Integrating Quantitative Methods into the Study of Democratisation

Integrating Quantitative Methods into the Study of Democratisation

Nicholas Lees, University of Liverpool

Quantitative evidence is central to the academic debate about the causes of democratisation. Without some familiarity with the quantitative evidence, many of the debates in this subfield of comparative politics are difficult to follow. Therefore, I wanted students on my second year democratisation module to get hands-on experience of working with data about patterns of democracy over the past few decades. My goal was for students to discover patterns for themselves and assess whether they were consistent with theories that they would encounter on the module. Incorporating a quantitative methods aspect into the module was therefore a strategy for increasing the students’ substantive understanding of the subject.

I designed the coursework so that students would have to think about how they would conceptualise democracy, how they could evaluate a theory of democratisation and how they could combine quantitative information from a dataset with an independently-researched qualitative case study. This was to ensure that the coursework assessed all parts of the taught component of the module and that students would get experience using the actual methods used in comparative politics.

Explain what you did

For the coursework component of the democratisation module (which takes place in semester 1 of the second year), students were tasked to complete a 2,250-word project using quantitative techniques to investigate the experience of democratisation of a single country. This project contributed 50% of the overall mark for the module. The project required them to select an operationalisation of democracy and a theory of democratisation, tying the project to specific weeks of the course when we discussed these issues. In the first part of the project, students had to generate cross-sectional statistics and discuss them in relation to their chosen country and theory. In the second part of the project, students had to supplement a historical account of their chosen country’s progress towards or away from democracy with longitudinal data.

The students were supported in writing the project by five one-hour lab sessions in which I taught them the basics of handling data in Microsoft Excel. We started with data navigation and moved on to writing simple formulas, calculating descriptive statistics and identifying correlations. In the later sessions we went through how to generate cross-tabulations and calculate Chi-squared statistics, and how to generate various graphs. 

What went well?

Some of the projects produced by students were very good pieces of work. The best projects used the techniques introduced in the lab sessions very effectively in conjunction with qualitative analysis and theoretical discussion. The majority of the students were able to use the dataset to generate relevant quantitative information and interpret it plausibly. Some of the students were able to draw claims and hypotheses from the literature and subject them to preliminary tests using simple techniques – indicating that these students had begun to acquire comparative politics research skills at a relatively early stage of their degrees.

It was especially encouraging to witness the increased confidence of students who were initially quite intimidated by the prospect of using quantitative data.

Challenges/what you would change/what went poorly

Some students found their initial encounter with the dataset quite intimidating. In addition, although almost all the students had used Excel in secondary school, some still had trouble reading information displayed in a spreadsheet. In future sessions, I plan to organise an additional lab at the beginning of the course to go through the absolute basics of reading tables and graphs.

Some students were nervous about the non-standard nature of the assessment and were unsure how to structure and present their projects. Not being able to visualise how the completed project would appear seemed to be a barrier for some students. I generated a mock-up project with lorem ipsum text (as used in publishing) to help them visualise what a completed project might look like. I will provide this mock-up early on in future sessions.

Conducting a Chi-squared test and interpreting results correctly was perhaps at the limit of what students could accomplish, given time constraints and the fact that few students on the module had taken any other course with a quantitative methods component. Although many students successfully completed this part of the assignment, many found the explanation of the test very challenging and counterintuitive. In the next session of the course, I plan to make the Chi-square test and similar analytical techniques extension activities – non-compulsory activities worth additional marks.

Perhaps surprisingly, the qualitative-historical discussions in student projects were often weaker than the quantitative parts of the analysis. It may be that students prioritised the quantitative sections, or that students were less familiar with writing case studies than anticipated.