Video: Introduction to fieldwork

﻿Good day, geographers, and welcome to this lesson, introducing fieldwork. Fieldwork plays a really important role in geography, and it gives us the opportunity to get out and about to investigate the world around us. I love travelling, but my mom hates me going because she worries about me, but that always used to be my fallback excuse. I have to go, I'm a geography teacher. I'm always curious about what I can see around me, and never miss any opportunity to teach my friends in geography as we're climbing mountains or kayaking down a river, but there are lots of great fieldwork opportunities right outside our door, however. We don't need to go so far. I'd be confident in setting the hypothesis that geography students love field trips. For today's lesson, all you need is a pen, pencil, paper, and a ruler. In a second, I'm going to ask you to pause and take a moment to get those, and clear away any distractions around you. Well, tentatively, you might choose to test the hypothesis that it will be too noisy where you are, and move to a quieter place where you won't be disturbed. Pause now, and I'll see you back in a second. So title on top of your piece of paper for me, please, "Introduction to Fieldwork". I'm going to get ready to start. The best thing about geography is fieldwork, but it's not just standing in a field in your wellies. This afternoon, I hit the shops, but it was a bit noisier than my morning. Fieldwork always starts with us coming up with a good question we'd like to investigate, a hypothesis. A hypothesis is a statement that you are going to test. A large challenge when living in urban areas is traffic, and I'm going to test my hypothesis today. Traffic decreases with distance from the town centre. The next step is to collect some primary data. Earlier, I made a tally chart to record my findings. I'm going to tally the number of vehicles that come past in a five minute time period. It's important to do a risk assessment when you undertake any fieldwork, so I've chosen to stand behind this railing. I'm doing this three different locations, moving away from the town centre. I've done my count at each location twice to make sure I can increase the reliability of my data. Traffic is significantly less at this location. Let's talk about results. In the town centre, I recorded a mean number of 108 cars over a five minute period. Moving away, I then recorded 53 cars in location two. And finally, as you can see, furthest away from the town centre, the traffic was very light with a mean number of just two cars per five minutes. After collecting my data, I needed to present it in a clear way. I use flow arrows to do this. The width of the arrow represents the number of vehicles, whereas the arrows' direction shows the traffic flow. This is much clearer than a bar chart. The bar chart doesn't show locations, and while it shows traffic decreases, that doesn't link to distance from the town centre. If we put it all together in a conclusion, today, I have proved my hypothesis. Traffic does decrease with distance from the town centre. One final thing, though, we need to evaluate our fieldwork. My evaluation is that the reliability of my data could be improved if I completed my count at different points during the day, so that's what I'll do next time. Busy day, haven't I? Okay, so we're going to start looking now in more detail about how we structure our fieldwork. The first thing we have to do is we have to come up with a question or a hypothesis. We need to go out and we need to collect our data. We need to present our data and then we need to analyse it. All of those steps will help us come to a conclusion, and we then have to evaluate, what did we do well, what did we not do so well? Right, let's test what you can remember straight away. I would like you to put the field work steps into the correct order like the diagram below. For each stage, I would like you to add the correct example. Pause the video, come back when you're done, and we see how you've gone. Stage one was question or hypothesis. And an example of this was does tourism have an economic impact in Blackpool? To collect data for that, we might have chosen to do a questionnaire. We might present that data presentation on a bar chart or a pie chart. We might then have analysed the data by saying 90% of the people said they spent over 10 pound on that visit. That would help us come to the conclusion that tourism does have an economic impact in Blackpool. But when we evaluate our study, we might have decided we wanted to increase our sample size by asking more people. We're going to go through each of the stages step-by-step. So the first one is a question or a hypothesis. A hypothesis is an idea to be tested, something we can either prove or reject. Have a look at that picture for me now. What could you test that was human geography? What would you like to test that is physical geography? So just five seconds to have a look at that photo. We could have the hypothesis that tourism has environmental impacts. If we were looking at physical investigation, we might have a look at whether hard engineering or whether that groyne restricts longshore drift, because we can see the beach has different widths each side of the groyne. Your turn to have a go. I've given you three different images, three different locations where we may undertake field work. Please, can you match these hypothesis to the correct location? Pause the video, and then we'll check how you got on. Right, hard engineering can have positive economic impacts. That would be most suitable in location C because in that location, they have groynes. Regeneration has a positive economic and environmental impact would be most suitable in location B. The area has recently undergone regeneration, so we might want to investigate what impacts that has had. And finally, environmental quality can influence quality of life, and that might be suitable in A. Next stage of data collection, this is the exciting bit when we get to go out and about. Primary data is fieldwork data that you have collected yourself. An example of this might be a questionnaire on how successful regeneration is, or it might be stood in a river, measuring the river depth from source to mouth. Secondary data is fieldwork data that someone else has collected. For example, you might research on the internet the cost of the regeneration project. That's not something you could find out probably by walking around the area. It could be river discharge figures for the whole of the past year. You couldn't get that data, and if you did it for the next year, it would take you a very long time. So secondary data is very important in providing background information and helping you understand the context of your inquiry. We also talk about quantitative data. That's a tricky word to say, say it for me, quantitative, quantitative. This data is numerical data. If we measured the width or depth, we would get a number. The river is four centimetres deep. The river is 34 centimetres deep. The other type of data is qualitative data. And again, a tricky word, qualitative. This data is not numbers. It tends to be opinion based data. So if you're out looking at regeneration and you ask someone, what is the most successful feature of Boscombe's regeneration project, they would give you their opinion. They might say that it was the climbing wall. They may see that it's more jobs. So that's non-numerical data. We call it qualitative data. Which of these is most likely to be the secondary dataset? Final three seconds, have you written it down? And it is population numbers. There is no way on a Thursday afternoon, you're going to be able to count every single person that lives in the town. You would need to get secondary data for that information. Which one of these is the qualitative data? Five seconds. It is questionnaire data. that's opinion based. There are lots of questions for you to consider, though, when you think about data collection. How are you going to collect that data? Why are you collecting it? Justification is so important. What sampling will you use, and we're going to look at that in a second. What equipment do you need? It's no good wanting to collect data if you don't have the equipment. How will you record it? You need to set up your questionnaire, or set up your data table before you go. So what data could we collect? Lets have a look at these pictures, five seconds. Can you think of any data we could collect? I'm going to go along the pictures from the top. So we can have a look at the pebble size, or we could have a look at how rounded those pebbles are. We could collect environmental quality survey, so looking at how clean the street is, how many of the buildings are occupied? We could have a look at their appearance. We could have a look at beach profile, so how flat or steep they are. We might ask questionnaires on regeneration. We might get out and about measuring river widths, or we could be conducting interviews with local shop owners. For whatever data we want to collect, it's really important that we complete a risk assessment. We need to think about what are the risks and how we can reduce them. In the photo, we can see people undertaking a river investigation. Weather can prove to be very hazardous. You can see that they have mitigated the risk, so reduced the likelihood of it causing harm by ensuring that their clothing is suitable. They have warm coats, gloves, and hats to avoid catching hypothermia. If the river was deeper in the lower course, it may not be safe to enter. As a general rule, you should only enter the river if the water won't go over the top of your wellies. But it isn't just physical geography that has risks, though. In urban environments, you still need to consider hazards like traffic, and take precautions such as always making sure you cross at a traffic light, so zebra crossing. Sampling is where we take a selection of data. It often is impractical or necessary to collect data from every person who enters a shop or every metre along the river. We wouldn't have the time to do it. Let's consider different ways we could sample the river's characteristics. For example, the river depth along the river. The first way is random sampling. We could collect the data at random. Using a random number generator, we could then sample each location, location one, two, three, four, five, six, seven, eight. The problem with random sampling is we could end up with all of our sample sites in one area, and that really wouldn't show us the change from source to mouth. A second way is systematic sampling. Here, we collect data at specific intervals. For example, every 400 metres down a river, all the way to the mouth. This would make sure that we looked at the characteristics all the way from source to mouth, but it could be very time consuming. Finally, we have stratified sampling. This is collecting data from different groups of the population to ensure fair representation or deliberately introducing bias. In this example, we know rivers are split into three courses, upper course, middle course, and lower course. If we want to understand how the characteristics change from source to mouth, we may choose to survey four locations in the upper course, and four locations in the lower course. It's also important to consider sample size. If I was looking at pebble size, by just measuring one pebble at each site, it wouldn't be very reliable. However, if I did a hundred pebbles at each site, it may take too long. 10 would be a more realistic number, and it would allow me to take a mean in case there were any anomalies. Your turn, which type of something has been used here? Five seconds, write it down. Did you go with systematic? So they've sampled at equal intervals through that river. Big task now, first thing I want you to do is I want you to pause, and I want you to make a copy of this table below. An important thing though, is you're going to have a bit of writing to fit in. So please make sure each row is three lines deep. Don't forget your readers, I don't want to see any messy tables, please. As soon as you've done the table, let's have a look at the task. You've drawn your table. Now, I want you to complete it using the information below. I've put up on the screen the seven definitions, and I've put up seven examples. So please complete the table. Pause, and I'll see you back when you're done. Best of luck. Right, let's check those. So the definitions and the examples are on the screen. Please pause now and make sure you've got them all correct. Well, we have a lot of our data. We need to decide how to present it. We need to be able to justify why I've chosen that type of presentation. We need to think more widely than just bar graphs and pie charts. Which presentation technique is most appropriate for our data? Is the data continuous? Is it in categories? Do I have numbers? Do I have percentages? All of these things will determine which data presentation technique we use. Line graphs are good for continuous data. For example, showing distance downstream of a river, or the number of tourists over a period of time. categories like pebble size or roundness might be best in bar charts, or if your sample size was different at the top of the river and the bottom of the river, you may need to convert them to percentages and pop them onto a pie chart. Scatter graphs are used for showing relationships, and radar graphs have multiple axes for things like environmental quality surveys. Instead of just creating graphs, locating them on a map or an aerial photo can aid our interpretation of patterns. As well as graphs, we might choose to use maps, annotated photos, field sketches, or leave the data in a table. We've collected our data, we've presented our data, now, we need to analyse it. We want to be able to describe the data. What can we see? We need to be able to identify patterns, and if we look at the total environmental quality score here, we can see that there's a pattern. From sites two to five, the environmental quality score increases. We need to identify any anomalies, and an anomaly in this data is the CBD. We need to be able to make links to data sets. This environmental quality survey may have been undertaken alongside some photo analysis of each site. And then we need to explain the data. So the fact that the CBD environmental quality score is higher, potentially because they've just had the area regenerated. Sometimes it might be appropriate for us to use statistics to aid our analysis. We might calculate the mean, the mode, the range of the data. So examiners really want to know your justification. Why did you choose that particular type of graph? So have a go yourself. I've given you three types of data and three types of presentation. Pause the video and try and match up the data with its correct presentation. Data A said modes of transport used by students getting to school. That would be appropriately presented on a pie chart. We could give percentages. For example, 60% of people used bikes to get to school. 25% of people went by car. Data B was an environmental quality survey at different locations. There were six categories of information on my survey. So therefore, a radar graph would have been most suitable. It's got as many axes as you would like. So this one here has got six different axes to show the different data for the three sites. Data C was river width at different distances down a river. That would look at relationships. So here, you've got six sites, and you've looked at the river width down that river. It's showing the relationship. Then we need to pull it all together as a conclusion. In a conclusion, you need to consider how does your data provide evidence to answer the question or to support your hypothesis? You might want to consider how valid is your conclusion? Validity means did the data you collected actually answer the question you'd intended it to? The conclusion tends to be much shorter than the analysis, as we're just using it to summarise our study. Finally, it's the evaluation. It's really important to be honest with ourselves. What did we do well, what could we have improved? So were there problems in your data collection method? Where are there limitations with your data? How reliable was your data, and reliable means how repeatable it was. If you went back and did that survey again, would you get similar results? What other data would have been useful for you to have had? Gosh, we've gone through a lot today. Let's try and apply that. So I've given you four questions for you to consider. Pause the video, and I will see you when you're done. Best of luck. Let's see how you got on. Question one, that data was secondary because the students did not collect the data themselves. If they'd collected the data themselves, it would have been primary. Question two, for primary data, you could use random sampling, systematic sampling or stratified, and you only needed to write down two of those. It was two marks. Question three, there are advantages and disadvantages of all of the sampling strategies. I would suggest pausing the video so you can check what you've got. And finally, number four, if you're conducting coastal fieldwork, you may want to stay five metres away from the cliffs in case there's a landslide. you might choose to face the sea at all times to avoid being swept away by a wave, or you might want to carry a mobile phone in case of an emergency, so you can always get help. Tricky one, that. Well done for tackling those questions. That brings us to the end of today's lesson. It's time for a conclusion. Fieldwork is made up of six stages, the question or hypothesis, data collection, data presentation, data analysis, conclusion, and evaluation. My favourite by far is data collection. Right, well, it's time for you to present your learning today by clicking to the next page and completing the quiz so I can have a go at completing some data analysis. I can draw some pie charts and come to a conclusion about how well you've done. I can't wait to see how you've got on. I might even calculate some means and some ranges for the data. Thanks for your time today. My evaluation is though that we need to complete lots more fieldwork. So please join me soon, when we would investigate some coastal fieldwork and work through the six stages together. Have a great day today.

Exit Quiz: Introduction to fieldwork

Lesson summary: Introduction to fieldwork

In this lesson, we will be introduced to fieldwork. We will consider the different stages and how they work together.

Geography

Y10 Geography

Key Stage 4

Year 10

Today we have looked at fieldwork and how it needs to be structured. Complete the quiz below to see how much you have learnt.

How many stages are there to fieldwork?

Which stage comes after data presentation?

What is the key term for 'an idea to be tested which can be either proved or rejected'?

What is the key term for numerical data?

Which is the type of sampling where you you would survey every 5th person who walked past you?

Geography

Introduction to fieldwork

Video

Introduction to fieldwork - quiz

Question 1

Question 2

Question 3

Question 4

Question 5

Q1.How many stages are there to fieldwork?

Q2.Which stage comes after data presentation?

Q3.What is the key term for 'an idea to be tested which can be either proved or rejected'?

Q4.What is the key term for numerical data?

Q5.Which is the type of sampling where you you would survey every 5th person who walked past you?