals