Retention of knowledge in the preparation of fish pickle, fish wafers and fish soup powder for an experimental group of 20 fisherwomen selected from three fishing villages was studied. The knowledge retention immediately after exposure and also at intervals of 15 days and 30 days after exposure differed significantly

Kandoran, M.K.

Thiagarajan, R.

Aquatic Commons

R of owledge in Fish Processing 
Fish men 
R. THIAGARAJAN and M. K. KANDORAN 
Central Institute of Fisheries Technology, Cochin - 682 029 
Retention of knowledge in the preparation of fish pickle, fish wafers and fish soup 
powder for an experimental group of 20 fisherwomen selected from three fishing villages 
was studied. The knowledge retention immediately after exposure and also at intervals 
of 15 days and 30 days after exposure differed significantly. 
The effectiveness of any extension effort 
is to be judged in terms of its capabilities to 
transfer the instructional content in its fullest 
measure to the receipient to absorb the same 
without any loss and retain the same for a 
longer period by the receipient. 
Marks (1955) reported that most people 
retained W to 15 percent of what they had 
heard, 30 to 35 per cent of what they had 
seen, 50 per cent or more of what they had 
seen and heard and upto 90 per cent by parti-
cipating with the involvement of all senses. 
Baskaran (1968) reported that young and 
middle aged farmers retained slightly more 
knowledge as compared to the older groups. 
In respect of education, those who had higher 
level of education had shown a better res-
ponse to retention of knowledge. 
Materials and Methods 
An experimental group of 20 fisherwomen 
was constituted from three fishing villages, 
Azheekal, Fort Cochin and Kannamaly in 
Ernakulam District, Kerala. The group 
was exposed to three messages, namely, pre-
paration of fish pickles, fish wafers and fish 
soup powder. Their knowledge retention 
was measured immediately, 15 and 30 
days after exposure. 
Knowledge was measured with the help 
of well structured knowledge check list. 
Knowledge check list had 12 questions with 
multiple choice answers for all the three 
messages. One score was given for each 
correct answer. So the individual who had 
given correct answers for all questions could 
get 12 scores. As the experimental group 
had no knowledge regarding the fish pro-
cessing technology before exposure, their 
knowledge at the pre-exposure stage was 
considered as zero. 
The independent variables selected for the 
study were age, educational status, employ-
ment status of the family, annual income and 
size of the family. 
Knowledge retention, to the amount of 
information recalled by the individual, was 
measured as follows: 
Extent of knowledge retention 
Knowledge score obtained by the 
individual ~~----~-----~x 100 Total knowledge score 
Statistical techniques used 
The changes in knowledge at three differ-
ent stages were analysed using the Mcnemar 
test for the significance of changes (Siegal, 
1956). For testing the significance, a four 
fold Table was constructed as follows: 
After 
+ Before + A ---B--
-C-~---D---
The chi-square value for the above Table 
was calculated using the following formula 
[(A-D)-1 ] 
X 2 = A-D 
2 
with df=l 
The analysis of variance was also worked 
out. 
FISHERY TECHNOLOGY 
RETENTIVITY OF KNOWLEDGE IN FISH PROCESSING BY FISHERWOMEN 145 
Results and Discussion 
Knowledge change in fish processing techno-
logy immediately after exposure 
The Menemar test for the significance of 
changes was made to find out the change 
occurred in the knowledge immediately after 
exposure. 
Immediately after exposure 
+ 
x 2 = 18.05** 
Before + 0 0 **significant 
exposire at 1 % level 
0 20 
The calculated chi-square value was signi-
ficant showing that changes occurred in the 
knowledge of fish processing technology by 
the experimental group immediately after 
the exposure. From the four fold Table it 
could be seen that knowledge change occurred 
in the positive direction. It means that all 
the members of the experimental groups 
acquired the knowledge immediately after 
the exposure. As this is the starting point 
the extent of knowledge retention is consi-
dered as 100 %-
Knowledge change in fish processing techno-
logy at an interval of 15 days after exposure 
15th day after exposure 
+ 
Immediately + 8 5 xi= 6.125* 
after * signifi-
exposure cant at 
7 0 5 % level 
The calculated chi-square value was signi-
ficant showing that there was a significant 
change in the knowledge level of fish pro-
cessing technology at an interval of 15 days 
after exposure. From the four fold Table 
it could be seen that the changes had occurred 
in the negative direction. Here 40 per cent 
of the fisherwomen showed knowledge redu-
ction cent from the point of was 13.75 per 
knowledge reduction immediately after expo-
sure to 15th day after exposure. 
Knowledge change in fish processing techno-
logy during the intervalfrom 15th to 30th day 
after the exposure 
Vol. 26, 1989 
15th day 
after 
exposure 
30th day after exposure 
+ X2 = 8.1*:;e 
-------
+ 10 
5 
5 
0 
**significant 
at1 % 
level 
Here also the chi-square value was signi-
ficant which showed that the knowledge 
change had occurred from 15th day to 30th 
day after the exposure. 50 per cent of 
the fisherwomen showed knowledge reduction 
Knowledge change in fish processing techno-
logy at an interval of one month after exposure 
30th day after exposure 
+ x2 = 9.1** 
Immediately + 11 5 ** significant 
-------
after at 1 % 
exposure level 
4 0 
The significant chi-square value shows 
that there was a significant change from 
immediate exposure to 30th day of exposure. 
Here 55 per cent of fisherwomen showed 
knowledge reduction in fish processing tech-
nology. 
Relative reduction of knowledge in fish pro-
cessing technology 
Analysis of variance technique was emplo-
yed to find out the difference in knowledge 
reduction from immediately after exposure 
to 15th day after exposure and from 15th 
day after exposure to 30th day after exposure. 
Table 1. Analysis of variance 
Source Df SS MSS F 
Knowledge 
reduction 1 2.025 2.025 9.6797** 
Error 38 7.950 0.2092 
Total 39 9.975 
** significant at 1 % level 
The significant value of 'F' (Table l) shows 
that the knowledge reduction from immedia-
tely after exposure to 15th day after exposure 
and from 15th day after exposure to 30th 
day after exposure significantly differed. 
146 R. THIAGARAJAN AND M. K. KANDORAN 
Mean values for knowledge 
The mean values from Table 2 show that 
the knowledge reduction was more from 
immediately after exposure to 15th day after 
exposure (M2) than from 15th day after 
exposure to 30th day after exposure (Ml). 
Table 2. Mean values for knowledge 
Intervals Mean 
values 
Immediately after exposure to 
15th day after exposure (M2) 1.65 
From 15th day after exposure to 
30th day after exposure (Ml) 1.35 
The Mcnemar test for the significance of 
changes was worked out to find the changes 
in the knowledge reduction. 
From 15th day after exposure to 
30th day after exposure 
Immediately 
after 
exposure 
15th day 
after 
exposure 
+ 
7 
10 
+ 
2 
1 
x2 =4.5* 
* signi:fican t 
at 5% 
level 
The significant value of chi-square showed 
that there was a significant change in the 
knowledge reduction during the two intervals. 
Here 35 per cent of fi.sherwomen showed 
knowledge reduction. 
The extent of knowledge reduction by .fisher-
women 
The extent of knowledge reduction by 
fisherwomen immediately, at 15th day and 
at 30th day after exposure is presented in 
Table3. 
Table 3. The extent of knowledge reduction 
by fisherwomen 
Intervals 
Immediately after exposure 
15th day after exposure 
30th day after exposure 
Extent of know-
ledge reduction 
(percentage) 
00.00 
13.75 
25.00 
From 15th day after exposure to 
30th day after exposure 11.25 
From Table 3 it could be seen that the 
knowledge reduction was maximum (25 per 
cent) at 30th day after exposure. 
Relative retention of knowledge in fish pro-
cessing technology immediately, at 15th and 
30 th day after exposure 
Analysis of variance technique was emplo-
yed to find out the significant difference 
in knowledge retention in fish processing 
technology immediately, 15th and 30th day 
after exposure (Table 4). 
Table 4. Analysis of variance 
Source DF SS MSS F 
Knowledge 
Error 
Total 
2 65.7 32.85 12.06** 
57 155.3 2.72 
59 221.0 
** significant at l % level 
From Table 4 it could be seen that the 
knowledge retention significantly differed 
among themselves. 
Table 5. Mean values for the knowledge 
retention immediately, 15th and 
30th day after exposure 
Intervals 
Immediately after 
exposure (M3) 
15th day after 
exposure (M2) 
30th day after 
exposure (Ml) 
Mean 
values 
12.00 
10.35 
9.00 
Critical 
difference 
1.2033 
From Table 5 it could be seen that the 
knowledge retention was maximum imme-
diately after exposure (M3) followed by that 
at 15th day of exposure (M2) and that at 
30th day of exposure (Ml). The calculated 
critical difference 1.2033 confirms the above 
results. 
Socio-economic characteristics of fisherwomen 
The mean and standard deviation for the 
socio-economic variables of the :fisherwomen 
are presented in Table 6. 
FISHERY TECHNOLOGY 
RETENTIVITY OF KNOWLEDGE IN FISH PROCESSING BY FISHERWOMEN 147 
Table 6. Mean and standard deviation for 
the socio-economic variables (n-20) 
SL Variables Mean Standard 
no. deviation 
X1 Age 23.45 5.58 
X2 Education 2.90 0.55 
X3 Size of the 
family 6.65 2.28 
Xi Employment 
status of the 
family 2.65 0.85 
X5 Annualincome 1467.00 565.69 
Y1 Knowledge 
retention 10.53 1.58 
Y2 Knowledge 
reduction 2.55 0.76 
Table 6 shows that average age of fisher-
women in the experimental group was 23, 
had education on the average up to high 
school level and the size of the fisherwomen 
family on the average was 6-7 members. 
Two to three persons were employed in each 
:fisherwomen family. The average annual 
income of the fisherwomen family was Rs. 
1500/-. 
Matrix of correlation for the selected socio-
economic variables 
The matrix of correlation was worked out 
for the socio-economic variables selected 
and the same is presented in Table 7. 
Table 7. Matrix of correlation for the sele-
cted socio-economic variables 
X2 Xs X4 X55 
X1 -0.45* 0.0006 0.23 0.21 
NS NS NS 
X2 0.013 0.38* 0.34 
NS NS 
Xs 0.75** 0.57*'~ 
Xi 0.47* 
NS = not significant; * significant at 5 % 
level; ** significant at l % level. 
A perusal of Table 7 indicates that age 
and education showed negative and signi-
ficant association, whereas education and 
employment status of the family, size and 
employment status of the family, size and 
Vol. 26, 1989 
annual income of the family showed positive 
and significant relation. From these results 
it could be inferred that more number of 
persons were employed in highly educated 
and larger sized family. It is natural that 
large family with more persons employed 
had high annual income. 
Correlation of the selected socio-economic 
variables with knowledge retention and know-
ledge reduction of the fisherwomen 
The correlation co-efficient for the selected 
socio-economic variables with knowledge 
retention and knowledge reduction are pre-
sented in Table 8. 
Table 8. Correlation co-efficients (n-20) 
St Variables 
no. 
X 1 Age 
X 2 Education 
X 3 Size of family 
X 4 Employment 
status of the 
family 
X 6 Annual 
income 
Knowledge 
retention 
(Y1) 
-0.54** 
0.65** 
0.11 NS 
0.28 NS 
0.38* 
Knowledge 
reduction 
(Y") 
0.21 NS 
O.H NS 
0.25 NS 
0.34 NS 
-0.36* 
NS = not significant; * significant at 5~~ 
level; ** significant at l % level 
From Table 8 it could be seen that the edu-
cation and annual income showed positive 
and significant relationship with knowledge 
retention. The highly educated women 
retained maximum knowledge when com-
pared to the low educated women. The 
age had negative and significant relationship 
with knowledge retention. This shows that 
the young women retained more knowledge 
than old women. The income showed nega-
tive and significant relationship with know-
ledge reduction. 
The multile regression equation was 
Y1 = 9.25 + 0.10 X1 + 1.09 X 2+ 0.24X3 
+ 0.814 X 4 + 0.0075 X& 
Y 2 =4.56 + 0.038 Xu+ O.H9 X 2 + 0.052X3 
0.35 X4 + 0.00034 X5 
148 
The R 2 calculated for knowledge reten-
tion was 0.62 and for knowledge reduction 
it was 0.25. The five selected socio-economic 
variables explained 62 per cent of the varia-
tion for knowledge retention and 25 per cent 
of the variation for knowledge reduction. 
The authors are grateful to Shri M.R. Nair, Dire-
ctor, Central Institute of Fisheries Technology, 
Cochin for his kind permission to publish this paper. 
They are also thankful to Shri H. Krishna Iyer, 
Head of Extension, Information and Statistics Divi-
sion of CIFT for helping in the statistical analysis 
of data and Shri K.K. Balachandran, Shri P.K. Vijaya 
and Smt. R. Thankamma, Scientists of CIFT for 
providing facilities to collect the data during the rele-
vant training programme. 
R. THIAGARAJAN AND M.K. KANDORAN 
References 
Baskaran, K. (l 968) Ind. J. Extn. Edn. 
1 (3 & 4), 28 
Marks, L.G. (1955) "The eyes have it but 
each sense plays a part", Paris, Paris, 
review, Europian Productivity Agency, 
CEEC 
Siegel Sidney (1956) Non-parametric Sta-
tistics for the Behavioural Sciences, 
Mc Graw-Hill Book Company, New 
York 
FISHERY TECHNOLOGY 


Relative retentivity of knowledge in fish processing by fisherwomen

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Relative retentivity of knowledge in fish processing by fisherwomen

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