Employment Outcomes of Graduates of an

Journal of Society & Technology 3:83-89 (2013)

Employment Outcomes of Graduates of an Agricultural School Naneta M. Panit1 , Susan S. Bentor1 & Elvira E. Ongy2 1 Naval State University-Biliran, Biliran, Philippines 2 Visayas State University-Baybay City, Leyte, Philippines Abstract The study aimed to determine the profile of the graduates and the factors which are significantly associated with better employment outcomes of an agricultural school. Descriptive research was used with the approved CHED Tracer study questionnaire with 291 BSEd and Agriculture related courses graduates from SY 2000 – 2010. Chi-squared test was used to determine if there exist relationship between employment status and sex, civil status, type of course, professional license, and skills of the graduates. Based on the findings of the study, factors that are associated with the employability of the graduates are sex, professional license, and skills. It was found out that women are more likely not to be employed than men. Keywords: descriptive, profile, skills, professional license, chi-squared test

Introduction One of the concerns of higher education sectors is the employment of the graduates, Naval State University – Biliran Campus as the agricultural school in Biliran Province faced with this problem. There has been an increase in numbers of an agricultural graduates and this signifies an increased supply of graduates to the industry. The Commission on Higher Education (CHED) has been requiring the colleges and universities to assess the outcomes of the graduates and work together between the needs and mission of their institution. To address the increasing rate of unemployment, Graduate Tracer Study (GTS) was conducted by several researchers to determine the employment outcomes of the graduates and the predictors of employment. Unwi, (2003), stated that graduates and organizations should adapt new skills and knowledge at regular periods in order to meet the challenges of the industry. To ascertain the employment outcomes of the graduates the following variables were determined: status of employment, professional examinations, and competencies/skills acquired in college applied *Correspondence: [email protected]

in the job. This concept was supported by the study of Montalvo (2006) that the relevant predictors affecting underemployment using logit estimation were the age, education, gender, urbanity and region. Moreover, Ariaso (2008) revealed that single- male graduates were more employable than those married, widow or widower, separated or divorced and single parent. This study adapted the Neoclassical theory which applies the standard demand – and – supply analysis to a labor market. Neoclassical theorists involve two factors: skill and resources. The theory was supported by the study of Baumol (1991) which states that “to be employed one must have the qualities and skills needed by the industry”. As for resources, neoclassical analysts state that new technologies such good machines, and updated computers makes the work more productive and efficient. The value of studies on the employment outcomes of graduates has been emphasized by a number of authors. For instance, Schomburg (2003) noted that the analysis of the relationship between higher education and work can be done through surveys. It provides accurate data on employment data and competencies of the

Journal of Society & Technology

Panit, Bentor & Ongy

graduates. According to Armenia (2008), the problem on compatibility between the courses offered by HEIs and the need of job market is an important factor that could determine employability of the new graduates in Eastern Visayas Region. However, in Naval State University – Biliran Campus, little is known about the employment outcomes of the graduates and the factors affecting employability of an agricultural related courses graduate. Hence, this paper presents information about the profile of the graduates of an agricultural school and the factors which are significantly related to employment outcomes of the graduates.

Methodology Data Gathering Instrument and Procedure

questionnaire and all filled-up questionnaires were returned to the researcher. Table 1 shows the distribution of the respondents by course with the target population and samples. There were 432 students that represent as the population of the study who are coming from six courses for the school year 2000-2010 of Naval State University. Out of 432, only 291 graduates responded.

Variables Associated Employment Outcomes

with

All variables used in this study are categorical. Table 2 presents the summary of the variables used in the study are sex, civil status, type of course, professional license, and skills associated with the employment status of the graduates. The type of course was categorized as either education courses or agriculture-related courses. Courses such as agricultural technology, agriculture, agribusiness, forestry, and fishery are categorized under agriculture-related courses while secondary education belongs to education courses. The variable for professional license has two levels (with professional license and without professional license). Skills of the graduates have 4 categories which include communication, human, entrepreneurial, and information technology skills. Employment status is categorized as well as either employed or unemployed. As the data contained 3 responses on the employment status (employed, self-employed, and unemployed), self-employed is merged with employed based on the definition of the National Statistical Coordination Board (NSCB). Self-employed is defined as employed individuals with a job but not at work.

Descriptive method of research was used in this study using the approved CHED Graduate Tracer Study Questionnaire adopted from Training Manual by Dizon (2006). It contained the following: personal information, educational background, trainings/advance studies attended after college, and unemployment data of the graduates. The questionnaire used the ended questions which were answerable by yes or no selection or with the given choices in each item which the respondent chooses. The list of graduates with home and email addresses and cellular phone numbers was secured from the office of the College Registrar which served as the population identified in this study. Samples were selected following the non-probability sampling technique employing convenience sampling. Here, samples were selected because they were accessible to the researcher. All graduates included in the list were contacted Data Analysis through email, facebook, conventional mail, and cellular phone calls and messaging, Descriptive analysis was carried out to however, not all responded. Those who have describe the socio-demographic profile of the responded were given with the guide respondents. Chi-squared test was used to 84


Bachelor Bachelor Bachelor Bachelor Bachelor Bachelor Total


Table 1: Distribution of Respondents Population Percent of Responses Groups 229 180 (78.60%) Secondary Education 49 28(57.00%) of Agricultural Tech. 89 52(58.42%) of Science in Agriculture 32 18(56.25%) of Science in Agribusiness 30 11(36.67) of Science in Forestry 3 2(36.67%) of Science in Fishery Tech 432 291 (67.36%

Table 2: Variables used in associating with the employment status of the graduates. Variable Employment Status (Employed, Unemployed) Sex (Male, Female) Civil Status (Married, Single) Type of Course (Agriculture-related courses, Education courses) Professional License (With license, without license) Skills (Communication, human, entrepreneurial, and information technology)

hand, 47.82% of unemployed have education courses whereas 52.17% have agriculture-related courses. Of all the graduates, 57.04% have professional license while 42.96% of them have no license. Out of 268 employed graduates, 53.36% have Results and Discussion professional license and only 46.64% have no license. For skills category, almost half of the Descriptive Statistics respondents (42.61%) have entrepreneurial skills and almost half (44.03%) of the Table 3 shows the responses for employment employed have entrepreneurial skills at the status or outcomes for each category of the same time. variables used in this study. A total of 153 and 138 graduates were females and males, respectively. It is observed from the cross Logistic Regression tabulation that more males (135) are employed than women (133) whereas only 3 Table 1 shows the employment status as males and 20 males are unemployed. influenced by civil status, gender, age, course Similarly, more single graduates (171) have professional license, and type of agency. As responded the survey than married ones shown in the table, civil status is not included (120). For those married and single employed as it might be that he/she is not yet married graduates, 60.07% are single while only (for married) the time he/she applied /got the 39.93% are married. Likewise, 61.86% of the job. Omnibus test shows that the model respondents have education courses while only 38.14% have agriculture-related courses. For significantly fits better an empty model those who are employed, 63.06% have (p=0.000) and Goodness of fit test shows education courses and only 36.94% for that the model fit adequately with the agriculture-related courses. On the other empirical data (p = 0.989). Table for the determine if there exist relationship between employment status and sex, civil status, type of course, professional license, and skills of the graduates.

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Table 3: Cross-tabulation of the variables related to employment status. Variables

Employment Status

Total

Unemployed Employed

Sex

Female Male

Total Civil-Status

Married

Single

Total

Education Courses Course Type Agricultural-related Courses

Without Professional License

With Professional License

153 100.00% 138 100.00% 291 100.00% 120

10.80%

89.20%

100.00%

10

161

5.80%

94.20%

23

268

7.90%

92.10%

11

169

6.10%

93.90%

12

99

10.80%

89.20%

23

268

7.90%

92.10%

Count

23

143

% within professional license category

13.90%

86.10%

Count

0

125

0.00%

100.00%

23

268

7.90%

92.10%

Count

Communication skills

Count

0

69

Human skills

% within skills category Count % within skills category

0.00% 12 21.40%

100.00% 44 78.60%

Entrepreneurship skills

Count

6

118

% within skills category

4.80%

95.20%

Count

5

37

% within skills category Count % within skills category

11.90% 23 7.90%

88.10% 268 92.10%

Information Technology skills Total

133 86.90% 135 97.80% 268 92.10% 107

% within professional license category Count % within professional license category

Total

Skills

20 13.10% 3 2.20% 23 7.90% 13

% within course type category Count % within course type category

Total

ProfessionalLicense

Count % within sex category Count % within sex category Count % within sex category Count % within civil status category Count % within civil status category Count % within civil status category Count % within course type category

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171 100.00% 291 100.00% 180 100.00% 111 100.00% 291 100.00% 166 100.00% 125 100.00% 291 100.00% 69 100.00% 56 100.00% 124 100.00% 42 100.00% 291 100.00%



Table 4: Cross-tabulation of the variables related to employment status. Variables Sex *Employment Status Civil Status *Employment Status Course Type *Employment Status Professional License *Employment Status Skills *Employment Status

Chisquare

p-value*

11.838 2.408 2.083

0.001 0.121 0.149

Odds ratios(for 2x2 table) for variables with significant relationship [Female/Male]=6.767 Cannot be computed Cannot be computed

18.806

0

Cannot be computed

22.518

0

Cannot be computed

variables in the equation shows that gender, age, professional license and skills are significant predictors for regular employment (p-values of 0.007, 0.030, 0.000 and .079). It can be derived from the table that males would likely increase their chances to be employed by 80.41% compared to females (p-value = 0.007). Course and type of agency where employed are not significant explanatory variables. The study of Ariaso (2008), supported that there were more males employed than females which indicates that males graduates were more employable than female graduates. Moreover, for every increase in age (year) of any employed individual will increase also his chances to get regular employment by 53.71 percent. Those who are employed with license and posses skills would likely increase his chances to get regular employment by 85.63% than those with no professional license. This finding was confirmed by Sambitan (1985) that of 160 BSIE graduate, majority were employed in teaching service because the course is designed purposely for teaching. Employment Outcomes of the Graduates Results of the analysis show that there were 291 valid cases observed and no missing case. The data meet the minimum requirement for chi-squared test wherein number of cells containing less than 5 counts did not exceed the minimum requirement stipulated. It was found out that 3 out of 5 variables analyzed

have significant relationship with employment status. These include sex (x2 11.838, p 0.01), professional license (x2 18.806, p 0.01),and skills (x2 22.518, p 0.01), while civil status (x2 2.408, p ¡ 0.05)and type of courses (x2 2.083, p ¡ 0.05)did not show any relationship with employment status. As depicted in the cross tabulation of the variables (Table 3), 86.9% of the females are employed compared to only 13.1% unemployed while men are 97.8% and 2.2% employed and unemployed, respectively. Odds ratios (Table 4) show that women have odds of 6.767 times higher than men to get unemployed. Thus, women have higher possibility that they will not be employed compared to men. Gender issues in employment have been widely debated. Numerous studies have conducted citing the significance of gender in the employment outcomes. As cited by OECD (2012), women have less chances to work full-time and more chances to be employed in lower-paid occupations and less likely to progress in their careers. It was stressed out further that gender pay gaps persist and women are more likely to live in poverty compared to men. Based also on the findings presented by the United Nations Human Rights in 2010, more men are employed in the formal workforce in the Philippines. It further shows that the Labor Force Survey in October, 2010 showed a total employed labor force of 36.5 million of which 22.3 M (61%) are men while 14.2 M (38%) are women.

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Professional license also shows significant relationship with employment status. Although, odds ratios were not determined, it can be depicted from Table 3 that 86.1% of the licensed professionals are employed and only 13.9% are unemployed. Whereas, all licensed professional graduates are employed and none is unemployed. It is very obvious that licensed professionals are more preferred by the employers and it is one of the major criteria used in many companies and government institutions in selecting the applicants. University Language Services (ULS) cited that neither graduation nor a specific college degree automatically qualifies someone to work in certain professions in the United States (US) but what is needed is the US licensure. Same through as what the Philippines is practicing. Similarly, skills also found to have high significant relationship with the employment status. It indicates that skills they possessed could be a significant or added factor to their employability. According to Beheshtifar and Norozy (2013), strong social skill can facilitate interpersonal interactions which can in turn lead to effective job outcomes. Many articles have cited that interpersonal skills are the most important factor in career advancement. Across the skills, entrepreneurial skills have the highest percentage of employment. It was noted that all respondents possessed skills. There are 118 employed graduates who possessed entrepreneurial skills out of 268 employed graduates. Skills is considered as a wow factor for the applicants in applying for a job as many have known. Civil status and course of the graduates show that they are not associated with their employability. This could mean that chances of being employed are the same for education and agriculture-related courses. Single and married graduates have also same chances that they will be employed or not. However, the result is not supported by the findings of some existing related studies. Roy and Mukherjee (2013) found out that marriage is

a factor of women’s employability in India. On the other hand, course is not significantly associated with the employment status.

Conclusion Based from the findings of the study, graduates who are passers of professional examination in their field of specialization and who possess skills needed by the industry are more employable. Male are more employable than female. Education graduates are employed suited to their field of specialization while there was an educational mismatch among the graduates of agriculture related courses.

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Coordination


Board.

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