Tag: Research skills

Data coding for qualitative research

Coding is an essential step in transforming raw and often messy data into structured insights that reveal the nuanced layers of human experiences and perceptions. In this post, I will explore the basics of data coding. It is important to note that there is no one “correct” way to code, with different researchers preferring different …

Common data analysis methods

Unlocking meaningful insights from data starts with selecting the right analysis strategy. Each approach to data analysis offers unique pathways for understanding complex information, yet choosing the best fit depends on knowing what each method can reveal. In this post, I explore five key strategies: statistical analysis, content or document analysis, thematic analysis, phenomenological analysis, …

Common data collection methods

In research, data collection is the cornerstone of meaningful analysis. Whether you’re conducting a small-scale qualitative study or a large quantitative survey, the method you use determines the depth, breadth, and reliability of your findings. Imagine you’re trying to understand how people form habits such as saving money, staying fit, or using technology. Do you …

Participant recruitment strategies in research

The way researchers select their participants impacts the validity and reliability of their findings, making participant recruitment one of the most crucial steps in the research process. But how do researchers go about this task? What strategies do they use to ensure their sample accurately reflects the broader population or the group they are investigating? …

Exploring 10 popular research designs: a quick guide

In research, the design chosen plays a pivotal role in determining how data are collected, analysed, and interpreted. Each design provides a unique lens through which researchers can explore their questions, offering distinct advantages and limitations. Below, I summarise ten common research designs, spanning qualitative, quantitative, and mixed methods approaches. Action Research Action research is …

The AI literacy framework for higher education

In an era where generative artificial intelligence (AI) permeates every aspect of our lives, AI literacy in higher education has never been more crucial. In our recent paper, we delve into our own journeys of developing AI literacy, showcasing how educators can seamlessly integrate AI into their teaching practices. Our goal is to cultivate a …

Developing AI literacy in your writing and research

I have recently developed and delivered a masterclass about how you can develop your AI literacy in your writing and research practice. This included a series of examples from my own experiences. I thought I’d provide a summary of this masterclass in a blog post so that everyone can benefit from my experiences. Artificial intelligence …

Moving beyond binaries in research: weaving the tapestry of participants’ experiences

In today’s data-driven world, there is a lot of talk about making decisions based on so-called objective data. For example, schools and universities use information about the mix of students and staff to shape how they teach and run things. Information such as age, where people live, how much schooling they have had, or their …

Theoretical and conceptual frameworks in research

Frameworks in research play a crucial role in shaping the direction of a research project. They serve as the foundation upon which studies are built and analysed, offering a lens through which researchers can interpret their findings. However, they are also a source of confusion for researchers so, in this blog post, I explain the …

Demystifying research paradigms

Let’s talk about one of the most complex parts of research – understanding the philosophical underpinnings of your worldview and how this shapes the way your research is done. This is called a research paradigm and is one of the areas I get the most frequent questions about from graduate research students. The popularity of …