RELATION BETWEEN CAREER MATURITY AND ACADEMIC PERFORMANCE

Dr. V K Pathak

Dr. Surat Pyari Pathak

ABSTRACT

This paper presents the seeming lack of traits and characteristics that need to describe career maturity among youth of secondary school students. Terminal points of the study are secondary school students of CBSE Delhi using a randomly selected sample from Agra & New Delhi. The authors drew data with a validated set of questionnaires on the status and level of their Career maturity. Data revealed that more than half of the sample are low on the maturity status while another considerable percentage are just barely mature, displaying traits of not having a specific career in mind. It was also found that the youth at secondary level do not spend time to think through possible employment in the society, they mostly never consult with adults on the demands of the world of work among other immature traits. Positive correlation between academic performance and carrier maturity was found in the study. School activities may improve the status of the students’ career maturity status was suggested as a improving measure.

Keywords:  Career maturity, Career maturity status, secondary school students, Academic Performance, Grade point Average (GPA).

Successful completion of schooling represents a channel for greater earnings and upward career mobility, and also increases the likelihood   for better earnings and employment. Additional benefits found to be concomitant with advanced education include greater occupational choice, political participation, and better mental health (Levin, Guthrie, Kleindorfer, & Stout, 1971). Advanced education is also a means for personal achievement, for a role providing service to others in the community and to participation in admired and rewarding professions in contemporary culture.

Secondary level students have to face various difficulties to successfully completion their schooling. As they stand at the threshold of the age of stress, strain and storm (G. Stanley Hall). Several factors affecting academic performance in the present study have been identified and examined, yet found to be inconsistent predictors of academic achievement (Huffman et al., 1986).

 

 Studies have shown that career maturity, realistically deals with occupational choices, correlates positively with academic performance in most student populations, including academic groups (Walsh & Hanle, 1975; West, 1986). Some distinct subgroups, however, are exceptions (Burkhead & Cope, 1984), and minority ethnic groups have been found to score consistently lower on career maturity than comparison to other groups (Loesch, Shub, & Rucker, 1979; Pelham & Fretz, 1982). Researchers working with secondary students often conclude that more study is needed to understand and address the problems in both educational and career processes of this group (Gade, Fuqua, & Hurlburt, 1984; Huffman et al., 1986; Lee, 1984). Consequently, we decided to examine the career maturity and its relationship with academic performance among students.

Students’ scores were found to be influenced by the factors other than ethnicity, including rural or urban background of the students, age, educational grade level, and gender. This present study shows an attempt to investigate and compare the career maturity of the Delhi and Agra students, and to determine if the positive correlation between career maturity and academic performance found in the population exists in this group.

Objectives

1. To study is there any correlation between Career Maturity and Academic Performance.

2. To study whether the variation in Academic Performance effects upon Career Maturity of students or not.

Hypothesis

H 1. There is no significant relation between Career Maturity and Academic Performance.

H 2. There is no significant effect of Academic Performance on Career Maturity.

Methodology of the Study

Sample of the Study

Selection of Sample for Study

The sample used in the present study consisted of 100 students who were enrolled at Delhi and Agra during session 2011-2012. The students were drawn from participation in two assignments. One group of 25 students participated voluntarily in a study of the effects of a computer-based guidance system conducted by a counselor in the school’s Career/Life Planning Center. In the second study, a Career Services program at the school administered a career maturity instrument to 25 students to obtain information regarding their educational and career planning characteristics. Career planning services and workshops are some of the activities offered by Career Services. These students voluntarily completed the instrument and a short data sheet, and were encouraged to make appointments to review their scores with the counsellor.

Fig.1: Sample of the Study

There was no significant difference in the mean age of the two groups. Grade-point average (GPA) was used as the operational definition of academic performance in the study, and the results of a t-test on GPA showed a significant difference (t = 3.04, p<.01) between the two groups, viz. students of Delhi & Agra.

Table: 1:  Student’s Distribution

Variable	Level	Students of Delhi	Students of Agra	Total
Academic Achievement	High	15	13	28
	Medium	24	27	51
	Low	11	10	21
Total		50	50	100

The total sample consisted of 28 students of High academic achievements, 51 students of medium academic achievement and 21 students of low academic achievements. The examination of the present study was based on four equal working weeks same as Delhi and Agra. The examination revealed no significant difference of the two groups examine for the study.

Instrument of the Study

The Career Maturity Inventory by Dr. Nirmala Gupta (An Indian Adaption of Crites’s CMI Test) was administered to the students in both groups. The score on this instrument was used as the operational definition of career maturity. The Attitude Scale is used for the study is Career Maturity Inventory (CMI), and "elicits the feelings, the subjective reactions, the dispositions that the individual has toward making a career choice and entering the world of work" (Crites, 1978, p. 3). Crites states that "Maturity of these attitudes is also associated with an individual having definite career choices, being consistent in choices over time, and making realistic choices" (p. 4).

CMI is the most widely used measure of career maturity, and has been in use for over a decade [Palmo and Lutz (1983)]. The CMI was developed initially for use with grade school and high school students. The CMI or its precursor, the Vocational Development Inventory, have been used in studies involving college populations (Anderson, 1976; Walsh & Hanle, 1975; West, 1986), ethnic minority populations (primarily Black students) in high school and college (Pelham & Fretz, 1982; McNair & Brown, 1983), other high school populations which included American Indian students (Lee, 1984; Schmieding & Jensen, 1968), disabled college students (Burkhead and Cope, 1983), rehabilitation clients at various stages of retraining (Strohmer, 1981), and disadvantaged students, some college-aged who dropped out of high school (Palmo & Lutz, 1983).

Procedure of the Study

Pearson product-moment correlations between career maturity and GPA were computed. The mean career maturity scores were compared with t-tests for significant differences.  

Data from the study were also investigated by three methods for the effect of class standing on the relationship between career maturity and GPA, and for career maturity differences in each class. I, the Pearson product-moment correlation between CMI score and cumulative credit hours was found for the total sample of two groups. II, the Pearson product-moment correlation between CMI scores and GPA was determined for each group in the total sample. III, the mean career maturity scores for each group were compared.

Results

The relationships of career maturity and academic performance are reported in Table 1.

TABLE 2:  Correlations between GPA and Career Maturity (CMI)

Category	N	Correlation*
Total Sample	100	r=.3949(p=.030)
Students of Delhi	50	r =.4174 (p =.022)
Students of Agra	50	r =.3953 (p =. 026)

*Pearson product-moment coefficient. 

 Results showed a significant positive correlation between career maturity and GPA for the total sample of students. A significant positive correlation was found for the group of students in the sample.

TABLE 3:   Mean GPA, Mean CMI Correlations through Levels

Category	No. of Students	GPA	CMI-AS	Correlation, (p)
Total Sample	100*	2.47	37.1	.3233 (.36)
Low Academic Achiever	21	2.36	33.5	.4177 (.022)
Medium Academic Achiever	51	2.63	37.6	.4687 (.057)
High Academic Achiever	28	2.67	38.0	.2173 (.497)

*N=100[Delhi(50)+Agra(50)]

Discussion

Implications of the Study

Present study reveals that students often score as fewer careers mature in relation to their academic achievement. It shows the results of the comparison of mean career maturity scores for the students have significantly related with their academic achievement. In fact, while the career maturity was nearly equal to the scores of academic achievements.

This study also investigated whether the positive correlation between career maturity and academic performance found in populations existed in this group of students. It can be concluded from the results that career maturity is positively correlated with GPA.

The mean career maturity score and the correlation between career maturity and GPA for students also suggest that career education might be used to address the problem of the educational attention rate of students. Career education has been shown to influence academic achievement for the better in other populations.

References

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