In a previous post, I gave a brief overview of a widely used, vanilla flavour type of content analysis. It’s far from the only type.
There are methodological debates about most things relating to content analysis, which have been running for the best part of a century, and which don’t look likely to end any time soon. There are, in consequence, numerous different types of content analysis, and many approaches to content analysis. The following sections give a very brief description of some of those other types. I’m planning to write in more detail about them at some point, when there’s nothing more exciting to do…
This is a guest article by Dan O’Neill; I hope you’ll find it interesting and useful.
How to conduct a successful focus group
By Dan O’Neill
While focus group methodology is often discussed in the context of market research, it is also used in a variety of research fields. Focus groups have been used to gather data on a wide range of research topics including: attitudes towards tobacco, meat quality, farming, electronic resources, patient quality, solar technology, health and safety, property management, and many more.
If you’re thinking about conducting a focus group for your own research, below are some fundamental things you’ll need to do to prepare for this type of study.
The previous articles in this series looked at mental models and ways of making sense of problems. A recurrent theme in those articles was that using the wrong model can lead to disastrous outcomes.
This raises the question of how to choose the right model to make sense of a problem. In this article, I’ll look at the issues involved in answering this question, and then look at some practical solutions.
So what is referencing anyway, and why should anyone care about it? What’s the difference between the Harvard system and the Vancouver system and the assorted other systems? How do you choose references that send out the right signal about you?
The answers to these and numerous other questions are in the article below. Short spoiler: If you do your referencing right, it gets you better marks, and you come across as an honest, capable individual who is highly employable and promotable. Why does it do this? Find out below…
The first article in this short series looked at one reason for movies presenting a distorted version of reality, namely conflict between conventions.
Today’s article looks at a reason for movies presenting a simplified version of reality. It involves reducing cognitive load for the audience, and it was studied in detail by Grice, in his work on the principles of communication. It can be summed up in one short principle: Say all of, but only, what is relevant and necessary.
At first sight, this appears self-evident. There will be obvious problems if you don’t give the other person all of the information they need, or if you throw in irrelevant and unnecessary information.
In reality, though, it’s not always easy to assess whether you’ve followed this principle correctly. A particularly common pitfall is assuming that the other person already knows something, and in consequence not bothering to mention it. Other pitfalls are subtler, and have far-reaching implications for fields as varied as politics, research methods, and setting exams. I’ll start by examining a classic concept from the detective genre, namely the red herring.
Note: I’ve written this article, like all the other Hyde & Rugg blog articles, in my capacity as a private individual, not as a member of Keele University.
This article intended as an explanation of why researchers need to pay serious attention to research ethics. It’s not intended as a complete overview of all the issues that ethics committees have to consider, which would require a much longer article. For example, I don’t discuss the issue of informed consent, although this is a very important topic. Similarly, I don’t discuss whether ethical review could lead to a chilling effect on research. Instead, I’ve focused on the underlying issue of why a researcher’s own opinion about ethics isn’t enough.
Research ethics committees are interesting places. The ethics committees I attend are the only committee meetings that I actively look forward to. This is partly because everybody is focused on doing a good, professional job as quickly and efficiently as possible, and then getting back to our other work. It’s also partly because the cases that we deal with are often fascinating.
Most research students view ethics committees as an obstacle to be passed, taking precious time and effort. The reality is very different. If you’re a researcher, whether a novice or an expert, the ethics committee is a valuable friend, and can help you avoid all sorts of risks that might otherwise cause you serious grief.
In this article, I’ll discuss some ways that ethics committees help you, and some things that could go wrong in ways that you might not expect. Some of those risks are seriously scary. I’ve avoided going into detail about triggering topics wherever possible, but some of the things that go wrong with ethics might trigger some readers. By way of a gentle start, here’s a restful image of a tropical beach.
As regular readers of this blog will know, I have an awed respect for the ability of Ancient Greek philosophers to spot a really important point, and to then produce an extremely plausible but only partially correct explanation, sending everyone else off in the wrong direction for the next couple of thousand years.
Today’s article is about one of those points, where the Ancient Greeks didn’t actually get anything wrong, but where they laid out a concept that’s only part of the story. It involves a concept that can be very useful for making sense of consumer preferences and life choices, namely the difference between intrinsic properties in the broad sense, and extrinsic properties in the broad sense.
Here’s an example. The image below shows a pair of Zippo lighters. One of them is worth a few dollars; the other is worth tens of thousands of dollars, even though it’s physically indistinguishable from the first one. Why the difference? The answer is below…