| Course Type | Elective Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 6 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Reviews literature on the methodological issues of qualitative research and the technical aspects of various approaches to qualitative analysis.
- Conducts, evaluates, selects and applies the appropriate data from various software programs used in qualitative analysis.
- Forms the qualitative research method part of his/her research/study according to the framework used in scientific meetings.
- Matches the appropriate data collection techniques with the right study area and participant profile.
- Review articles related to the subject, compares the trends over the years and analyzes the contents of current issues.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | The course will provide students with an understanding of the role of qualitative research in the social sciences; knowledge and experience in the use of qualitative methods; an appreciation of their limitations and the social, theoretical and political context of their use. It will also include qualitative data analysis, and writing and presenting qualitative research. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Course Overview |
|
2nd Week |
Epistemologies & Study Design |
|
3rd Week |
Introduction to Coding |
|
4th Week |
Grounded Theory & Inductive Coding |
|
5th Week |
Conceptual Framing & Deductive Coding |
|
6th Week |
Moving Beyond Coding: Matrices & Network Displays |
|
7th Week |
Trustworthiness |
|
8th Week |
Midterm |
|
9th Week |
Moving Beyond Coding |
|
10th Week |
Drawing and Verifying Inferences & Conclusions |
|
11th Week |
Visualizing Qualitative Data |
|
12th Week |
Writing about Qualitative Data: Transparent Path of Inference |
|
13th Week |
Writing about Qualitative Data: Representations of Data |
|
14th Week |
Evaluating Qualitative research |
|
15th Week |
General Evaluation |
|
| Recommended or Required Reading | Miles, M. B., Huberman, A. M. & Saldana, J. (2019). Qualitative data analysis: A methods sourcebook, 4th Edition. Thousand Oaks, CA: Sage. |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Practice
- Project
- Other
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Practice |
2 |
10 |
| Project |
1 |
30 |
| 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 |
1 |
1 |
1 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
4 |
56 |
| Preparation for Final exam |
1 |
30 |
30 |
| Course hours |
15 |
3 |
45 |
| Preparation for Midterm exam |
1 |
20 |
20 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
1 |
1 |
| Homework |
|
|
|
| Project |
1 |
15 |
15 |
| Performance Practice |
2 |
6 |
12 |
| Total Work Load | 180 |
| Total Work Load / 30 (h) | 6 |
| ECTS Credit of the Course | 6 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
