Monthly Subscription Starting at AED 99 + VAT
- Level Foundation
- المدة 27 ساعات hours
- الطبع بواسطة Erasmus University Rotterdam
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Offered by
عن
Welcome to this massive open online course (MOOC) about Qualitative Comparative Analysis (QCA). Please read the points below before you start the course. This will help you prepare well for the course and attend it properly. It will also help you determine if the course offers the knowledge and skills you are looking for. What can you do with QCA? • QCA is a comparative method that is mainly used in the social sciences for the assessment of cause-effect relations (i.e. causation). • QCA is relevant for researchers who normally work with qualitative methods and are looking for a more systematic way of comparing and assessing cases. • QCA is also useful for quantitative researchers who like to assess alternative (more complex) aspects of causation, such as how factors work together in producing an effect. • QCA can be used for the analysis of cases on all levels: macro (e.g. countries), meso (e.g. organizations) and micro (e.g. individuals). • QCA is mostly used for research of small- and medium-sized samples and populations (10-100 cases), but it can also be used for larger groups. Ideally, the number of cases is at least 10. QCA cannot be used if you are doing an in-depth study of one case. What will you learn in this course? • The course is designed for people who have no or little experience with QCA. • After the course you will understand the methodological foundations of QCA. • After the course you will know how to conduct a basic QCA study by yourself. How is this course organized? • The MOOC takes five weeks. The specific learning objectives and activities per week are mentioned in appendix A of the course guide. Please find the course guide under Resources in the main menu. • The learning objectives with regard to understanding the foundations of QCA and practically conducting a QCA study are pursued throughout the course. However, week 1 focuses more on the general analytic foundations, and weeks 2 to 5 are more about the practical aspects of a QCA study. • The activities of the course include watching the videos, consulting supplementary material where necessary, and doing assignments. The activities should be done in that order: first watch the videos; then consult supplementary material (if desired) for more details and examples; then do the assignments. • There are 10 assignments. Appendix A in the course guide states the estimated time needed to make the assignments and how the assignments are graded. Only assignments 1 to 6 and 8 are mandatory. These 7 mandatory assignments must be completed successfully to pass the course. • Making the assignments successfully is one condition for receiving a course certificate. Further information about receiving a course certificate can be found here: https://learner.coursera.help/hc/en-us/articles/209819053-Get-a-Course-Certificate About the supplementary material • The course can be followed by watching the videos. It is not absolutely necessary yet recommended to study the supplementary reading material (as mentioned in the course guide) for further details and examples. Further, because some of the covered topics are quite technical (particularly topics in weeks 3 and 4 of the course), we provide several worked examples that supplement the videos by offering more specific illustrations and explanation. These worked examples can be found under Resources in the main menu. • Note that the supplementary readings are mostly not freely available. Books have to be bought or might be available in a university library; journal publications have to be ordered online or are accessible via a university license. • The textbook by Schneider and Wagemann (2012) functions as the primary reference for further information on the topics that are covered in the MOOC. Appendix A in the course guide mentions which chapters in that book can be consulted for which week of the course. • The publication by Schneider and Wagemann (2012) is comprehensive and detailed, and covers almost all topics discussed in the MOOC. However, for further study, appendix A in the course guide also mentions some additional supplementary literature. • Please find the full list of references for all citations (mentioned in this course guide, in the MOOC, and in the assignments) in appendix B of the course guide.الوحدات
First read the course guide
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1
Readings
1
Readings
- Course guide
Lectures
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4
Videos
4
Videos
- 1.1. Objectives and agenda of the course
- 1.2. QCA vs other approaches
- 1.3. Set theory and complex causality
- 1.4. The QCA research field
Not mandatory, but recommended: supplementary readings
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1
Readings
1
Readings
- Readings in course guide
Lectures
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4
Videos
4
Videos
- 2.1. Orientation and focal points
- 2.2. Cases, outcomes and conditions
- 2.3. Crisp vs fuzzy sets
- 2.4. Calibration with quantitative, qualitative and secondary data
Not mandatory, but recommended: supplementary readings
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1
Readings
1
Readings
- Readings in course guide
Assignments about weeks 1 and 2
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1
PeerReview
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1
Assignment
1
Assignment
- Assignment 1. Main terms and background
1
Peer Review
- Assignment 2. Calibration
Lectures
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3
Videos
3
Videos
- 3.1. The purpose and construction of a truth table
- 3.2. Raw consistency
- 3.3. Resolving contradictory configurations
Not mandatory, but recommended: supplementary readings
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1
Readings
1
Readings
- Readings in course guide
Assignments for week 3
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2
Assignment
2
Assignment
- Assignment 3. Make a truth table for crisp data
- Assignment 4. Make a truth table for fuzzy data
Lectures
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3
Videos
3
Videos
- 4.1. What is logical minimization?
- 4.2. The minimal formula
- 4.3. Parameters of fit
Not mandatory, but recommended: supplementary readings
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1
Readings
1
Readings
- Readings in course guide
Assignment about week 4
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1
Assignment
1
Assignment
- Assignment 5. Minimize a truth table
Lectures
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3
Videos
3
Videos
- 5.1. Using FsQCA 3, part 1
- 5.2. Using FsQCA 3, part 2
- 5.3. Do's and don'ts for the write-up
Not mandatory, but recommended: supplementary readings
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1
Readings
1
Readings
- Readings in course guide
Assignments about weeks 4 and 5
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1
Discussion
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2
Assignment
2
Assignment
- Assignment 6. Using the program fsQCA for the analysis of crisp data (PLUS bonus assignment 7; is not mandatory)
- Assignment 8. Using the program fsQCA for the analysis of fuzzy data (PLUS bonus assignment 9; is not mandatory)
1
Discussions
- Assignment 10. Critical reflection (bonus assignment; is not mandatory)
Auto Summary
Discover the intricacies of Qualitative Comparative Analysis (QCA) with this comprehensive MOOC designed for both novice and experienced researchers in the social sciences. This course, brought to you by Coursera, delves into the methodology and practical application of QCA, a powerful tool for assessing cause-effect relationships across various levels, from individual cases to countries. **Course Highlights:** - **Focus:** Understand and apply QCA, a comparative method essential for both qualitative and quantitative researchers. - **Content:** Gain insights into the methodological foundations of QCA and learn to conduct your own QCA study through engaging videos, supplementary readings, and practical assignments. - **Duration:** The course spans five weeks, meticulously structured to transition from theoretical foundations to hands-on QCA applications. - **Assignments:** Complete 7 mandatory assignments out of 10 to earn a course certificate, ensuring a thorough grasp of the material. **Instructor and Resources:** - **Instructor:** Expert guidance provided by Coursera's seasoned educators. - **Supplementary Material:** While the course videos are the core learning resource, detailed readings from Schneider and Wagemann (2012) and additional literature enhance understanding, especially for more technical topics. **Subscription Options:** - **Starter:** Access essential course materials and assignments. - **Professional:** Unlock advanced features and additional resources. **Target Audience:** - **Researchers:** Ideal for social scientists seeking systematic comparative methods. - **Academics and Practitioners:** Suitable for those dealing with small to medium-sized samples, aiming to explore complex causative factors. Embark on this foundational journey to master QCA and elevate your research capabilities with Coursera's expertly curated course.
Fadi Hirzalla