Speaker 1: In this video, we're going to unpack the two related concepts of research constructs and research variables so that you can understand what they are, how they're different, and how to use them correctly in your research project. Let's do it. So first, let's start with a big picture view and then we can zoom into the finer details. Research constructs and variables both relate to the things of interest that you're going to explore within your study. For example, let's say you're interested in job satisfaction and more specifically you're interested in what factors impact an employee's job satisfaction. In this case, both job satisfaction and all of those things, those factors that might impact job satisfaction, would be considered either constructs or variables. So as you can see, constructs and variables are pretty central to any research project because they link directly to the things that you're interested in investigating. But it's important to say that these two things are different and we're going to unpack how they're different in this video. Before digging deeper though, it's worth mentioning that this video is based on an extract from our popular online course, Research Methodology Bootcamp. If you're new to formal academic research and research methodology specifically, you'll definitely want to check that out. And to say thanks for watching this video, we've got a special 60% off discount offer just for you. You can find the link to that in the description. So let's start with research constructs. Simply put, a research construct is an abstraction that researchers use to represent a phenomenon that's not directly measurable. For example, intelligence, motivation, or agreeableness would all be constructs because they're not directly observable and measurable. Since constructs aren't directly measurable, they have to be inferred from other indicators that are measurable or which can be directly observed. For example, the construct of intelligence can be inferred based on a combination of more quantifiable factors like IQ scores and language proficiency levels, both of which can be directly observed and measured. As a researcher, it's really important for you to clearly define your constructs and to make sure that they can be operationalized. In other words, you'll need to think about how you can develop ways to measure these abstract concepts or constructs using relevant indicators or proxies that accurately reflect the underlying phenomenon that you're interested in. In technical terms, this is called construct validity. If you want to learn more about that, we've got a dedicated video covering construct validity, and again, you can find the link to that in the description. Now that we've looked at constructs, let's move on to variables. Now, it's worth mentioning that within research, the terms construct and variable are often used quite loosely and sometimes even interchangeably, but as I mentioned, they're not the same thing. A variable refers to a phenomenon that is directly measurable and that can take on different values or levels. For example, things like someone's age or heart or weight and even their blood pressure would all be considered variables as these things can be directly observed and quantified using some sort of measurement instrument. Typically, constructs are more abstract than variables since they represent broader ideas and concepts, while variables are really specific measures within those concepts. In other words, as a researcher, you'll typically need to use a combination of variables if your aim is to measure a construct. Thinking back to the example that we looked at earlier, intelligence would be a construct, while IQ score and language proficiency levels would be two potential variables that you could use to measure that construct of intelligence. Now, it's important to mention that it's not always the case that a researcher wants to measure a construct. Oftentimes, research projects have other aims, for example, to explore how people experience something or the emotions that they attach to a certain phenomena or to a certain construct. So, long story short, while there is this relationship between variables and constructs, in other words, you can use a combination of variables to measure a construct, it's not always the case that you need both of these. Quite commonly, constructs will be the focus within qualitative research, while variables will be front and center within quantitative research. But that's not to say that quantitative studies never explore constructs, it's just that they use a combination of variables to do that. It's also worth mentioning that there are multiple different types of variables. So, you may have heard of things like dependent variables and independent variables, moderators and mediating variables, and so on. If you are keen to learn more about variables, we've got a dedicated video that unpacks all of that terminology, and again, you can find the link in the description. Now that we've unpacked what both constructs and variables are and how they differ, let's look at a few practical examples to solidify your understanding. A great example of a research construct is motivation. It's something that we can all relate to, whether that's high motivation or low motivation, but it's also something that we can probably all agree is pretty difficult to quantify and to measure. If you wanted to quantify motivation levels in a study, you could consider using self-reported motivation scales, for example, the situational motivation scale or the sports motivation scale. These are basic survey tools where people respond to a set of statements relating to their motivation levels. Another way that you could potentially measure motivation is by observing participants' actual behavior and assessing their level of motivation based on their level of persistence when they pursue a specific goal. For example, how much time do they spend or how many attempts do they make to achieve a certain goal? This would be another way in which you could quantify motivation. Another good example of a research construct is social capital. In other words, the quality and quantity of resources and connections that an individual has within a social network. To measure this construct, you could look at variables such as the person's network size. In other words, how many people do they know? You could also look at the diversity of that network, however you might define that, for example, age or gender or income level and so on. And so these factors would give you quantifiable variables which together you could use to assess the research construct of social capital. So to summarize, as you can see in both of these examples, the research construct or a research construct is more abstract and it's less directly observable, whereas the research variables are directly observable and most importantly measurable. So while these two things, research constructs and research variables, are similar in that they're both interested in your things of interest within your research study, they're not the same thing. And so don't make that mistake when you're writing up your research methodology. Alright, so hopefully you now have a clearer understanding of the two related concepts of constructs and variables. 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