# Usefulness of farm women training programmes in livelihood security

Nusrat Sultana, Abdulla Al-Asif, Md. Mehadi Imam Dihider, S M Ahsan, Faruki Shabia Maraj

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Nusrat Sultana, Abdulla Al-Asif, Md. Mehadi Imam Dihider, S M Ahsan, Faruki Shabia Maraj. Usefulness of farm women training programmes in livelihood security. International Journal of Business, Social and Scientific Research, 2015, 4 (1), pp.13-24. hal-05025943

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USEFULNESS OF FARM WOMEN TRAINING PROGRAMMES IN
LIVELIHOOD SECURITY

Nusrat Sultana<fnref n="1" />, Abdulla-Al-Asif<fnref n="2" />*, Md. Mehadi Imam Dihider<fnref n="3" />, S.M. Ahsan<fnref n="4" />, Faruki Shabia Maraj<fnref n="5" />

Nusrat Sultana, Abdulla-Al-Asif, Md. Mehadi Imam Dihider, S.M. Ahsan, Faruki Shabia Maraj (2015) Usefulness of Farm Women Training Programmes in Livelihood Security. Int. J. Bus. Soc. Sci. Res. 4(1): 13-24. Retrieve from http://www.ijbssr.com/currentissueview/14013121

Received Date: 05/09/2015

Acceptance Date: 05/10/2015

Published Date: 05/10/2015

Abstract

The study was conducted at sadar upazila of Patuakhali district to determine the extent of usefulness of farm women training program in livelihood security and explore relationships with their 11 selected characteristics namely Age, Education, Family size, Family education, Training experience, Agricultural knowledge, Family co-operation, Annual family income, Decision making ability, Communication and Fatalism. Data were collected from 106 rural farm women (housewives) using pre-tested interview schedule during 10 July, 2014 to 20 August, 2014. Findings of the study indicated that the usefulness scores of women ranged from 25 to 62 with a mean 38.45 and standard deviation 11.21 against the possible range of 0 to 75. and 45.28 percent of the women had medium, 34.91 percent of them had low and 19.81 percent of the women had high usefulness of training programmes. The coefficient of correlation showed that out of 11 selected characteristics of the farm women, age had negative significant relationship, and rest of ten characteristics had positive significant relationships with usefulness of training programmes in livelihood security. Medium problem faced by the majority farm women in participating training programmes.

**Key words:** Women Training Program, Livelihood Security.

Introduction

The half of the population of the world is consist of women and their contribution to the overall
development. But their capable participation in various activities is not the same as men's even today.
Any society of a nation can't develop without the active participation of women. It saidthat the hands
that rock the cradle can't rule the world. The fact is that most of the women's domestic role is combined
with financial activities and application of their expertise and labor to earn the extra income for the
family, which makes the difference between a reasonably better lives and eliminate family poverty.
Women contributing two-thirds of world's work hours. But she wages only one-third of the total income
and owns less than one-tenth of the final wage. Among total Bangladesh population of 152.51 million,
women constitute 75.13 million. Women constitute nearly fifty percent of population, perform two-thirds
of the work and produce fifty percent of food commodities consumed by the country. They earn one
third of remuneration and own ten percent of the property or wealth of the country. This scenario shows
that the financial status of women is in worse condition and in the context of Bangladesh this situation is
very bad. Women are regarded as the "better half" of the society. But the reality in our society is still
male dominated and women are not treated as equal both inside and outside the four walls of the house.
In fact, they are treated as less strength and reliableto men. In the Bangladeshi context women enjoy an
unfavorable status in society. The actual target of economic development of a country is to increase the
income and quality of life of its population. Rural development, particularly agrarian advancement in
Bangladesh is no exception to this and it is an important issue that development activities should be
equally participated by women and men. Undoubtedly, access of rural women to decision making
provides various benefits of development not only to the family but also to the society through which
people seek a better livelihood in the rural areas. The major aim of the government policymakers of
Bangladesh is to raise family income and ensure the better life through participatory and harmonious
effort of the exploited people, who are considered as target people. The activities of women are mainly
restricted within the household especially in taking care offamily membersand kids, maintaining homes
and preparing and serving food to family members. In addition the rural women also serve themselves in

<footnote>*Corresponding Authors Email: jessoreboyhemel@gmail.com</footnote>

<footnote n="1">1. Department of Agricultural Extension and Rural Development, Patuakhali Science and Technology University Dumki, Patuakhali.</footnote>

<footnote n="2">2. Department of Aquaculture, Faculty of Fisheries, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.</footnote>

<footnote n="3">3. Department of Microbiology and Hygiene, Faculty of Veterinary, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.</footnote>

<footnote n="4">4. Department of Horticulture, Faculty of Agriculture, Patuakhali Science and Technology University, Bangladesh.</footnote>

<footnote n="5">5. Faculty of Agriculture, Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bangladesh.</footnote>
agricultural and non-agricultural activities within the homestead (Halim, 1985). Women are the disadvantaged class of the society. Different organizations are trying to develop the overall sphere of community at grass root level by providing different trainings to women and mainstreaming them in development program. A large number of GO and NGOs are working in rural areas in different development program such as homestead gardening program, goat rearing program and other income generating activities. Different GO and NGOs reported that they have succeeded in their field, enabling a large number of women in taking part in their development programs. But few organizations investigate and report about the extent of usefulness of these training programmes for which these are designed. For true development of rural women, organizations have to find out the level of usefulness of training programmes offered. The main focus of the study was to determine and revealed the usefulness of farm women training programmes in livelihood security. The present study is conducted to determine the nature and extent of usefulness of the farm women training programmes of GOs and NGOs in livelihood security as perceived by them and describe some selected characteristics of farm women. The selected characteristics are age, annual family income, decision making ability, communication exposure, education, family size, family education, training exposure, agricultural knowledge, family co-operation, and fatalism. This study also revealed the relationship between each of the selected characteristics of the rural women and their usefulness of farm training programmes in livelihood security and described the problems faced in participating training programmes by farm women.

## Methodology

The study conducted in Sadar upazila of Patuakhali district during 10 July 2014 to 20 August 2014, where different GOs and NGOs conducted a number of training. The total number of sample was 106. In the study, both dependent and independent variables were taken to measure the rural women's livelihood security. The independent variables were age, education, family size, family income, agricultural knowledge, family co-operation, and annual family income. Decision making ability, Communication, Fatalism, etc., and the dependent variable was Usefulness of farm women training programmes in livelihood security.

## Measurement of usefulness of farm women training programmes in livelihood security

Usefulness of farm women training programmes in livelihood security was viewed in terms of five assets of livelihood: (a) human capital (b) natural capital (c) economic capital (d) social capital (e) physical capital.

A comprehensive list of indicators of livelihood security under the above mentioned 5 livelihood assets which were expected to be improved as a result of receiving training by the farm women was prepared. The indicators were collected from the objectives of the training programmes, consultations with experts, training providers, supervisory committee, and literature review. After that five indicators were retained under each of the five assets of livelihood. Thus, a total of 25 indicators reflecting livelihood security were finally selected for the scale.

Usefulness of farm women training programmes in livelihood security of a respondent was measured by computing usefulness of farm women training programmes score using of 25 indicators of livelihood security under 5 livelihood assets which were expected to be improved as a result of receiving training by the respondent. A respondent was asked to indicate her opinion on the extent of level of usefulness against each of the indicator along with a 4-point continuum "high", "medium", "low", and "not at all", while weights assigned to those responses were 3, 2, 1, and 0 respectively.

<figure><img src="image_3.png" /><figcaption>Fig. 1: Red circle showing Study area.
(Source: mapofbangladesh.blogspot.com)</figcaption></figure>

## Problems faced by farm women in participating training programmes

Problem faced in participating in training program by the respondent was measured by using eight different problems. The problems had been selected based on the problem faced in participating in training program. The women were requested to indicate their opinion towards the problem faced in participating in training program, a four point scale such as "high", "medium", "low", not at all " were used in this purpose and weights were assigned to each of the scale responses as 3 for "high", 2 for "medium", 1 for "low" and 0 for "not at all". The possible score could range from 0 to 24 where 0 indicating no problem and 24 indicating higher problem in income generating activities.

<figure><img src="image_4.png" /></figure>
## Statement of hypotheses

The following hypotheses were formulated to explore the relationships between the dependent and independent variables. The research hypothesis for this study was: "There is a relationship between each of age, education, farming experience, farm size, annual income, training received, communication exposure, cosmopoliteness, agricultural knowledge and fatalism with usefulness of farm women training programmes in livelihood security".

## Data Collection

During the interview, the researcher paid utmost care in collecting data by avoiding external interference. Extension personnel helped the investigator to collect data from the women respondent without any obstacle. Thus, the researcher did not face any difficulty to establish rapport during data collection. Appreciable cooperation was received from almost all the respondents during interview. The pretest was done from 6th July to 14th July 2014. Final data collection was done during 20th July to 2 September, 2014.

## Data Processing and Analyses

Data collected for the study were systematically recorded, edited, arranged, compiled, tabulated, computerized and analyzed in accordance with the objectives of the study. The computer software like Microsoft Excels and SPSS were used to analyze the data. The following statistical treatment were used to describe, represent and in explaining the relationships among variable included in the study.

## Results

### Characteristics of the Rural Women

#### Age

The age of the farm women ranged from 22 to 65 years with a mean 45.42 and standard deviation of 8.11. For the purpose of analysis, the respondents were classified into three categories as young aged (up to 35 years), middle aged (36 to 50 years) and old aged (above 50 years) shown in table 1.

<table><caption>**Table 1.** Distribution of the farm women according to their age</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Young age (up to 35 years)</td><td>40</td><td>37.74</td><td rowspan="3">45.42</td><td rowspan="3">8.11</td></tr><tr><td>Middle age (36 – 50 years)</td><td>47</td><td>44.34</td></tr><tr><td>Old age (above 50 years)</td><td>19</td><td>19.92</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

#### Education

The education scores of the women ranged from 0 to 14 with a mean of 4.11 and standard deviation 3.23. Based on the educational scores, the women were classified into four categories, "Illiterate and can sign only" (0 to .5), "primary education" (1 to 5), "secondary education" (6 to 10), "above secondary education" (above 10) as shown in table 2.

<table><caption>**Table 2.** Distribution of the women according to their education</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Illiterate and Can sign only (0 and .5)</td><td>08</td><td>07.55</td><td rowspan="4">4.11</td><td rowspan="4">3.23</td></tr><tr><td>Primary education (1-5)</td><td>60</td><td>56.60</td></tr><tr><td>Secondary education (6 – 10)</td><td>35</td><td>33.02</td></tr><tr><td>Above secondary education (above 10)</td><td>03</td><td>02.83</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

#### Family size

The family size scores of women ranged from 2 to 12 with a mean 6.42 and standard deviation 2.07. Based on the family size scores, the women were classified into three categories, "small family size" (2 to 4), "medium family size", (5 to 7), "large family size" (8 to 11). The distribution of women according to their family size is shown in table 3.

<figure><img src="image_5.png" /></figure>
<table><caption>**Table 3.** Distribution of the women according to their family size</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Small family size (2-4)</td><td>39</td><td>36.79</td><td rowspan="3">6.42</td><td rowspan="3">2.07</td></tr><tr><td>Medium family size (5-7)</td><td>53</td><td>50.00</td></tr><tr><td>Large family size (8-11)</td><td>14</td><td>13.21</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

## Family education

The family education of the farm women ranged from .1 to Tk. 12. The mean and standard deviation were 6.45 and 2.86. The women were classified into three groups based on their family education score as follows. These are, low family education (0.1 – 5.0), medium family education (5.01-10.01) and high family education (above 10.01). The distribution of the respondents based on family education is shown in the table 4.

<table><caption>**Table 4.** Distribution of the women according to their family education</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low family education</td><td>38</td><td>35.85</td><td rowspan="3">6.45</td><td rowspan="3">2.86.</td></tr><tr><td>Medium family education</td><td>47</td><td>44.34</td></tr><tr><td>High family education</td><td>21</td><td>19.81</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

## Training exposure

The training exposure scores of the women ranged from 15 to 30 with the mean and standard deviation being 19.68 and 3.66 respectively. Based on their training exposure scores, the women were grouped into four categories as, “low training exposure” (15-20), “moderate training exposure” (21-25), and “long training exposure” (above 25). The distribution of the women according to training exposure is shown in the following table 5.

<table><caption>**Table 5.** Distribution of the women according to their training exposure</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low training exposure (1-3)</td><td>37</td><td>34.91</td><td rowspan="3">19.68</td><td rowspan="3">3.66</td></tr><tr><td>Medium training exposure (4-6)</td><td>44</td><td>41.51</td></tr><tr><td>Long training exposure (above 6)</td><td>25</td><td>23.58</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

## Family co-operation

The observed family co-operation scores of the farm women ranged from 4 to 24 with an average of 16.44 and a standard deviation of 3.04 against the possible range of 0 to 30. On the basis of their family co-operation scores, the farmers were classified into four categories “low family co-operation” (up to 11), “medium family co-operation” (11-18) and “high family co-operation” (above 18). The distribution of the farmers according to their family co-operation scores is shown in table 6.

<table><caption>**Table 6.** Distribution of farmers according to family co-operation</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Farmers</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low family co-operation</td><td>21</td><td>19.81</td><td rowspan="3">16.44</td><td rowspan="3">3.04</td></tr><tr><td>Medium family co-operation</td><td>62</td><td>58.49</td></tr><tr><td>High family co-operation</td><td>23</td><td>21.70</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

## Agricultural knowledge

The observed agricultural knowledge scores of the farm women ranged from 12 to 33 with an average of 22.22 and a standard deviation of 4.84 against the possible range of 0 to 40. On the basis of their scores, the respondents were classified into three categories: “Low agricultural knowledge” (12 to 19), “Medium agricultural knowledge” (20-27), and “High agricultural knowledge” (above 27). The distribution of the farm women according to their agricultural knowledge is shown in table 7.

<figure><img src="image_6.png" /></figure>
<table><caption>**Table 7.** Distribution of farmers according to agricultural knowledge</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low agricultural knowledge</td><td>36</td><td>33.96</td><td rowspan="3">22.22</td><td rowspan="3">4.84</td></tr><tr><td>Medium agricultural knowledge</td><td>42</td><td>39.62</td></tr><tr><td>High agricultural knowledge</td><td>28</td><td>26.42</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

**Annual family income**

Annual family income score of the respondents ranged from 63.11 - 303.23 and the average was 82.34 with a standard deviation of 48.35. According to the annual income of the women, they were classified in to three categories viz. low annual income (up to 143), medium annual income (above 143 to 223) and high annual income (above 223) table 8.

<table><caption>**Table 8.** Distribution of the women according to their annual family income</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low annual family income</td><td>55</td><td>51.89</td><td rowspan="3">82.34</td><td rowspan="3">48.35</td></tr><tr><td>Medium annual family income</td><td>32</td><td>30.19</td></tr><tr><td>High annual income</td><td>19</td><td>17.92</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

**Decision-making ability**

The decision-making ability scores farm women ranged from 9 to 18 with a mean 15.56 and standard deviation 3.26. Based on the decision-making scores, the women were classified into three categories, “low decision-making”(9 to 12), “medium decision-making”, (13 to 16), “high decision-making” (16 to 18). The distribution of women according to their decision-making is shown in following table 9.

<table><caption>**Table 9.** Distribution of the women according to their decision-making ability</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low decision-making</td><td>27</td><td>25.47</td><td rowspan="3">15.56</td><td rowspan="3">3.26</td></tr><tr><td>Medium decision-making</td><td>45</td><td>42.45</td></tr><tr><td>High decision-making</td><td>34</td><td>32.08</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

**Communication exposure**

The communication exposure scores of the women ranged from 21 to 63 against the possible range of 0 to 84. The mean and standard deviation were 27.8 and 12.8 respectively. Based on observed communication exposure scores, the women were classified into three categories viz. “low communication exposure” (21–35), “medium communication exposure” (36 – 50), and “high communication exposure” (above 50). The distribution of women based on the scores is shown in the following table 10.

<table><caption>**Table 10.** Distribution of the women according to their communication exposure</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low communication exposure</td><td>36</td><td>33.96</td><td rowspan="3">17.8</td><td rowspan="3">12.8</td></tr><tr><td>Medium communication exposure</td><td>44</td><td>41.51</td></tr><tr><td>High communication exposure</td><td>26</td><td>24.53</td></tr><tr><td>Total</td><td>106</td><td>100.0</td><td></td><td></td></tr></tbody></table>

**Fatalism**

The fatalism scores of women ranged from 19 to 36 against 8 to 40 with a mean 26.12 and standard deviation 7.33. Based on the fatalism scores, the women were classified into three categories, “low fatalism” (19 to 24), “medium fatalism”, (25 to 30), and “high fatalism” (31 to 36). The distribution of women according to their fatalism is shown in following table 11.

<figure><img src="image_7.png" /></figure>
<table><caption>**Table 11.** Distribution of the women according to their fatalism</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low fatalism (18 to 24)</td><td>26</td><td>24.53</td><td rowspan="3">28.22</td><td rowspan="3">3.84</td></tr><tr><td>Medium fatalism (25 to 30)</td><td>45</td><td>42.45</td></tr><tr><td>High fatalism (31 to 36)</td><td>35</td><td>33.02</td></tr><tr><td>Total</td><td>105</td><td>100</td><td></td><td></td></tr></tbody></table>

## Usefulness of the farm women training programmes

The usefulness scores of women ranged from 25 to 62 with a mean 38.45 and standard deviation 11.21 against the possible range of 0 to 75. Based on the usefulness scores, the women were classified into three categories, "low usefulness" (25 to 37), "medium usefulness", (38 to 50), "high usefulness" (above 50). The distribution of women according to their usefulness is shown in following table 12.

<table><caption>**Table 12.** Distribution of the women according to their usefulness</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low usefulness</td><td>37</td><td>34.91</td><td rowspan="3">38.45</td><td rowspan="3">11.21</td></tr><tr><td>Medium usefulness</td><td>48</td><td>45.28</td></tr><tr><td>High usefulness</td><td>21</td><td>19.81</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

Usefulness Index (UI) was computed with the aspects, having better understanding regarding women's usefulness. The computed UI ranged from 94 to 220 which were arranged in rank order according to SMI as shown in table 13.

<table><caption>**Table 13.** Rank order of usefulness of livelihood security indicators</caption><thead><tr><th rowspan="2">aspects of livelihood</th><th colspan="4">Extent of usefulness</th><th rowspan="2">UI</th><th rowspan="2">Rank Order</th></tr><tr><th>High</th><th>Medium</th><th>Low</th><th>Not at all</th></tr></thead><tbody><tr><td>Human capital</td><td>31</td><td>60</td><td>10</td><td>5</td><td>220</td><td>1</td></tr><tr><td>Social capital</td><td>16</td><td>75</td><td>10</td><td>5</td><td>205</td><td>2</td></tr><tr><td>Physical capital</td><td>8</td><td>5</td><td>72</td><td>21</td><td>103</td><td>4</td></tr><tr><td>Natural capital</td><td>11</td><td>15</td><td>34</td><td>46</td><td>94</td><td>5</td></tr><tr><td>Economic capital</td><td>21</td><td>45</td><td>40</td><td>0</td><td>190</td><td>3</td></tr></tbody></table>

Table shows that human capital ranked 1st and then social capital as 2nd and economic capital got 3rd position. The physical capital ranked 4th and natural capital ranked 5th.

## Relationship between the Selected Characteristics of the Farm Women and their usefulness of training programmes

Pearson's Product Moment Co-efficient of Correlation (r) was computed in order to explore the relationship between the selected characteristics of the rural women and their usefulness of training programmes. The relationship between the dependent and independent variables has been presented in following table 14.

<table><caption>**Table 14.** Relationship between the selected characteristics of the rural women and their usefulness of training programmes</caption><thead><tr><th>Dependent Variable</th><th>Independent Variables</th><th>Co-efficient of correlation (r)</th></tr></thead><tbody><tr><td rowspan="10">Usefulness of training programmes</td><td>Age</td><td>-.260**</td></tr><tr><td>Education</td><td>.206*</td></tr><tr><td>Family size</td><td>.044</td></tr><tr><td>Family education</td><td>-.083</td></tr><tr><td>Training exposure</td><td>.301**</td></tr><tr><td>Agricultural knowledge</td><td>.027</td></tr><tr><td>Family co-operation</td><td>.195*</td></tr><tr><td>Annual family income</td><td>.023</td></tr><tr><td>Decision making ability</td><td>.103</td></tr><tr><td>Communication exposure</td><td>.297**</td></tr><tr><td>Fatalism</td><td>.012</td></tr></tbody></table>

<figure><img src="image_8.png" /></figure>

<footnote>*Significant at .05 percent level of probability (.176 at df 104)</footnote>

<footnote>** Significant at .01 percent level of probability (.230 at df 230)</footnote>
## Age and usefulness

The relationship between age of the farm women and their usefulness of training programmes was determined by testing the following null hypothesis ‘There is no relationship between age of farm women and their usefulness of training programmes in livelihood security’.

The calculated value of the coefficient of correlation between the concerned variables was found to be -.260 as shown in the Table 14. The following observations were made:

* The computed value of ‘r’ (r=-.260) was found to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability.

* The null hypothesis was rejected.

* The relationship between the concerned variables was significant negatively.

## Education and usefulness

The relationship between education of the farm women and their usefulness of training programmes in livelihood security was determined by testing the following null hypothesis ‘There is no relationship between education of farm women and their usefulness of training programmes in livelihood security’.

The calculated value of the coefficient of correlation between the concerned variables was found to be .206 as shown in the Table 14. The following observations were made:

* The computed value of ‘r’ (r=.206) was found to be larger than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis was rejected.

* The relationship between the concerned variables was significant.

* The relationship showed positive trend of the women.

## Family size and usefulness

The relationship between family size the farm women and their usefulness of training programmes was determined by testing the following null hypothesis ‘There is no relationship between family size of farm women and their usefulness of training programmes in livelihood security’.

The calculated value of the coefficient of correlation between the concerned variables was found to be .044 as shown in the Table 14. The following observations were made:

* The calculated value of the coefficient of correlation between the concerned variables was found to be .044 which is smaller than the tabulated value (r=.176) with 104 degrees of freedom.

* The null hypothesis could not be rejected

* The relationship was not significant.

## Family education and usefulness

The relationship between family education the farm women and their usefulness of training programmes was determined by testing the following null hypothesis ‘There is no relationship between family education of farm women and their usefulness of training programmes in livelihood security’.

The calculated value of the coefficient of correlation between the concerned variables was found to be .083 as shown in the Table 14. The following observations were made:

* The calculated value of the coefficient of correlation between the concerned variables was found to be .083 which is smaller than the tabulated value (r=.176) with 104 degrees of freedom at .05 level of probability.

* The null hypothesis could not be rejected

* The calculated value of ‘r’ (r=.083) was not significant

## Training exposure and usefulness

The relationship between training exposure of the farm women and their usefulness of training programmes in livelihood security was determined by testing the following null hypothesis ‘There is no relationship between training exposure of farm women and their usefulness of training programmes in livelihood security’.

The calculated value of the coefficient of correlation between the concerned variables was found to be .301 as shown in the Table 14. The following observations were made:

* The computed value of ‘r’ (r=.301) was found to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability.

* The null hypothesis was rejected.

* The relationship between the concerned variables was significant.

<figure><img src="image_9.png" /></figure>
* The relationship showed positive trend.

## Agricultural knowledge and usefulness

The relationship between agricultural knowledge the farm women and their usefulness of training programmes was determined by testing the following null hypothesis 'There is no relationship between agricultural knowledge of farm women and their usefulness of training programmes in livelihood security'.

The calculated value of the coefficient of correlation between the concerned variables was found to be .027 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r= .027) was found to be smaller than tabulated value (r= .176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis could not be rejected.

* The relationship between the concerned variables was not significant.

## Family co-operation and usefulness

The relationship between family co-operation of the farm women and their usefulness of training programmes in livelihood security was determined by testing the following null hypothesis 'There is no relationship between family co-operation of farm women and their usefulness of training programmes in livelihood security'.

The calculated value of the coefficient of correlation between the concerned variables was found to be .195 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r= .195) was found to be larger than tabulated value (r= .176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis was rejected.

* The relationship between the concerned variables was significant.

* The relationship showed positive trend.

## Annual family income and usefulness

The relationship between annual family income of the farm women and their usefulness of training programmes was determined by testing the following null hypothesis 'There is no relationship between annual family income of farm women and their usefulness of training programmes in livelihood security'.

The calculated value of the coefficient of correlation between the concerned variables was found to be .023 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r= .023) was found to be smaller than tabulated value (r= .176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis could not be rejected.

* The relationship between the concerned variables was not significant.

## Decision making ability and usefulness

The relationship between decision making ability of the farm women and their usefulness of training programmes was determined by testing the following null hypothesis 'There is no relationship between decision making ability of farm women and their usefulness of training programmes in livelihood security'.

The calculated value of the coefficient of correlation between the concerned variables was found to be .103 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r= .103) was found to be smaller than tabulated value (r= .176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis could not be rejected.

* The relationship between the concerned variables was not significant.

## Communication exposure and usefulness

The relationship between communication exposure of the farm women and their usefulness of training programmes in livelihood security was determined by testing the following null hypothesis 'There is no relationship between communication of farm women and their usefulness of training programmes in livelihood security'.

<figure><img src="image_10.png" /></figure>
The calculated value of the coefficient of correlation between the concerned variables was found to be .297 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r=.297) was found to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability.

* The null hypothesis was rejected.

* The relationship between the concerned variables was significant.

* The relationship showed positive trend.

## Fatalism and usefulness

The relationship between fatalism of the farm women and their usefulness of training programmes was determined by testing the following null hypothesis 'There is no relationship between fatalism of farm women and their usefulness of training programmes in livelihood security'.

The calculated value of the coefficient of correlation between the concerned variables was found to be .103 as shown in the Table 14. The following observations were made:

* The computed value of 'r' (r=.103) was found to be smaller than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability.

* The null hypothesis could not be rejected.

* The relationship between the concerned variables was not significant.

## Problems faced in participating training programmes by farmwomen

The problem faced in participating training programmes scores of farm women ranged from 7 to 18 with a mean 13.22 and standard deviation 3.23. Based on the problem scores, the women were classified into three categories, "low problem" (7 to 10), "medium problem", (11 to 14), and "high problem" (15 to 18). The distribution of women according to their problem is shown in following Table 15.

<table><caption>**Table 15.** Distribution of the women according to their problems faced</caption><thead><tr><th rowspan="2">Categories</th><th colspan="2">Women</th><th rowspan="2">Mean</th><th rowspan="2">Standard Deviation</th></tr><tr><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Low problem</td><td>32</td><td>30.19</td><td rowspan="3">13.22</td><td rowspan="3">3.23</td></tr><tr><td>Medium problem</td><td>44</td><td>41.51</td></tr><tr><td>High problem</td><td>30</td><td>28.30</td></tr><tr><td>Total</td><td>106</td><td>100</td><td></td><td></td></tr></tbody></table>

## Recommendations for policy implications

The following recommendations were made:

1. Training exposure had significant positive relationship with usefulness of training programmes in livelihood security. So it is recommended that different GOs and NGOs formulate need based training programmes.

2. Communication exposure plays important role in the development of women. So, it is recommended that concerned authorities should enhanced better facilities for communication exposure.

## Discussion

The highest proportion 44.34 percent women in the study area was in the middle aged compared to 37.74 percent of them being young aged and 19.92 percent old. It was found that vast majority (82.08 percent) of the respondents belongs to young to middle aged category. It might be due to selection procedure of the trainees by the training providers. It is rational that young and middle aged group showed hard working ability and hence this age group got priority to be selected as trainees. This study is relevant with Islam et al. (2015) finding of age relation of farmer. Kaur and Talukder (2007) also found the relevant result.

About 7.55 percent of the respondents were illiterate or could sign only compared to 56.60 percent of them having primary level of education, 33.02 percent had secondary level of education and nearly 2.83 percent had above secondary level of education. Thus, majority (92.45 percent) of the respondents had education with varying extent. Islam et al. (2015) revealed that of education of farmer, only 7.4% of the population has higher level of education and about 14% of the farmers have no education.

Computed data indicate that 36.79 percent of the women had small family size, 50.00 percent of them had medium family size and the rest 13.21 percent of the women had large family size. This study is relevant with Asif et al. (2015) findings.

<figure><img src="image_11.png" /></figure>
Slightly over than two-fifths (44.34 percent) of the women had medium family education compared to 35.85 percent low family education and 19.81 percent high family education. It is seen that more than fifty percent of the farm women had medium to high family education.

The majority (41.51 percent) of the women had training exposure compared to 34.91 percent low training exposure and 23.58 percent high training exposure. The subject matters on which the women received training were rice production, pest management, water management, compost preparation, fruit tree management, fruit production, livestock production, poultry production, nursery and vegetable cultivation. Islam et al. (2015) showed that the majority (71.9%) of the respondents had no training experience, while, about 17.4% had short training experience.

Islam et al. (2015) stated that about 41.3 percent of the respondents had low annual family income, while 17.4 and 11.6 percent of them had medium and high annual family income, respectively. Among the respondents about 29.8 percent were very poor. In our present study the majority (58.49 percent) of the farmers had medium family co-operation compared to 19.81 and 21.70 percent having low and high family co-operation respectively. It was revealed that family co-operation was helpful for taking part in development activities like training.

The majority (39.62 percent) of the women had medium agricultural knowledge compared to 33.96 and 26.42 percent having high and low agricultural knowledge respectively. Islam et al. (2015) suggested that 47.1 percent of the farmers had medium knowledge on agriculture and climate change and livelihood compared with 45.5 percent having high knowledge and 7.4 percent had low knowledge on agriculture.

The highest proportion (51.89 Percent) of the women had low annual family income, while 30.19 percent women had medium and 17.92 percent had high annual family income. It also showed that nearly fifty percent (48.11 percent) women constituted medium annual family income to high family income category. There is no published data available in family income criteria.

Slightly over than two-fifths of the farm women had medium decision making ability compared to 32.08 percent high and 25.47 percent low decision making ability. It is revealed that majority of the farm women have medium to high decision making ability. No published data are available.

Over two-fifths (41.51 percent) of the women had medium communication exposure to different communication sources and 33.96 percent of the women had low communication exposure and 24.53 percent of the women had high communication exposure. So majority (75 percent) of the respondents had low to medium communication exposure. Islam et al. (2015) revealed that 66.1 percent of the farmers had low communication exposure compared with 24.8 percent having medium communication exposure and 9.1 percent having high exposure.

The preset study indicates that 33.02 percent of the women had high fatalism, 42.45 percent of them had medium fatalism and the rest 24.53 percent of the women had low fatalism. Most of the women had medium to high fatalism. Islam et al. (2015) stated that about 81 % of the respondents were highly depends on their fate other than performance, which is one of their superstition. 15.7 percent of farmers moderately depend on their fate and 3.3 percent dependent on their fate poorly.

Computed data indicate that 45.28 percent of the women had medium, 34.91 percent of them had low and 19.81 percent of the women had high usefulness of training programmes. No Previous work is found on this area.

Each of 11 selected characteristics (age, education, family size, family education, training exposure, agricultural knowledge, family co-operation, annual family income, decision making ability, communication exposure, and fatalism) of the farm women and their relationships with usefulness of training programmes in livelihood security. No Previous work is found on this area.

The relationship between age of the farm women and their usefulness of training programmes was found the value of ‘r’ (r=-.260) to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability. The null hypothesis was rejected. The relationship between the concerned variables was significant negatively. The relationship between age of women and their usefulness of training. The younger women considered training programmes more useful than the older women in livelihood security. No Previous work is found on this area.

The relationship between education of the farm women and their usefulness of training programmes in livelihood security was found the value of ‘r’ (r=.206) was found to be larger than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis was rejected. The relationship showed positive trend of the women. So education of women had significant positive relation with decision making ability of the women. No Previous work are found on this area.

The relationship between family size the farm women and their usefulness of training programmes was found the value of ‘r’(r=.176) with 104 degrees of freedom. The null hypothesis could not be rejected.

<figure><img src="image_12.png" /></figure>
The relationship was not significant. So there was no relationship between the family size of farm women and their usefulness of training programmes in livelihood security. No Previous work is found on this area.

The relationship between family education the farm women and their usefulness of training programmes was the value of (r=.176) with 104 degrees of freedom at .05 level of probability. The null hypothesis could not be rejected the calculated value of ‘r’ (r=.083) was not significant. So there was no relationship between the family education of farm women and their usefulness of training programmes in livelihood security. No Previous work is found on this area.

The relationship between training exposure of the farm women and their usefulness of training programmes in livelihood security was the value of ‘r’ (r=.301) was found to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability. The null hypothesis was rejected. The relationship between the concerned variables was significant. The relationship showed positive trend. So the more the training exposure the more the usefulness of farm women training program in livelihood security. No Previous work is found on this area.

The relationship between agricultural knowledge the farm women and their usefulness of training programmes was the value of ‘r’ (r=.027) was found to be smaller than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis could not be rejected. So there was no relationship between the agricultural knowledge of farm women and their usefulness of training programmes in livelihood security. No Previous work are found on this area.

The relationship between family co-operation of the farm women and their usefulness of training programmes in livelihood security was the value of ‘r’ (r=.195) was found to be larger than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis was rejected. The relationship between the concerned variables was significant. So family co-operation of women had significant positive relation with decision making ability of the women. The more the education the more the usefulness of farm women training programmes in livelihood security. No Previous work is found on this area.

The relationship between annual family income of the farm women and their usefulness of training programmes was the value of ‘r’ (r=.023) was found to be smaller than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis could not be rejected. So there was no relationship between the annual family income of farm women and their family income. No Previous work is found on this area.

The relationship between decision making ability of the farm women and their usefulness of training programmes was the value of ‘r’ (r=.103) was found to be smaller than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis could not be rejected. There was no relationship between the decision making ability of farm women and their usefulness of training programmes in livelihood security. No Previous work is found on this area.

The relationship between communication exposure of the farm women and their usefulness of training programmes in livelihood security was the value of ‘r’ (r=.297) was found to be larger than tabulated value (r=.230) with 104 degree of freedom at .01 level of probability. The null hypothesis was rejected. The relationship between the concerned variables was significant. The more the education the more the usefulness of farm women training program in livelihood security.

The relationship between fatalism of the farm women and their usefulness of training programmes was the value of r' (r=.103) was found to be smaller than tabulated value (r=.176) with 104 degree of freedom at .05 level of probability. The null hypothesis could not be rejected. The relationship between the concerned variables was not significant. So there was no relationship between the fatalism of farm women and their usefulness of training programmes in livelihood security. No Previous work is found on this area.

The data indicate that 30.19 percent of the women had low, 41.51 percent of them had medium and the rest 28.30 percent of the women had higher problem faced in participating training programmes.

Recommendation

* Considering the significant positive relationship between usefulness of training programmes in livelihood security and their ages, it is recommended that different GOs and NGOs should offer age specific program for women for their more useful training program in livelihood security.

* Education of women had significant positive relationship with usefulness of training programmes in livelihood security. Education plays an important role in the way of developing women. Necessary literacy programs should be undertaken to educate women by different organizations so that women can be aware about different beneficial training programmes. So, it

<figure><img src="image_13.png" /></figure>
is recommended that concerned organizations should take initiatives to give women more opportunity for education.

* Training exposure had significant positive relationship with usefulness of training programmes in livelihood security. So it is recommended that different GOs and NGOs formulate need based training programmes.

* Communication exposure plays important role in the development of women. So, it is recommended that concerned authorities should enhanced better facilities for communication exposure.

## Conclusions

Slightly over than two-fifths (45.28 percent) of the women had medium, 34.91 percent of them had low and 19.81 percent of the women had high usefulness of training programmes. The situation reveals that majority of the women had medium to high usefulness of the training programmes in livelihood security, so, it can be concluded that the training programmes, could change the situation of women in Bangladesh. Age had negative significant relationship with usefulness of training programmes in livelihood security. It meant that the younger women had more usefulness of the training programmes. Education level of the women in the study area was relatively satisfactory because majority of the women in this area had education up to primary level but was not high. Education had positive correlation with usefulness of training programmes in livelihood security. Training exposure had significant positive relationship with usefulness of training programmes in livelihood security. The majority (41.51 percent) of the women had medium training exposure compared to 34.91 percent low training exposure and 23.58 percent high training exposure. Training makes an individual capable of performing job correctly. Family co-operation is an important aspect for the women in any developmental activities. Family co-operation had significant positive relationship with usefulness of training programmes in livelihood security. The finding showed that the majority (58.49 percent) of the farmers had medium family co-operation compared to 19.81 and 21.70 percent having low and high family co-operation respectively. It was revealed that family co-operation was helpful for taking part in development activities like training. So, it might be concluded that unless steps are taken to enhance family co-operation, the women would continue to suffer in taking part in the training programmes. Communication exposure of women had a positive significant relationship with usefulness of training programmes. In the study area it was found that majority (75 percent) of the respondents had low to medium communication exposure. So, it can be concluded that steps should be taken by different agencies for improving communication exposure.

## References

Asif, A. A., Samad, M. A., Rahman, M.H., Farid, M. A., Yeasmin, S. M., Rahman, B. M. S. (2015). Socio-economic Condition of Fish Fry and Fingerling Traders in Greater Jessore Region. International Journal of Fisheries and Aquatic Studies., 2(4): 290-293.

Halim, A. 1985.“A Historical Review of Approaches for the Communication of Agricultural Research”.National Symposium on Agricultural Research Bangladesh Agricultural Research Council, New airport Farm gate, Dhaka.

Islam, M. R., Biswas, M. J. H., Akanda, M.G. R., Amin, M.R., Hasan, I.M., Asif, A.A., Sheheli, S. and Sharif, B.M.N. (2015). Attitude of the farmers towards climate change effect on agriculture, Asian J. Med. Biol. Res., 1(2): 367-379.

Kaur, H. and Talukdar, R.K. (2007).Utility of Farm Women Training Programmes in Livelihood Security. Indian Res. J. Ext. Edu.,7(2&3): 15-17.

<figure><img src="image_14.png" /></figure>