Chevron Left
Retour à Qualitative Comparative Analysis (QCA)

Avis et commentaires pour d'étudiants pour Qualitative Comparative Analysis (QCA) par Université Érasme de Rotterdam

4.8
étoiles
72 évaluations
24 avis

À propos du cours

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....

Meilleurs avis

GS
31 déc. 2020

This course was a very good introduction. Professor Hirzalla explains QCA very clearly, slowly, and thoroughly. I wish there was a second part to this course.

EC
1 janv. 2021

Very well organized content. Great supporting material! Suitable for complete beginners in QCA. Challenging but interesting assignments.

Filtrer par :

1 - 24 sur 24 Avis pour Qualitative Comparative Analysis (QCA)

par Kiri D

10 mai 2020

Excellent course and perfectly pitched at the right level (not to easy, not too hard)

par Aritra H

20 juin 2020

It is a fantastic course on a very intriguing and novel approach to qualitative research. The assignments were super helpful and the references were in-depth and carefully chosen. I specially like Dr. Hirzalla's approach in encouraging learners to learn by reading and hands on practice rather than delivering lectures only through A/V mode. That way, as a learner, I could internalize the concepts and techniques in a more holistic way. I thank Dr. Hirzalla and the entire team of Erasmus University for conceptualizing and delivering this course. Cheers!

par Kellan N

3 déc. 2019

I love how the course explains the truth table construction: very simple and straight forward! Also important, the exercises are helpful to get hands-on experiences (manually constructing the truth table). Thank you very much!

par Geoffrey S

1 janv. 2021

This course was a very good introduction. Professor Hirzalla explains QCA very clearly, slowly, and thoroughly. I wish there was a second part to this course.

par Evelyn C

2 janv. 2021

Very well organized content. Great supporting material! Suitable for complete beginners in QCA. Challenging but interesting assignments.

par Rosa M V V

11 déc. 2020

Excelente curso, explica la teoría necesaria para entender el QCA, ejemplos sobre uso del mismo y aplicación en ejercicios prácticos.

par Stephan M

25 nov. 2020

Fantastic course. Very engaging. Great videos. Easy to follow. Exercises are not too easy, not too hard. Can definitely recommend it!

par DEVESH B

23 mai 2020

Very good course but more exercises using software should be incorporated. Software functions should be discussed in detail.

par Mirza F T

15 janv. 2021

Very comprehensive learning process and clear instructions. Examples provided are also very helpful for the whole course.

par Volodymyr K

30 avr. 2020

Very understanding and very easily explained hard stuff. Very great word!!! thanks!!!

par Nimra B

13 juil. 2020

Very help to get basic understanding of all main steps involved in data analysis.

par Joseph L

18 août 2020

An excellent course. The instructor was very clear in his explanation.

par Monu S

23 juin 2020

Very interesting well conducted course Thanks to Dr Fadi Hirzala

par Mikkel M

20 oct. 2020

Useful instructions and very detailed assignments and answers.

par Manuel A S S

12 janv. 2020

Very nice

par Aswini K B

4 juil. 2020

Amazing

par Jolien G

26 juil. 2019

Nice introductory course. Good pacing, highlights are being discussed, easy to follow.

par Zhu Z

15 juil. 2019

Very brief but clear introduction of QCA. Highligh recommended for beginners.

par Fernando R R

15 sept. 2020

Great!

Erasmus could add one week for expose mvQCA and Tosmana.

par Vareska v d V

20 nov. 2020

Great to learn something new. I did think the course was a bit light - I now know what I need to do to perform the analyses, but I am not always sure about the background of a certain procedure. The peer-graded assignment didn't work well for me - no one has reviewed it..

par Maud v M

29 avr. 2020

Great course. The videos are short but insightful. We receive access to an extensive list of readings and resources. Finally, I enjoyed the assignments very much. Thank you!

par Júlia P N

18 juil. 2020

The course is great for beginners. I would like it to be a little more complete, exploring more complex topics, but the complementary readings filled this gap.

par Anel O

15 avr. 2020

great for basic notions and simple level exercise. Good recommended literature