[0:00]Hi, and thank you for joining me on this little session on unseen fieldwork. Today in this video, we're going to be going through the inquiry process.
[0:08]We're going to talk about some of the key bits of information I think you need to know for the exam, and also some example exam questions, so you know exactly what you're up against. Now, part of the paper three exam will be looking at something called unseen fieldwork, where in other words, you're going to be given another student's fieldwork and you're going to be asked questions about their approach. Now, all geographical inquiry or fieldwork follows the same process. We start off by introducing and planning the inquiry, then we choose which methods we want to use and we collect some data. We then present that data in a graph or a chart, and then we analyze it. Once we've analyzed our data, we can draw conclusions, and that conclusion will answer the overall inquiry of our focus. And once we've done a conclusion, we can then evaluate our approach. Now, because this unseen fieldwork, You are going to be asked to do these six things for another student's work. In other words, you might be asked to evaluate the methods they used. You might be asked to suggest why their data presentation was good or for a better way they could present it. You might be asked to analyze their data, or they might give you some data and ask you to form a conclusion about it. So, let's get started with the fieldwork then. So, when I'm planning the fieldwork process, the first the first thing I'm going to do is produce an inquiry question, all right? So, I'm going to make an inquiry question, and that inquiry question needs to be manageable. I need to investigate something that I can do within a day, or half a day. It needs to be measurable. So it needs to be something that I can actually do as a year 11 student within a day. And it has to be specific. So it has to reference something in particular. So for example, a bad inquiry question might say something on the lines of, to what extent is crime in Liverpool getting significantly worse? That's not a manageable question because I'm not going to be able to go as a year 11 student and work out the answer. I'm going to find it very difficult to measure that, uh data, and it's not particularly specific. It's quite a general question. A better inquiry question might be something on the lines of, how do people perceive environmental quality in Toxteth, Liverpool?
[3:00]And for that inquiry question, I've got something that's manageable. I can probably find out the answer to that in a day or an afternoon. I can think of ways to measure how people's opinion think about environmental quality in Toxteth, and it's also quite specific.
[3:15]The other thing you need to do when planning fieldwork is a risk assessment. Now, all the teachers before you leave school, have to make a risk assessment. And the idea is that if you were to have done this fieldwork yourself, you would also have to think about the risks. And basically, all that is referring to is the idea that things can go wrong. And it's what you can do in that risk assessment is identify the risks and then put things in place to mitigate that risk, to prevent it from actually happening. So for example, a potential risk on coastal or river fieldwork could be unstable land or steep river cliffs that you could fall into and injure yourself. So, how do we mitigate that? Well, we wear appropriate clothing and appropriate footwear. If we're in a city center, there might be the potential risk of engaging with the public or engaging with strangers in the community, or getting lost, for example. And a really good way of safeguarding that, as a risk assessment, would be to have a buddying up system. So students have a buddy in which they can check on at all times, so if anyone's got lost. And it's also things as simple as checking out when the tide's going to come in. Because if you're going on to do a beach survey, and you're planning to do your fieldwork, as the tide is coming in, you might find that quite risky. So by checking the tide timetable before you go, and you're going to make sure that you're not going to get caught in a high tide, and any injury, uh the death, et cetera, you know, it's a bit extreme, you know, you're not going to get like that, okay? Now, when we do the fieldwork, it's all about collecting data. But before we collect data, we have to really think about what is that data going to represent. What methods are we going to use? How are we going to sample it? How are we going to make sure it's accurate and how are we going to make sure that it is reliable? We're going to go through those things now. So, let's imagine I'm going to a town center. And in my town center, I would like to measure how the air pollution changes in Liverpool City Centre. What I need to think about then, is, well, how am I going to get that data?
[5:39]Am I just going to randomly go to a place in Liverpool, take the air pollution reading, and then use that in my conclusion, because that would be very inaccurate. It could be completely biased because I could literally go to the main road, the Strand in Liverpool, and I could find really high air pollution, and then my conclusion saying, well, there's really high air pollution in Liverpool. That's not fair. So what we need to do to remove bias in investigation is something called sampling. Now, sampling is whereby you are removing bias from your choices. So for example, a simple random sample would be me, choosing 10 locations in Liverpool, put them into a hat, draw in three or four out and using them for my samples. Another technique would be systematic sampling, whereby, again, I might decide to
[6:40]do a, a sample technique at every single traffic light, or I might say that every 100 meters, I'm going to do a reading or every 20 meters, I'm going to do a reading and that is known as a systematic sample. And finally, stratified sampling, which you might not really use really here, is where you choose sub groups of the population. So maybe you choose gender, or maybe you choose race or religion. And then you choose to ask a certain number of those people a question. So for example, if you're in a room of uh of people, you might do a stratified sample by determining that you're going to ask um an equal number of different genders, you're going to ask an equal number of different races or different religions as well. In geography, the systematic sample is what you would most likely use. You would place a quadrat at every 10 meters to measure a sand dune. You would measure air pollution every 20 meters in Liverpool. Now, we do this for a couple of reasons, mainly because sampling makes our fieldwork data more reliable. And what that means is that if we were to complete the same investigation again, another student may get a similar result. We can improve our reliability as well and our accuracy by doing several things. We can increase the sample size, get more data. The more data you get, the more reliable your that your your answers will be. We can visit the site at multiple times a day. If I only study air pollution at 9:00 in the morning during rush hour, that will give me massively different data, to if I was to measure air pollution at 12:00 p.m. or at 3:00 p.m. outside of rush hour. We could visit the site on multiple occasions to make sure that that one day wasn't an anomaly, and we could also add in additional methods as well. Okay? Now, when it comes to actually collecting this fieldwork, there are a couple of things we need to know about. Firstly, primary and secondary data. Now, primary data is data that you go and collect yourself in person. And primary data is pretty good. Because generally speaking, it can be quite trustworthy. Because you know that you're collecting the result, you know who's doing it, you know it's going to be more reliable. It will be up to date information. In other words, you know that what you are collecting is the most up-to-date information possible. However, it can sometimes require cooperation from other people who may not help. If I'm doing a survey, they might not want to answer it. It's very, very time consuming, doing set primary data, and we might not always find the answers we need. So sometimes, I might also have to refer to secondary data, which is using data that someone else has collected. And this has quite a few benefits. It's very easy to collect. I can go on Google, I can type in what I want to find out, and I can find some secondary data. It gives you data from the past, so not just in the present. But not always reliable. It can be out of date quite often, um it is actually out of date as well. And the source itself isn't always trustworthy, like Wikipedia, who knows who's collected that data. It could be anybody, so we can't always trust secondary data. Now, some examples of these then. So primary data would be your questionnaires, your field sketches, your bi-polar surveys, annotated photographs, pedestrian counts, beach profiles. Your secondary data is more likely to be things like OS Maps, using the census for population data, online photographs, geology maps, et cetera. And my strong advice would be to make sure that you know a couple of primary and secondary data methods and you remember those pros and cons. So maybe make sure you make a notes throughout this video as well. Okay? Within that then, we also have two more subsets of data. We have something called qualitative data, which is non-numerical data. Examples include field sketches, photographs, written descriptions, poems and stories. They're ways of collecting information, but they're not numerical. They're opinionated, they're subjective. And they are useful because they can help us gain a sense of the place. They can help us gain a perception of a place. But they can't really help us out studying much about a river or a coast in terms of the actual physical side of it. So therefore, we might have to use some quantitative data, which is numerical data. And that data might be measuring velocity, measuring the build up of sediment, pedestrian counts, measuring the number of waves every minute. And that data is subjective, opinionated, which is less reliable and less likely to be repeated.
[12:10]Now, the next stage of our data or fieldwork process is data presentation. So once we've collected our qualitative and quantitative data, and once we've decided, we've got our primary, our secondary sources, we need to find a way to present those data in graphs or charts. And we do that because it helps us analyze or interpret and helps us draw conclusions. It also makes the data far easier and quicker to read and understand. So it helps with our analysis and our conclusions. Now, when it comes to the questions on these exams, it's going to give you some graphs or charts or ways that students have presented their data. And the first thing we need to ask ourselves is, is the data discrete or is it continuous? Discrete data is data values that are only in certain groups or values, so for example, the number of brothers or sisters you have. If you're asking for your favorite soft drink, Coca-Cola, Fanta, Sprite, that is discrete data. And for discrete data, you need to use a data presentation technique that suits that, for example, using a bar chart or a pie chart. For continuous data, that's data which can take any value in an order, even in decimal points. So for example, if I was trying to measure the distance from the ocean and the steepness of the beach, that is continuous data because in degrees, I could measure at any point, take value of what the gradient of that beach is.
[14:10]And you need to think about that when you're looking at some of these data presentation methods. So, for this one, for example, this is not a good way of presenting noise pollution in five areas. Because it is discrete data, and therefore, if it is discrete data, we might include bar charts. We might include something called a proportional symbol, which is essentially where the size of the symbol represents how large the data set is. And that's because of accuracy, and because it's very hard to read, it's not very visibly recognizable. It's quite hard to read that graph. So it a lot of it will come back to these two points here. Okay? So I've got another example then. So, on figure eight, we've got an isoline map of pedestrian flows. What the student was doing here, we're trying to work out how many people, or what, how many people walk along certain parts of London. And the problem with that map is it is quite hard to read. So what alternatives do we do? Well, we could have done proportional flow lines. We could have done located bars, or we could have done located proportional symbols. If there is a map to do with the data, you need to make sure that there is a spatial dimension to it. If there was a map using data, you need to make sure that it includes some sort of location. For example, you could put a located bar chart within that fairly easily and just use um that information essentially, okay? Right then. Another example. We've got study figure seven, data collected by means of questionnaire about the employment structure of a town. And it's given you a compound bar chart to complete. How else could we present this discrete data, the three different sectors of the economy. Well, we could do a pie graph or a pie chart. This is a compound bar chart, so we could just do a bar chart, or we could do a triangular graph, which is essentially where we put primary, secondary and tertiary in three triangles, and you work out the percentage of each one. Another method here. Study figure five, two sets of data collected by students who were carrying out a geographical inquiry about traffic problems in a town center. The following four methods were considered for presenting the data shown in figure five. Well, if we look at figure five, we've got car ownership in the town. We've got the date and we've got the number of cars. So, for B, for car ownership, sorry, it's B, the line graph that is going to be the best option. It is continuous data. For the second one, how they traveled there, car, walk, bus, motorcycle, it is discrete data, which means it would be a pie chart that we use to represent those subgroups. If there was a map showing the most popular routes, you might use C or D in your answer. But remember, we only need location where it specifies certain parts. Now, within this as well, this kind of links back to the primary, secondary, tertiary criteria as well. But we also need to look at the strengths and limitations of data collection methods. So on the side here, we've got a student and they have used a noise level. Level one, they can hear a whisper. Level five, they cannot hear the conversation at all. And in theory, they could work out how much noise pollution there was by doing this.
[18:28]Now, instantly, I'm thinking of this two things. Firstly, it's primary data. They've collected it themselves. And secondly, that is also qualitative data as well. It's based on opinions, on feelings. So, if we think back to the previous part of this this video, we already can be thinking about what the limitations and advantages are going to be. So, advantage-wise, it's quick. You can gather a lot of information. It doesn't require any equipment, and it's fairly easy to understand. However, it is subjective. It is very subjective. It's not totally clear what those categories mean. To me, a whisper might mean a different thing to you. Some people might have slightly better hearing than others. You might have a different perception of noise. So it's not a very accurate method. And by doing that, it would make it very difficult to compare this investigation with another person or another investigation itself. So give a second method here then. These guys have done an environmental quality survey in a town center. What they've done is, is when they've put a negative, they've put it in the minuses, and when it's a positive opinion, they've put it in the positives. Now again, I'm thinking of this, it's primary data, it's qualitative. So advantage is again, easy to read and understand, quick to complete, so a lot of data can be gathered, does not require any complicated equipment. And disadvantages, very subjective. People may have different opinions on what's good or what's bad. It's very difficult to complete again. Some people may not understand the language and simply say anything. Anything on there that is a disadvantage of qualitative data, you would be able to add in for this exam question as well. Now, the final part of this really today is looking at conclusions and analysis. So, for this one, you could be handed some data and asked to give a conclusion or asked to evaluate a conclusion as well. So, on the left, we've got figure six, which shows a car park survey. What they've done is, they've taken A, D, B, C and E, and they've measured what percentage full it was on Wednesday and what percentage full it was on Saturday, okay? So it says, suggest reasons for the differences shown between Wednesday and Saturday. Well, let's think about this. On a Saturday, I'm more likely to go shopping. So therefore, I would expect the car park to be more full. There might be events on a Saturday, like a football match that makes me go and visit this car park. I might also say that we could think about the time of day. 11:00 a.m. is likely to be busier than 2:00 p.m. because in the morning people are more likely to run their errands. And to get the next couple of marks in this question, all you then do is you'd back up these with some example percentages. So, for example, you could say, on Saturday 11:00 p.m., 11:00 a.m., in car park A, it was significantly higher at 92% compared to 72%. This could be because of on Saturdays, people might go shopping. So look for obvious answers, then use data to back up your answer for a conclusion. The same thing here, comparing the relationship between distances from source to depth of a river. We're saying the same things. We're looking at the relationship, we're looking for any anomalies, we're looking for the general pattern as well. Okay? And we're using data to back up our answers. Now, the final part of the fieldwork here is there will be definitely be some sort of maths questions on here. The first one could be about interquartile range. And remember for this, we put the numbers into order. We find the median number. We then select the numbers above and below the median. Then within those subgroups, we find Q1, the median, and Q3, the median. We subscribe Q1 from Q3 to get the interquartile range. So you line them all up and you find the median. You split them into the upper and lower quartiles, then within that you find the median again. And for this question here, that would work out at 10.4 minus 1.4, which would equal nine. If you want to pause the video and have a go at that yourself to see how I got that answer, please do. You could also be asked, again, for interquartile range with pebble size. And just because it's using geography, doesn't mean that the maths changes. All I would do is I would line them up from sample one to 11. I would find the median. I would then split them into the two groups above and below the median. Find their median to calculate the interquartile range. And if you'd like to have a go yourself, please do. But 12 is the upper quartile, Q3. Six is Q1. So my interquartile range for that would be six. And the last thing that is likely to pop up could be median and mode. The mode is the most common value, the value which appears the most. The median, the number in the middle when all values are arranged in ascending order, the range is the highest value minus the lowest.
[24:51]So, hopefully that has gone through most of the fieldwork stuff there, and helped you feel a little bit more confident about that.
