![]() | Primary School Agriculture: Volume I: Pedagogy (GTZ, 1985, 144 p.) |
![]() | ![]() | Part II: Teaching methods |
![]() | ![]() | 3. Indoor activities |
![]() |
|
The data collected by the various teams during outdoor work must be collated before it can be of any use in further teaching. Teams come back with information about a few rows, a few stands, or one experimental block. But the scope of study is usually at least one plot or a whole experimental area. Before observations can be analyzed at this level, they have to be collated. This could be done by the whole class or by the teacher alone. At the end of an outdoor activity, the teacher could collect all the observation and record sheets and sort them out at home, as part of his lesson preparation, and present them in class the following day. On the other hand, he/she could do it with the class in a first follow-up lesson. In this case, the headings of the observation sheet would be used to design a big table on the central blackboard. The reporter or team leader of each team is then asked to read out his observations which the teacher or a pupil writes down. If a class is used to this procedure, the pupil reporting may well write down the observation himself.
Most of the time, the outdoor activities will have been organised row by row. Data should be compiled starting with row 1, row 2, row 3 and so on. This means that observations appear on the board in the order in which they occurred on the farm.
Since the data on the blackboard are going to be used by the whole class, it is vital for the blackboard display to be clear and tidy. If the exercise of arranging the data in order lasts too long, it can easily bore the pupils. This is yet another reason why pupils should not be asked to collect too much data at a time.
Since we advocate the active involvement of pupils and since sorting out the data in class provides another opportunity for reading and speaking, we are in favour of doing this as a class activity.
As soon as the display on the blackboard is complete, teacher and pupils copy it into their exercise books so that it can be referred to when the blackboard has to be used for something else in between lessons. If possible, a few problems should be worked on directly after the observations have been collated. It is for the teacher to asses whether further work on the results of the outdoor activities will retain the pupils' attention or whether they need something else in between.
1. Maize Growth with Different Methods of Weed Control
Date of Observation: |
15/5/1978 |
Time of the Day: |
10 a.m. |
No. of weeks after planting: |
9 |
Experimental Block No., Method of weed control |
Height of Maize Plants |
No. of cobs |
Weed growth |
General Remarks on Maize Growth |
(1) |
65, 70, 75 |
70 |
very dense, healthy, grass nearly as high as the maize |
maize plants and very poor, leaves pale, chocked by weeds |
no weeding |
72, 55, 60 |
| | |
no mulching |
61, 73, 65 |
| | |
|
70, 50, 52 |
| | |
|
64, 58, 60 |
| | |
|
71, 63, 66 |
| | |
|
58, 50 | |
| |
(2) weeding no mulching |
65, 85, 75 |
100 |
a few weeds growing between the rows and very close to some maize plants |
healthy, dark green leaves |
|
72, 75, 80 |
| | |
|
61, 73, 75 |
| | |
|
70, 82, 80 |
| | |
|
64, 68, 70 |
| | |
|
71, 63, 86 |
| | |
|
62, 60 | |
| |
(3) no weeding mulching |
60, 72, 77 |
95 |
a few healthy weeds where |
healthy, dark green leaves the mulch is thin |
|
72, 60, 62 |
| | |
|
63, 70, 65 |
| | |
|
70, 60, 62 |
| | |
|
64, 61, 60 |
| | |
|
71, 63, 66 |
| | |
|
62, 60 | |
| |
(4) weeding and mulching |
65, 85, 75 |
120 |
nearly no weeds growing |
very healthy and tall, good yield expected |
|
76, 77, 85 |
| | |
|
65, 73, 79 |
| | |
|
70, 82, 80 |
| | |
|
74, 78, 72 |
| | |
|
80, 78 | |
| |
Maize Growth with Different Methods
of Weed Control
2. The Development of Yams
Date of Observation: |
2/3/1978 |
Time of the Day: |
9:00 a.m. |
No. of weeks after planting: |
12 |
Table
3. The Maize Harvest - the Quality of Maize Cobs at Harvesting
Date of Observation: |
7/2/78 |
Time of Day: |
8:30-11:00 a.m. |
No. of weeks after planting: |
21 |
Row No. |
Cobs damaged by |
good Cobs |
(6) |
(7) | |||
|
(1) |
(2) |
(3) |
(4) Big |
(5) Small |
Cobs total |
Total weight |
1 |
14 |
22 |
1 |
10 |
10 |
57 |
4 kg |
2 |
10 |
44 |
- |
8 |
43 |
75 |
5.5 kg |
3 |
39 |
36 |
1 |
9 |
25 |
110 |
6 kg |
4 |
41 |
31 |
2 |
13 |
30 |
117 |
6.5 kg |
5 |
23 |
26 |
2 |
21 |
36 |
108 |
7 kg |
6 |
46 |
64 |
- |
14 |
27 |
151 |
8 kg |
7 |
48 |
74 |
1 |
- |
17 |
140 |
7 kg |
8 |
46 |
21 |
- |
7 |
14 |
88 |
6 kg |
9 |
49 |
55 |
- |
4 |
11 |
119 |
5 kg |
10 |
42 |
42 |
- |
14 |
20 |
118 |
7 kg |
11 |
34 |
64 |
1 |
11 |
28 |
138 |
7.5 kg |
12 |
60 |
19 |
1 |
9 |
16 |
165 |
9 kg |
13 |
63 |
80 |
3 |
13 |
14 |
173 |
10 kg |
14 |
48 |
85 |
3 |
8 |
8 |
152 |
7 kg |
15 |
26 |
107 |
3 |
17 |
21 |
174 |
12 kg |
16 |
15 |
70 |
- |
7 |
23 |
115 |
8 kg |
17 |
57 |
86 |
- |
11 |
14 |
168 |
7.5 kg |
18 |
49 |
39 |
- |
10 |
34 |
132 |
11.5 kg |
19 |
42 |
56 |
- |
30 |
25 |
153 |
7 kg |
20 |
32 |
76 |
3 |
3 |
30 |
144 |
7.5 kg |
21 |
43 |
110 |
1 |
9 |
34 |
197 |
10.5 kg |
22 |
31 |
49 |
- |
7 |
7 |
94 |
7 kg |
23 |
15 |
34 |
1 |
11 |
15 |
76 |
8.5 kg |
24 |
23 |
58 |
1 |
24 |
10 |
116 |
5.5 kg |
25 |
25 |
69 |
5 |
11 |
12 |
122 |
8.5 kg |
26 |
12 |
45 |
- |
9 |
3 |
69 |
5 kg |
|
933 |
1522 |
29 |
290 |
497 |
3271 |
194 kg |
3.2.2 Working
Through the Data
Marty though not all the observations are numbers. Working through them therefore means doing mathematical operations. This shows how simple calculations can help to answer questions arising from practical experience and activities. As we work through the three examples given in section 3.2.1 you will see for yourself how one could analyse the data resulting from observation and practical work on the school farm or on the farm of a local farmer.
Example 1: Maize Growth with Different Methods of Weed Control (see above)
1. Height of the Maize Plants:
- Calculate for each block separately the average height of the 20 sample maize plants and record, again for each block, the tallest and the shortest plant. The calculations involved are addition and division.
The Height of the Maize Plants
Block |
Average or |
Tallest |
Shortest |
(1) |
62.9 cm |
75 cm |
50 cm |
(2) |
69.6 cm |
86 cm |
61 cm |
(3) |
65.0 cm |
77 cm |
60 cm |
(4) |
75.7 cm |
85 cm |
65 cm |
Total |
68.3 cm |
86 cm |
50 cm |
2. Number of Cobs
Order the blocks according to the number of cobs growing, from lowest to highest. Is this order the same as the one obtained if you order the blocks according to the average height of the maize plants?
3. Weed Growth
There are no calculations to be done. Ask the teams which have observed the same blocks for more details: What kind of weeds were seen? What other weeds besides grasses were growing? What did the soil look like below the mulch?
4. General Remarks on Maize Growth
Here again there are no calculations needed. Ask the teams for more details like the thickness of the stalks, size and thickness of the cobs, signs of tassling, the growth of adventitious roots etc.
Example 2: The Development of Yams
1. Number of Sets Planted
- Calculate the total number of sets planted (simple addition).
2. Number of Sets Having Germinated
- Calculate the total number of sets which have germinated
(simple addition).
- Calculate the germination rate:
Total number of germinated sets x
100
Total
number of sets planted
- Is the germination rate the same for the whole farm? Calculate the germination rate for each row separately.
- Example:
row 1: (28 x 100)/34= 82.4 per
cent
row 4: (8 x 100)/38= 21.0 per cent
3. Type of Disease
What types of diseases were seen? Discuss them with the class. Ask for details: how did you recognize the various diseases reported? Correct errors or raise doubts and check on the spot if necessary.
- Calculate the total number of plants affected by the various
diseases (simple addition).
- Calculate the percentage of diseased plants for
each disease separately (division).
Example:
plants affected by mosaic disease: |
8 |
plants affected by rot: |
8 |
percentage of plants affected by mosaic disease: |
1.6 |
percentage of plants affected by rot: |
1.6 |
4. What the Yam Vines Look Like
- Calculate the number of destroyed or damaged vines. Since one yam plant may grow more than one vine, it does not make sense to calculate the percentage of yam plants with destroyed or damaged vines.
- Calculate the number of vines not yet trained and of vines poorly trained. Comparing it to the number of germinated yams gives a rough indication of how well the yam farm is being looked after.
5. Mulching
Assign teams to the rows where there was not enough mulching.
6. Remarks
Sort the remarks according to topics and whether they indicate good or poor growth. Re-write the short remarks as complete sentences. Are there any remarks showing that more farm care is needed?
Example 3: The Maize Harvest - The Quality of Maize Cobs at Harvesting (p. 65)
1. Number of Maize Cobs in Each Column (i.e. under each heading)
- Calculate the total number of cobs under each heading (7 simple additions).
- Add the totals for each heading of columns 1-5 (birds, weevils, smuts, big cobs, small cobs). The sum should be equal to the sum of column 6 (total number of cobs).
- Draw 4 graphs showing the number of cobs damaged by birds, the number of cobs damaged by weevils, the number of big cobs, and the total number of cobs row by row (for an example see the graphs in the complete sub-unit in Part III, p. 99). These graphs will show better than a table full of figures the distribution of the total yield and the damage throughout the farm.
2. Yield per Hectare
Calculate the yield per hectare (division).
3. The Amount of Damage Done
Relative figures, i.e. shares or proportions give a better idea of the damage done than the absolute figures calculated in 1.
Calculate the percentage of cobs damaged by birds and weevils.
Example:
cobs damaged by birds: (933 x 100)/3271 =
28.5%
cobs damaged by weevils: (1522 x 100)/3271 = 46.5%
- Calculate the percentage of damaged cobs (birds and weevils) for each row separately. This will answer the question whether roughly the same proportion of cobs,were attacked in each row or whether there are areas of the farm where the damage is particularly bad.
- Make graphs showing the percentages of damaged cobs row by row. This means two graphs.
4. Estimate of the Grain Lost due to Birds, and Weevils
Here the problem is less one of doing sums than of a sound estimation technique. It means reasoning out ways of assessing the losses due to the various maize pests. The reasoning might become quite involved, and the pupils might not be able to follow. The necessary examples have been provided in the sub-unit on the maize harvest. Teachers will have to judge for themselves whether their pupils can understand the reasoning behind such simple estimation techniques.
These few examples have shown that even with a restricted number of observations a lot of follow-up work can be done. Since it can be broken down into a number of simple tasks - mainly doing a lot of sums - these simple tasks should be assigned to the various teams organized for the outdoor activities.
In this way, everybody will be busy for a relatively short time after which the results of the data analysis will be reported by the different teams.
It should be clear that it is not possible to do all the data analysis in one lesson. It would not be desirable either. The sub-unit on the maize harvest (p. 99) shows how a subunit is structured according to topics of interest. Whenever the observations made during harvest could be useful, the class works through them. Where the observations do not provide answers, other sources (books, knowledgeable people) will help. Finally, there is nothing wrong with confessing one's ignorance.
- Even with a restricted number of observations a lot of follow-up work can be done. It would not be desirable to do all data analysis in one lesson.
- It would be wrong, however, to limit the follow-up work of an
outdoor activity to problems that may safely be solved by working through
data.
3.2.3 Arriving at
Conclusions
Conclusions from the data will always be based on some kind of comparison. The yield on one part of the farm will be higher than elsewhere, and we might find that a particular part has received more manure than the rest, and therefore we conclude that the high yield was due to manure. The damage done by birds is heaviest in the centre of the farm. We know that birds are easily scared away and conclude that they feel safest at the centre of the farm where they can take their time and eat up the maize.
- What is important in our work is that these conclusion be clearly explained. Pupils must know the reasoning by which a conclusion is drawn from the data.
- Conclusions and the way they were derived should therefore be put in writing so that at the end of a sub-unit there is a series of tentative conclusions about the topic under study.