Explorez tous les épisodes du podcast Mixed Methods Research

Discussing the planning and testing phase of data analysis tools upgrades.

This is the findings from running three analysis on a same data set - one manual, one rule-based and one machine-learning based to summarize unstructured research data.

I discuss an example of a project where I used semantic analysis to humanize data during research analysis.

We discuss three challenges in reconciling structured and unstructured data in research analysis.

We discuss the process of building custom dictionaries for research and three limitations of commercial dictionaries.

What might be an interesting construct for automating the processing of some of your participant research? We look at semantic automation.

What should we think about when paying for participants? How can payment skew the research work?

This is a ten minutes segment from a one-hour interview with guest Charlie Beckett, past senior producer and programme editor at BBC News and Current affairs, current founding director of Polis, the think-tank for research and debate around international journalism and society (London School of Economics). You can find the original podcast episode here: Different by Design.

UPDATED - This is Part of the Data Stories Series

Written by Corina Paraschiv.

A special thank you to Kenneth D. Bailey’s work on typologies and taxonomies, for having inspired this Data Story.

A reflection on the value of self-referential coding in informing your research - when handled cautiously.

During COVID, we had to rethink how to design the end-to-end experience for co-creation workshops, for the digital realm. Inspired by Ian Chipchase’s reflections on characteristics of popup studios, here is how we digitalized our workshop spaces for participants.

I share an example from a project around wayfinding and people with autism, as a springboard to rethinking inclusive research protocoles.

How do we maintain objectivity and remove bias, while also accommodating research participants?   A short reflection.

This is Part of the Data Stories Series.

Written by Corina Paraschiv

A special thank you to Kenneth D. Bailey’s work on typologies and taxonomies, for having inspired this Data Story.

Learning the programming language R can be done through two approaches. Which one makes the most sense for researchers?

Researchers use categories all the time.  While embracing diversity and plurality, researchers nevertheless often resort to classifications and groupings.  Why are categorizations so important?  What role do they fulfill in our roles as researchers?  This episode is part of the Data Stories Series, and you can find a written version of it on Medium, here.

How do research design decisions affect mixed methods research budgets?  I discuss the topics with a concrete project example, and invite you to see the details of the research in the conference session "From qualitative to quantitative data analysis: Using binary variables coding and non-parametric statistics in industry research", over at MAXDAYS23 , MAXQDA annual conference here.  

Qualitative vs quantitative data research: the age-old question.  In this episode, we investigate why sometimes, quantitative data research isn't necessarily better.  You can have a look at the Medium Article "Where Data Falls Short" here.

How do you find the best tools for your user research?  How do you strategically think about software and research app services, as the options increase?  What features truly matter?  This episode combines practical insights and self-reflection to help you determine your perfect tools - now and in the future.