1
00:00:01,000 --> 00:00:08,710
‫We're now going to look at a muddled answer for line graphs, which is, of course, a common piece

2
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‫of visual information that you could see in your task.

3
00:00:12,880 --> 00:00:20,590
‫One question a few of you have been asking for more of these modeled live writing type lessons.

4
00:00:20,770 --> 00:00:27,520
‫And if you do want to see more of certain things, then let me know and I will try and update and create

5
00:00:27,520 --> 00:00:29,080
‫new lessons for you.

6
00:00:29,800 --> 00:00:37,330
‫OK, so let's go back to our checklist in red at the top, we have our structure and organization,

7
00:00:37,510 --> 00:00:40,870
‫which as always, is your paraphrased introduction.

8
00:00:41,170 --> 00:00:48,010
‫The overview and to detail paragraphs, of course, will need some clear grouping which we can think

9
00:00:48,010 --> 00:00:51,400
‫about whilst we write our part underneath.

10
00:00:51,400 --> 00:00:58,420
‫We have a few writing features such as our adverb, verb, adjective, noun agreements and of course,

11
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‫mixed opener's in a different mix of sentence types to use in our writing.

12
00:01:04,990 --> 00:01:08,110
‫So let's move on to our question.

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00:01:09,400 --> 00:01:16,720
‫The graph below represents the total exports of clothing from three different countries over a time

14
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‫period, summarizes the information by selecting and reporting the main features and make comparisons

15
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‫where relevant.

16
00:01:27,280 --> 00:01:32,130
‫OK, so let's take a look at the visual information that we have.

17
00:01:32,140 --> 00:01:35,020
‫And once again, begin with the title.

18
00:01:35,410 --> 00:01:45,880
‫So our title says Clothing exports between 1990 to 2003 and then going to take a look at the line graph

19
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‫and see if there is a key, which there is.

20
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‫So the three countries are Colombia, Japan and Myanmar.

21
00:01:53,970 --> 00:01:59,970
‫It's worth saying that once you get to your question, it's definitely worth looking around the graph

22
00:01:59,970 --> 00:02:04,690
‫for visual information to get a better understanding of the data you've been showing.

23
00:02:05,320 --> 00:02:06,190
‫So back to the key.

24
00:02:06,190 --> 00:02:12,250
‫We've got these three countries, Colombia, Japan and Myanmar, and they are color coded onto our line

25
00:02:12,250 --> 00:02:13,180
‫graph above.

26
00:02:13,990 --> 00:02:19,600
‫On the y axis, we can see millions of dollars from zero to a thousand million dollars.

27
00:02:20,170 --> 00:02:34,120
‫And on the x axis, we have our years from 1990, 2000, 2011, 2012 and 2013 from just taking a quick

28
00:02:34,120 --> 00:02:34,650
‫snap.

29
00:02:34,660 --> 00:02:36,350
‫Look at this data.

30
00:02:36,640 --> 00:02:43,180
‫The big thing that stands out is Myanmar, which has gone from zero in 1990 and sprung up all the way

31
00:02:43,180 --> 00:02:47,380
‫to 800 plus 900 million dollars.

32
00:02:48,130 --> 00:02:52,190
‫That's just taking a very quick glance at the data we've been showing.

33
00:02:52,690 --> 00:02:57,040
‫So once again, we now need to think about creating our plan.

34
00:02:59,180 --> 00:03:07,360
‫OK, so we need to begin by grouping our data into the two groups, of course, that will correlate

35
00:03:07,570 --> 00:03:11,230
‫with what I describe in each detail paragraph.

36
00:03:11,680 --> 00:03:14,280
‫So here is the data that we have.

37
00:03:14,290 --> 00:03:21,220
‫I could group by country, although if I was to Group Colombia and Japan in Group one and Myanmar in

38
00:03:21,220 --> 00:03:26,570
‫Group two, that would mean detailed paragraph two would only discuss Myanmar.

39
00:03:26,860 --> 00:03:34,210
‫So to be able to compare in each detail paragraph, I think it's better to use the data to give me more

40
00:03:34,240 --> 00:03:38,260
‫idea about what I can compare in each detail paragraph.

41
00:03:39,490 --> 00:03:49,200
‫So let's go with Group one as being 1990 to, let's say, 2000.

42
00:03:49,570 --> 00:03:52,840
‫So I will compare in fact, 2011.

43
00:03:53,320 --> 00:04:01,400
‫And then for Group two, I'm going to go with 2012 to 2013.

44
00:04:01,930 --> 00:04:11,050
‫So in my first detailed paragraph, I will describe all three countries between the years of 1990 to

45
00:04:11,050 --> 00:04:14,350
‫2000 to 2011.

46
00:04:14,950 --> 00:04:21,400
‫And my second group, which will be detailed paragraph two, will be all three countries described again

47
00:04:21,910 --> 00:04:25,600
‫in 2012 and 2013.

48
00:04:27,150 --> 00:04:36,540
‫So let's move on to our overview and I need to think about a few general statements that I could write

49
00:04:36,540 --> 00:04:37,060
‫about.

50
00:04:37,470 --> 00:04:43,720
‫I think I'm going to split into Colombia and Japan and Myanmar.

51
00:04:44,160 --> 00:04:49,660
‫So that's how I'm going to describe a very general trend for each of those two.

52
00:04:49,680 --> 00:04:58,860
‫So if I do C.J. for Colombia and Japan and I'm going to say overall, no large changes.

53
00:05:00,770 --> 00:05:06,380
‫Although we can see, for example, with Colombia, there is an increase, it's not quite as pronounced

54
00:05:06,380 --> 00:05:07,380
‫as in Myanmar.

55
00:05:07,730 --> 00:05:13,400
‫Japan very much stays the same, fluctuate round about 550 million.

56
00:05:15,300 --> 00:05:25,650
‫And then we need to say something for me and myself, I just add an M and then I can say huge fluctuations,

57
00:05:25,860 --> 00:05:35,360
‫huge fluctuations in exports, because we can see from Moema, they get to zero all the way up to hundred

58
00:05:35,370 --> 00:05:36,720
‫and nine hundred and fifty.

59
00:05:37,020 --> 00:05:40,170
‫Then a huge downturn to 350.

60
00:05:40,680 --> 00:05:45,000
‫So there's a lot more differences in the export from Myanmar.

61
00:05:45,150 --> 00:05:48,220
‫Myanmar in comparison to the other two countries.

62
00:05:48,600 --> 00:05:50,070
‫So that's my plan.

63
00:05:50,110 --> 00:05:51,010
‫Let's have a quick look.

64
00:05:51,270 --> 00:05:58,230
‫On 1990 to 2011, Group two is 2012 to 2013.

65
00:05:58,240 --> 00:06:00,290
‫So they are mid detail paragraphs.

66
00:06:00,810 --> 00:06:08,910
‫My overview, I'm going to simply say that Columbia and Japan didn't see huge changes in their exports,

67
00:06:09,180 --> 00:06:17,130
‫whereas Myanmar saw very drastic differences between the years in their exports of their clothes.

68
00:06:17,910 --> 00:06:21,630
‫So it's time for me to move on to actually writing this report.

69
00:06:21,810 --> 00:06:27,540
‫And I do feel that I have a good understanding about the information shown to me now.

70
00:06:29,940 --> 00:06:37,560
‫OK, so let's begin with our paraphrased introduction, so return to the question, the first part of

71
00:06:37,560 --> 00:06:38,140
‫the question.

72
00:06:38,520 --> 00:06:45,330
‫The graph below represents the total exports of clothing from three different countries over a time

73
00:06:45,330 --> 00:06:45,800
‫period.

74
00:06:46,110 --> 00:06:54,220
‫So I need to use my understanding of synonyms to paraphrase and rewrite from my report the line graph.

75
00:06:54,240 --> 00:07:01,410
‫So instead of saying the graph below the line graph, or I could say the given line graph, the given

76
00:07:01,410 --> 00:07:12,100
‫line graph represents, let's say shows instead of represents the total exports of clothing.

77
00:07:12,120 --> 00:07:14,580
‫So that's very similar to what the question has said.

78
00:07:14,580 --> 00:07:15,560
‫But that's OK.

79
00:07:15,570 --> 00:07:27,630
‫We don't need to paraphrase and change everything from three different countries over a time period

80
00:07:27,630 --> 00:07:30,140
‫of 13 years.

81
00:07:31,170 --> 00:07:34,850
‫And once again, I do apologize for the spelling there.

82
00:07:34,860 --> 00:07:38,690
‫So let's read back our introduction paragraph.

83
00:07:39,000 --> 00:07:47,130
‫The given line graph shows the total export of clothing from three different countries over a time period

84
00:07:47,130 --> 00:07:48,440
‫of 13 years.

85
00:07:48,750 --> 00:07:51,330
‫So I've paraphrased the question.

86
00:07:51,330 --> 00:07:56,730
‫I've used some different expressions and language and I am happy with what I have written.

87
00:07:56,910 --> 00:08:00,510
‫So let's move on to our overview paragraph.

88
00:08:01,440 --> 00:08:08,220
‫You remember from the plan that the overview I grouped Colombia and Japan together and stated there

89
00:08:08,250 --> 00:08:13,420
‫weren't huge differences, especially not in comparison to Myanmar.

90
00:08:13,890 --> 00:08:21,070
‫I also mentioned in my plan that Myanmar saw huge fluctuations in their total exports of clothes.

91
00:08:21,540 --> 00:08:22,950
‫So let's begin.

92
00:08:22,950 --> 00:08:33,660
‫And of course, as always, overall, we can see that Colombia and Japan.

93
00:08:35,220 --> 00:08:36,840
‫Didn't see.

94
00:08:38,260 --> 00:08:45,480
‫Such huge fluctuations in comparison to Myanmar.

95
00:08:47,540 --> 00:08:54,200
‫So that very simply just gives an overall idea of the data that's been shown and I've managed to do

96
00:08:54,200 --> 00:08:55,250
‫it in one sentence.

97
00:08:55,790 --> 00:09:03,740
‫Overall, we can see that Colombia and Japan didn't see such huge fluctuations in comparison to Myanmar

98
00:09:03,740 --> 00:09:05,750
‫in and let's say what the fluctuations are.

99
00:09:05,750 --> 00:09:15,950
‫I didn't see such huge fluctuations in clothing exports in comparison to Myanmar, let's say, whose

100
00:09:15,950 --> 00:09:23,840
‫figures changed drastically over that time period.

101
00:09:25,520 --> 00:09:27,530
‫Let's have one more read through.

102
00:09:27,530 --> 00:09:35,060
‫Overall, we can see that Colombia and Japan didn't see such huge fluctuations in clothing exports in

103
00:09:35,060 --> 00:09:41,820
‫comparison to Myanmar, whose figures change drastically over the time period.

104
00:09:42,350 --> 00:09:48,320
‫So I think that gives a really nice overview of the visual information that we have.

105
00:09:49,880 --> 00:09:56,810
‫It's also important to note that I haven't included any specific figures in the overview, which you

106
00:09:56,810 --> 00:10:04,700
‫shouldn't do, we save that for the detail paragraphs which I'm going to move onto now, say, from

107
00:10:04,700 --> 00:10:12,910
‫the plan, you remember that I grouped Group one as 1990, 2000 and 2011.

108
00:10:13,250 --> 00:10:20,810
‫So in my first detailed paragraph, I'll be explaining and describing the data from the three countries

109
00:10:21,020 --> 00:10:23,660
‫over these first three years.

110
00:10:24,320 --> 00:10:30,410
‫So let's begin with in 1990, Colombia and Japan.

111
00:10:31,870 --> 00:10:33,460
‫Colombia and Japan.

112
00:10:35,370 --> 00:10:52,950
‫Had similar exports at around, let's say, 450 to five hundred and seventy million dollars in that

113
00:10:52,950 --> 00:10:53,470
‫year.

114
00:10:55,170 --> 00:11:00,120
‫On the other hand, a really good mix open that we can start with.

115
00:11:00,300 --> 00:11:09,270
‫On the other hand, Myanmar had zero sales of clothing, some using sales, because I think I'm using

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‫exports too much.

117
00:11:11,040 --> 00:11:19,170
‫Myanmar had zero sales of clothing, had zero sales of clothing that I could say had no.

118
00:11:20,850 --> 00:11:24,610
‫Had no sales of clothing at all.

119
00:11:25,530 --> 00:11:33,510
‫On the other hand, Myanmar had no sales of clothing at all over the next in the next 10 years, in

120
00:11:33,510 --> 00:11:39,000
‫the next 10 years to 2000, Myanmar's.

121
00:11:40,610 --> 00:11:42,170
‫Myanmar's figure.

122
00:11:43,480 --> 00:11:45,890
‫Rose, Myanmar.

123
00:11:46,060 --> 00:11:52,240
‫Sorry, apologies for my rights in that Myanmar's figure rose drastically.

124
00:11:53,910 --> 00:12:06,030
‫Rose drastically to 800 million dollars, let's say, from Colombia and Japan, which are very similar,

125
00:12:06,030 --> 00:12:17,490
‫around 520, let's say, of 800 million dollars, over two hundred and fifty million more than both

126
00:12:17,880 --> 00:12:20,010
‫Japan and Colombia.

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00:12:20,080 --> 00:12:21,980
‫OK, let's have a quick read through.

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00:12:21,990 --> 00:12:23,510
‫So we've done the first two years.

129
00:12:23,520 --> 00:12:25,800
‫I also need to describe 2011.

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00:12:26,700 --> 00:12:35,820
‫In 1990, Colombia and Japan had similar export at around 450 to hundred and seventy million dollars.

131
00:12:36,510 --> 00:12:39,790
‫On the other hand, Myanmar had no sales of clothing at all.

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00:12:40,200 --> 00:12:44,820
‫So that's 1990 down in the next year, in the next 10 years.

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00:12:45,030 --> 00:12:50,040
‫This is why it's important to read your writing back in the next 10 years to 2000.

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‫Myanmar's figure rose drastically.

135
00:12:53,370 --> 00:12:56,160
‫So I'm using these different features of language.

136
00:12:56,880 --> 00:13:05,010
‫In the next 10 years to 2000, Myanmar's figure rose drastically to 800 million dollars, over 250 more

137
00:13:05,010 --> 00:13:06,960
‫than both Japan and Colombia.

138
00:13:07,720 --> 00:13:10,890
‫And what do we see until 2011?

139
00:13:11,250 --> 00:13:17,450
‫So we can see that all countries saw some increase into 2011.

140
00:13:17,460 --> 00:13:22,590
‫So let's keep it simple and just write that onto 2010.

141
00:13:22,860 --> 00:13:26,250
‫Let's not start with onto all countries.

142
00:13:29,510 --> 00:13:31,490
‫So an increase.

143
00:13:32,810 --> 00:13:45,230
‫All countries saw an increase in an increase in exports in 2011, so I'm not being too specific there.

144
00:13:45,230 --> 00:13:49,130
‫I'm just saying that all the countries had some kind of increase.

145
00:13:49,400 --> 00:13:55,940
‫I think I've wrote quite a lot for my first detailed paragraph, and I could say that Myanmar was still

146
00:13:55,940 --> 00:13:56,660
‫the highest.

147
00:13:57,440 --> 00:14:09,860
‫All country saw an increase in exports in 2011, with Myanmar still the highest.

148
00:14:10,860 --> 00:14:19,110
‫In total sales, I'm going to say, instead of export, so that's my first three years, don't I'm now

149
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‫going to move on to describe 2012 to 2013.

150
00:14:25,020 --> 00:14:33,180
‫So there is actually quite a big change between these two years of 2011 and 2012, and that is that

151
00:14:33,510 --> 00:14:41,460
‫Myanmar's figure shoots all the way down to become the lowest once again, actually almost half or pretty

152
00:14:41,460 --> 00:14:47,770
‫much exactly half of what Colombia is producing in clothing that year.

153
00:14:47,790 --> 00:14:54,630
‫So Myanmar is at around 350 million dollars, whereas Colombia is at 700.

154
00:14:54,630 --> 00:15:00,270
‫So that's probably something that I can use using this language of halves and quarters or whatever you

155
00:15:00,270 --> 00:15:01,800
‫need to do for your report.

156
00:15:01,800 --> 00:15:05,780
‫It shows the examiner at different understanding of the language.

157
00:15:06,180 --> 00:15:10,320
‫So let's move on to detail paragraph two.

158
00:15:11,840 --> 00:15:25,370
‫Let's begin with Myanmar saw a massive downturn in clothing production and clothing export, let's say

159
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‫in 2012, falling to 300, falling to around 350 million dollars, half of Colombia's total sales.

160
00:15:46,080 --> 00:15:51,810
‫Which stands at seven hundred million dollars.

161
00:15:53,370 --> 00:16:00,450
‫And let's describe Japan in this year, so Japan decreased slightly.

162
00:16:02,330 --> 00:16:10,640
‫To around, let's say, five hundred and sixty million dollars to around five hundred and sixty million

163
00:16:10,640 --> 00:16:13,040
‫dollars million dollars.

164
00:16:13,070 --> 00:16:16,180
‫So I've described all the information about 2012.

165
00:16:16,370 --> 00:16:18,780
‫Let's move on to 2013.

166
00:16:19,250 --> 00:16:24,610
‫Now we can see that both Colombia and Japan see steady decreases.

167
00:16:24,770 --> 00:16:28,100
‫Where is Myanmar actually has another fluctuation.

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00:16:28,100 --> 00:16:30,560
‫So and Myanmar sees an increase.

169
00:16:31,370 --> 00:16:46,760
‫So we can describe this, let's say by 2013, both Colombia and Japan continued to see a decrease in

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00:16:46,760 --> 00:16:47,780
‫exports.

171
00:16:48,350 --> 00:16:53,720
‫Whereas another way to say, on the other hand, whereas Myanmar.

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00:16:55,970 --> 00:16:59,570
‫So a slight increase.

173
00:17:00,650 --> 00:17:13,460
‫A slight increase, although he was still the lowest producer or exporter of clothes in 2013.

174
00:17:14,240 --> 00:17:19,490
‫OK, I could go on to maybe describe, you know, that Colombia was the highest in the end and Japan

175
00:17:19,490 --> 00:17:21,470
‫was second and gives some more figures.

176
00:17:21,470 --> 00:17:27,880
‫But to be honest, I think I've gone into quite enough detail and have described lots of the main data.

177
00:17:28,130 --> 00:17:29,960
‫So let's have a quick read through.

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00:17:29,960 --> 00:17:30,590
‫Wants more.

179
00:17:32,060 --> 00:17:37,820
‫OK, so from the start, from my paraphrased introduction, and I can see from my checklist paraphrased

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00:17:37,820 --> 00:17:38,360
‫introduction.

181
00:17:38,360 --> 00:17:40,040
‫Yes, overview, yes.

182
00:17:40,040 --> 00:17:41,410
‫Detail paragraphs two.

183
00:17:41,420 --> 00:17:41,880
‫Yes, sir.

184
00:17:41,890 --> 00:17:43,910
‫I know that I've structured this in the right way.

185
00:17:44,150 --> 00:17:45,170
‫Clear grouping.

186
00:17:45,360 --> 00:17:49,130
‫This is my data, how I've grouped and described my data here.

187
00:17:49,130 --> 00:17:53,370
‫So I know the examiner is going to find this quite easy to follow.

188
00:17:53,660 --> 00:17:54,680
‫So let's read through.

189
00:17:55,250 --> 00:18:02,690
‫The given line graph shows the total export of clothing from three different countries over a time period

190
00:18:02,690 --> 00:18:04,280
‫of 13 years.

191
00:18:05,060 --> 00:18:12,680
‫Overall, we can see that Colombia and Japan didn't see such huge fluctuations in clothing exports in

192
00:18:12,680 --> 00:18:18,570
‫comparison to Myanmar, whose figures changed drastically over the time period.

193
00:18:18,590 --> 00:18:24,830
‫So I've got some interesting vocabulary here to describe the trends in the visual information.

194
00:18:25,910 --> 00:18:34,460
‫In 1990, Columbia and Japan had similar exports at around 450 to five hundred and seventy million dollars

195
00:18:34,670 --> 00:18:35,570
‫in that year.

196
00:18:35,580 --> 00:18:40,040
‫So I'm comparing these two countries and saying it's quite similar.

197
00:18:40,070 --> 00:18:41,300
‫There is some difference.

198
00:18:42,240 --> 00:18:47,720
‫Myanmar also on the other hand, Myanmar had no sales of clothing at all.

199
00:18:48,740 --> 00:18:57,170
‫In the next 10 years to 2000, Myanmar's figure rose drastically to eight hundred million dollars.

200
00:18:57,170 --> 00:19:06,950
‫Some moving on to this year now rose drastically to 800 million dollars, over 250 more than both Japan

201
00:19:06,950 --> 00:19:08,010
‫and Colombia.

202
00:19:08,030 --> 00:19:14,480
‫So comparing again making comparisons, all countries saw an increase.

203
00:19:14,480 --> 00:19:16,870
‫They need to just get rid of that.

204
00:19:16,880 --> 00:19:25,310
‫All countries saw an increase in exports in 2011, with Myanmar still the highest in sales, still the

205
00:19:25,310 --> 00:19:26,630
‫highest in total sales.

206
00:19:26,630 --> 00:19:30,940
‫So Myanmar is very high in 2011 for their exports.

207
00:19:30,950 --> 00:19:33,130
‫In fact, the highest on the whole line graph.

208
00:19:33,320 --> 00:19:34,970
‫That's something you could even mention.

209
00:19:34,970 --> 00:19:36,920
‫But I have chosen not to.

210
00:19:37,850 --> 00:19:38,360
‫Okay.

211
00:19:38,360 --> 00:19:50,000
‫Myanmar saw a massive downturn in clothing exports in 2012, falling to around 350 million dollars,

212
00:19:50,870 --> 00:20:00,030
‫over half, you could say half of Colombian's of Colombia's total sales, which sat at 700 million dollars.

213
00:20:00,050 --> 00:20:07,400
‫So comparing this part of the day to Japan decreased slightly to around 560 million dollars.

214
00:20:07,430 --> 00:20:09,140
‫So there's a slight decrease here.

215
00:20:09,980 --> 00:20:19,100
‫By 2013, both Colombia and Japan continued to see a decrease in exports, whereas Myanmar saw a slight

216
00:20:19,100 --> 00:20:25,190
‫increase, although it was still the lowest exporter of clothes in 2013.

217
00:20:27,590 --> 00:20:34,760
‫So that rounds up this task, one report for lying graphs that I feel that I have definitely include

218
00:20:35,030 --> 00:20:42,800
‫lots of information, specific information about this visual information, and I know that my features

219
00:20:42,800 --> 00:20:44,380
‫checklist is well covered.

220
00:20:44,390 --> 00:20:46,580
‫So the organization is there.

221
00:20:46,580 --> 00:20:48,200
‫It's easy to read.

222
00:20:48,200 --> 00:20:55,760
‫And I've got lots of specific information with some good language, such as where as an although and

223
00:20:55,910 --> 00:20:57,530
‫different kinds of things in here.

224
00:20:57,530 --> 00:20:59,750
‫So I'm pretty happy with this task.

225
00:20:59,750 --> 00:21:01,010
‫One report.

226
00:21:01,910 --> 00:21:03,800
‫See you in the next lesson.