Teach research methodology using these low-prep exercises

There are several concepts that are essential to students’ understanding of research methodology. Since teachers often find it challenging to present and discuss these in an accessible and powerful way, I will use this resource to share some of the low-prep strategies I have been using in my compulsory undergraduate political science classes.

Research ethics

This involves introducing students to three very classic cases relevant to research ethics:

• The Milgram Shock Experiment
• The Stanford Prison Experiment 
• Little Albert Experiment. 

First, I present the brief contextual background for the cases before prompting students to reflect on the ethical dilemmas presented and their associated implications for research practices. Meanwhile, I invite students to suggest some of the alternative ways for conducting the above experiments ethically. The aim is that these contextualised examples allow students to understand the abstract principles behind them.

Conceptualisation, operationalisation and measurement of variables

I invite students to come up with some questions to ascertain someone’s height without using the traditional quantitative method (asking for their height). So, if height is not measured in the usual way and students still need to find out how “tall” someone is, they need to use other questions to get their answers. For example, they may structure their question as follows:

Do these statements apply to you?

• I find it challenging trying to find clothes that are a perfect fit
• I am always asked to stand at the back whenever taking group photos 
• My classmates complain that I block their view if I am sitting in front of them.

This short exercise is highly interactive and prompts creativity and out-of-the-box thinking. Doing it will help them become more mindful of keeping variables concrete, specific and rigorous in their research.

• Resource collection: How to build data literacy on campus
• Tweaks to make when teaching political science and social policies in the GenAI age
• Strategies to help students conceptualise their research projects

Randomisation and causal inference

For this activity, I randomly divide the class into two large groups based on the last digit of their student numbers (whether it is an odd or even number). I then invite them to stand up if they have certain traits, such as being a male or a female, if they live in residential halls or not, whether they are wearing a society’s hoodie or not, and so on. This exercise aims to highlight that, due to the randomisation of the groups, both observable and unobservable characteristics of both groups are roughly equal and the researcher can then assign a treatment or test to just one group, allowing the researcher to see the “true” causal effect. This stimulation can allow students to stretch their bodies a bit after a long lecture and enable them to understand the power of methods in a more personal manner.

Field research and case studies

This exercise requires me to come up with several research questions and encourage students to think about how they can potentially make use of field research and case studies to answer them. For instance, I ask them to look into whether an elite high-school background affects an undergraduate’s popularity on campus, whether gender imbalance increases conflict in student association meetings and whether campaigning while wearing a business suit affects campus election outcomes. The aim here is to provide more relatable research contexts that will allow them to come up with more interesting and critical questions for conducting research inquiry.

Survey questionnaire design

At the start of a class, I ask students what they would ask their research participants if they wanted to investigate Hong Kong university students’ opinions on dating and marriage. Students must then share their questions and I invite others to comment on their appropriateness. After some brief discussions, I show students a hypothetical and poorly written survey and ask them to compare their own questions with the survey ones. This comparison can help them understand the difference between effective and poor survey design.

Quantitative statistical analysis

For this activity, I prepare and upload a hypothetical raw dataset on a list of participants of an extra-curricular activity for my students to process. The data captures their student number, donations collected for the club, hours spent on club activities, expected GPA, gender and level of interest in the club. Students need to then perform a basic analysis of these variables. They must calculate the mean, median and mode and portray the relationships between the variables using appropriate graphs or tabulations. Students can then play with these numbers to become more data literate and learn to navigate the statistical software.

Qualitative thematic coding

For this activity, I offer students a list of excerpts from interview transcripts adapted from real articles from top-tier journals related to first-year undergraduate student residential experiences and life outcomes in Hong Kong. I then ask students to read the transcripts and identify recurring words, phrases or concepts that stand out to them. 

After that, I show students some real analytical results with a big coding table illustrating the themes, categories, subcategories and code examples throughout the open, axial, selective, and theoretical coding processes. This can offer insights into how to categorise and group codes into meaningful clusters in a hands-on manner.

All of these exercises require minimal prep work, saving teachers time while enabling them to ease students effectively into the world of research.

Adrian Man-Ho Lam is a course tutor in the department of politics and public administration at the University of Hong Kong.

If you would like advice and insight from academics and university staff delivered direct to your inbox each week, sign up for the Campus newsletter.