Sign up for our newsletter, to get updates regarding the Call for Paper, Papers & Research.
Effects of Career Adaptability, Work Volition on the Perceived Life Satisfaction and Moderating Role of Gender of Undergraduates in State Universities, Sri Lanka
- D.D Lokuge
- I.K.J.P Kumara
- K.R Ambepitiya
- 1959-1973
- Feb 15, 2024
- Human resource management
Effects of Career Adaptability, Work Volition on the Perceived Life Satisfaction and Moderating Role of Gender of Undergraduates in State Universities, Sri Lanka
D.D Lokuge, I.K.J.P Kumara, K.R Ambepitiya
Faculty of Management, Social Sciences and Humanities, General Sir John Kotelawala Defence University, Sri Lanka
DOI: https://dx.doi.org/10.47772/IJRISS.2024.801143
Received: 27 December 2023; Revised: 09 January 2024; Accepted: 13 January 2024; Published: 15 February 2024
ABSTRACT
Education has become a top priority in labour market in Sri Lanka. As a result, high competition develops within each individual undergraduate in selecting a career path. The main aim of this research paper is to recognize relationship between identified constructs relating to career and life satisfaction of state sector university undergraduates who enroll to Social Sciences and Humanities degree programmes. A structured questionnaire-based survey was used to conduct a quantitative study, and 174 state sector university undergraduates, who were looking for jobs, were included in the qualified sample. Data was analyzed by using software such as SPSS version 22 and AMOS. The study was supported by three laid down hypotheses, and findings identified that career adaptability, life satisfaction and work volition are having positive relationship. Having noticed that work volition is partially mediated, hypothesis four was also used in further analyzing of data. The empirical investigation showed that there is no any gender influence on undergraduates’ career adaptability and perceived life satisfaction. The last hypothesis was not supported as gender which does not consider as a moderator.
Keywords: Career Adaptability, Work Willingness, Volition, Life Satisfaction, Undergraduates
INTRODUCTION
Undergraduate intakes for state universities in Sri Lanka have increased tremendously in recent decade. Out of the annual university intake, female enrolment is 64.8% while male enrolment is 35.2% (University Grant Commission in Sri Lanka, 2022). Graduate employability in Sri Lanka is an area which extensively discussed in the academic arena (Ariyawansa, 2013; Liyanage, Kumara, & With anawasam, 2016; Weligamage, 2007). The findings reveal that compared to other degree programmes (i.e Management, Engineering, Medicine) Social Sciences and Humanities graduates face difficulties in finding employment opportunities. Most of them employed in irrelevant disciplines in public sector organizations absorb under the graduate training scheme in Sri Lanka. Hence, their job satisfaction is in a questionable state.
Manathunga and Kappagoda (2020) noted that the life satisfaction of students depends on personality, separation and homesickness, interpersonal relationships, stress and university facilities. Weerasinghe and Fernando (2018) recognized that the availability of some physical infrastructure including lecture theaters, well stocked libraries, lodging facilities, entertainment along with employability of undergraduates in state universities were recognized as the factors most influencing overall student satisfaction. However, their study highlighted whether the quality of life of university students remains an understudied issue that can create problematic situations if not properly addressed. Yatigammana and Wijayarathna (2021) found that many university students are immersed in high-stress environments due to academic workloads and responsibilities. They revealed that gender effect in relation to the quality of life of university students has a significant impact on study domains. In addition, in their study, they analyzed the life satisfaction of students at public universities in four mainstreams: health segregated into physical, mental, environmental constructs and social relationships as another construct. Gunasekara and Jayasekara (2021) examined the influence of happiness on the academic performance of students. Undergraduates’ sole awareness of future career prospects is an essential factor in maintaining attention and morale to do their degrees well. In the absence of much literature on student life satisfaction predicted by career adaptability, this research paper aims to examine how career adaptability and work willingness affect the perceived life satisfaction of social sciences and humanities undergraduates, leading to their subjective well-being. Then examine whether the gender of the students has an impact on the relationship between career adaptability and their life satisfaction.
REVIEW OF LITERATURE
Career aspirations of undergraduates in Sri Lanka were studied as a core construct of career development (Rathnayake & Elvitigala, 2020). Career adaptability is another important construct in career development according to the career construction theory (Savickas, 2002), which has paid limited attention in empirical investigation within the context of Sri Lanka.
Career adaptability
Sovickas’ (1997, 2002, 2005) studies on career construction theory, career adaptability belongs to four dimensions including concern, confidence, control and curiosity which indicates how individuals sense about choosing their career options and transitions. Greater level of adaptability is associated with positive career maturity among college students (Douglass & Duffy 2015).
Life satisfaction
In theory, life satisfaction is noted as a holistic view about how one face events in his/her life (Huebner et al., 2005). However, this mental assessment reflects how individuals believe their lives need to be compared to how it in reality (Paschali & Tsitsas 2009). In brief, life satisfaction denoted the quality of life as a subjective evaluation. When asked what determines life satisfaction, the existing literature can be divided into two main areas, one being personality (i.e. genetics, innate traits) and the influence generate from some environmental situations (i.e. life circumstances and some important turning points in the life such as career transitions). In support of the career adaptability argument, it is necessary to examine empirically whether it plays a role in determining life satisfaction (Dwivedi and Rastogi, 2016).
Willingness to work (Work volition)
It is emphasized that in vocational psychology, this construct expressed their favourations in basic career decision making. In this endeavor work volition comprised of the role of interests, values, skills, personality and self-efficacy (Brown & Lent, 2019). Many studies in the global context found that the sense of courage in career decision making is in positive relationship with an array of career outcomes mainly on career adaptability and academic satisfaction and life satisfaction (Duffy et al. 2013; Duffy, Diemer, & Jadidian, 2012). In search of empirical studies relating to the work willingness there is a limited understanding of this useful construct. Duffy, Autin & Bott (2015) defined the notion of work volition is the ability to generate future career related decisions by conquering obstacles and ultimately leading to work readiness.
Gender as a moderator
The gender of the undergraduates and their life satisfaction in previous results showed that there is a significant association (Zeng et al., 2022). As there is a dearth of scholarly work on the influence of gender on career adaptability and life satisfaction, this research will help to examine whether gender matters in the relationship between career adaptability and student life satisfaction.
RESEARCH DESIGN
This research paper is based on positivist approach. A quantitative study makes it possible to verify the hypotheses developed. The time horizon of this study is cross-sectional. Data were collected within the month of June 2023. The target population was all final year undergraduates enrolled in Social Sciences and Humanities programs at state universities. A total of 200 final year undergraduates were selected from four state universities (Ruhuna n=35, Sabaragamuwa n=30, University of Sri Jayewardenepura n=60 and Rajarata n=75) and were participated in the study. The gender composition is 56.32% male (n=98) and 43.68% (n=76) female. Out of distributed questionnaires 174 (87%) were the qualified questionnaires after eliminating outliers and inappropriately filled questionnaires, 56.32% male (n=98) and 43.68% (n=76) female. All the undergraduates were within the age range of 24-27 as they were the final year undergraduates and the sampling method used in this study is convenience sampling. Although the sampling method should be a probability sampling technique for a quantitative study to satisfy generalizability, with the existing time constraint, the researchers have chosen non-probability sampling (convenient sampling) method, which is a limitation of this study. All participants verbally agreed to participate voluntarily in the research work prior to being administered the questionnaire based survey. The questionnaire consisted of four parts and 41 items were included.
Fig. 1 Conceptual model
H1: The is a positive relationship between career adaptability and perceived life satisfaction of the undergraduates in state universities in Sri Lanka.
H2: There is a positive relationship between career adaptability and work volition of the undergraduates in state universities in Sri Lanka.
H3: There is a positive relationship between work volition and perceived life satisfaction of the undergraduates in state universities in Sri Lanka.
H4: Work volition mediates career adaptability and perceived life satisfaction of the undergraduates in state universities in Sri Lanka.
H5: Gender of undergraduates moderates the relationship between career adaptability and perceived life satisfaction.
Measures
Career adaptability (Independent variable) – Career adaptability is a crucial variable in students’ occupational development and is defined as a psychological construct that describes an individual’s willingness and resources to cope with existing and expected vocational development activities (Savickas, 2002, p. 156). Undergraduates’ level of career adaptability was assessed using the 24-point Career Adapt Ability Scale (CAAS) (Savickas & Porfeli 2012). The CAAS consists of four subscales: concern, control, curiosity, and confidence. Each one comprised of six items and undergraduates may respond on a 7-point Likert scale within the range of 1 (not strong) to 7 (strongest).
Work volition (Mediating variable) Willingness to work, defined as the assumed ability to make career decisions in a way to suppress limitations which then enhance the life satisfaction (Duffy et al., 2012). Even though it is extremely difficult to find previous literature directly examine the relationship between career adaptability and willingness to work, the fact that career adaptability of people assists to overcome job challenges. Work volition, consisted of 7 items that measured an individual’s perceived capacity to make future occupational choices. Work Volition Scale–Student Version (WVS-SV) was used to measure the willingness to work. Participants were responded to these 7 items on a 7-point Likert-type scale from strongly disagree (1) to strongly agree (7).
Life satisfaction (Dependent variable) – Diener et al. (1985) introduced the Satisfaction With Life Scale (SWLS). This scale’s indicators often developed to measure the subjective well-being of life satisfaction (Neto & Barros, 2007). Participants were responded to these 5 items on a 7-point Likert-type scale from strongly disagree (1) to strongly agree (7).
Gender (Moderating variable) – Previous studies of gender differences in life satisfaction have produced results lead to confusion during the interpretation. Wood, Rhodes, & Whelan (1989) stated in their seminal work on gender studies, positive well-being found that female report higher life satisfaction than male. Haring, Stock & Okun (1985) showed in their meta-analysis that in the comparison of happiness with gender male found to be happier than female but there is a very slight difference available. To support this empirical investigation other researchers also indicated that the male participants had a higher level of life domain satisfaction than their female counterparts (Diener et al., 1999; Fujita, Diener & Sandvik, 1991). This research paper examines by becoming a male or a female undergraduate whether there is any significant influence to the relationship between career adaptability and life satisfaction.
DATA ANALYSIS AND RESULTS
A structured questionnaire based survey used to gather primary data for the study. The questionnaire was distributed among 200 final year undergraduates in the discipline of Social Sciences and Humanities. In the data cleaning procedure, the details of univariate outliers found when looking at a distribution of values in a single dimension (ex: career adaptability) by using box plots. After recognizing those outliers have corrected by eliminating those cases (86, 114, 102, 150,and 157). Further recognized some questionnaires were with missing values. At the end of data cleaning process 174 cases were available for data analysis. Then referring to Q-Q plots and histograms found all the variables were normally distributed. It is examined the skewness and Kurtosis of all variables. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. When considering the skewness all the variables were within the range of +1.96 to -1.96. Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. Kurtosis of all the variables are within +3 to -3. Therefore, it was possible to conclude that the data normally distributed. In addition, assumptions about normality, linearity and independence of residuals were subsequently checked. Further, to see how the dichotomous variable (gender) is having moderating effect on career adaptability and life satisfaction. Validity concerns were sorted out by considering the composite reliability (above 0.7) and average variance extracted (AVE) (greater than 0.5). A confirmatory factor analysis (CFA) was considered as appropriate when some empirical studies provided some insight into the underlying latent variable structure. CFA that performed using IBM AMOS 22 software and excel stat tool package were utilized to calculate the fit indices: Chi-Square, Comparative Fit Index (CFI), and Root Mean Square Error Approximation (RMSEA). In order to analyze the mediating effect of work volition used SPSS AMOS bootstrapping method as scholars have advised that the significance of these effects is best tested by bootstrapping techniques (Preacher, Rucker, & Hayes, 2007; Shrout & Bolger, 2002).
18.97% of the undergraduates’ families earn less than Rs.50,000 per month. 45.98% of the undergraduates’ families are receiving an income range between Rs. 51,000 – Rs.100,000. 25.86% of the undergraduates’ families earn an income range between Rs.101,000- Rs.200,000. Further, only 9.20% earn more than Rs.200,000 per month. Overall 64.95% of the undergraduates’ family income is less than Rs. 100,000 and 35.05% have more than Rs.100,000. Compared to upper income earning families in the sample, lower income earning families are approximately twice greater.
Table 1: Cross Tabulation of Gender and Job Relevance for The Degree | |||||
Job relevance for the degree | Total | ||||
Yes | No | do not know | |||
Gender | Male | 55 | 19 | 24 | 98 |
Female | 6 | 16 | 54 | 76 | |
Total | 61 | 35 | 78 | 174 |
Source: Survey data 2023
When considering about the gender perception about the perceived job relevance for the degree programme, male are more confident than female undergraduates as per the table 01 cross tabulation.
Table 2: Cross Tabulation of Gender and Family Income | ||||||
Family Income | Total | |||||
<50000 | 51000-100000 | 101000-200000 | >200000 | |||
Gender | Male | 19 | 45 | 24 | 10 | 98 |
Female | 14 | 35 | 21 | 6 | 76 | |
Total | 33 | 80 | 45 | 16 | 174 |
Source: Survey data 2023
Table 2 indicates that 64 male undergraduates’ family income is less than Rs.100,000 while 49 female undergraduates’ family income is less than Rs.100,000. Compared to the percentages (64/98)= male 65% and female (49/76) 64%. It implies that there is only 1% difference between male and female undergraduates’ gender influence on family income.
Due to the slight changes made to the original Career Adapt Ability Scale (CAAS), Work Volition (student version) and Life satisfaction it was necessary to test the reliability of the revised tool before presenting the analysis results.
Table 3. Reliability Of Measurement Instrument
Construct | Cronbach’s Alpha | No of items |
Career concern | .859 | 6 |
Career control | .838 | 6 |
Career curiosity | .824 | 6 |
Career confidence | .843 | 6 |
Career adaptability | .946 | 24 |
Work volition | .855 | 7 |
Life satisfaction | .883 | 5 |
Source: Survey data 2023
Pallant (2005) stated if Cronbach’s alpha coefficient is 0.7 or above indicate an ideal reliability of each construct. Accordingly, each section of the questionnaire was tested. From the results, as shown in Table 03 Cronbach’s alpha coefficients of variables ranged from 0.824-.946. This was in line with the standard scale 0.7. Accordingly, observed items expressed a good internal consistency.
Table 4. Descriptive Statistics and Correlations
Construct | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
1 | Career concern | – | ||||||
2 | Career control | .72 | – | |||||
3 | Career curiosity | .67 | .76 | – | ||||
4 | Career confidence | .62 | .70 | .77 | – | |||
5 | Total CA | .86 | .90 | .90 | .87 | – | ||
6 | Total WV | .49 | .45 | .41 | .40 | .50 | – | |
7 | Total LS | .43 | .34 | .36 | .43 | .44 | .54 | – |
Mean | 5.17 | 5.15 | 5.11 | 5.32 | 5.19 | 3.85 | 4.74 | |
SD | .91 | .89 | .83 | .82 | .76 | 1.92 | 1.15 |
Note: All correlations significant at the P<.001 level
The means and standard deviations of career concern 5.17 (SD=.91), career control 5.15 (.89), career curiosity 5.11 (SD=.83), career confidence 5.32 (SD=.82), career adaptability 5.19(SD=.76), work volition 3.85 (SD= 1.92) and life satisfaction 4.74 (SD=1.15), are presented in Table 04. The mean scores of a 7-point Likert scale (1–7) were within the range of 5.11-5.32 for career adaptability with a low standard deviation shows lower spread and average respondents in to agree position. Mean and standard deviation of work volition 3.85 (SD=1.92) and life satisfaction 4.74 (SD=1.15) higher spread with average respondents in the position of disagree. A correlation analysis was also conducted for all variables as presented in Table 4. Bivariate correlations among seven variables shows that career concern (r=.43), career control (r=.34), career curiosity (r=.36), career confidence (r=.43), career adaptability (r=.44) and work volition (r=.54) are within the range of .3-.7 then considered as having moderate positive relationship with undergraduates’ life satisfaction. The simple regression was conducted to see whether career adaptability total score predicted life satisfaction of university students. Analysis findings appear in Table 5.
Table 5. Results Of Simple Regression Analysis Regarding Career Adaptability Predictor Role In Life Satisfaction
Variable | B | Β | T | R | ∆R2 | F |
Constant | 1.278 | – | 2.363** | |||
Career adaptability | .667 | .442 | 6.467** | .442 | .196 | 41.828** |
*p<.001
As presented in Table 05, according to results of Simple Regression Analysis, career adaptability significantly predicted life satisfaction (R= .442, ΔR2 = .196, F= 41.828, p<.001). In addition to this, career adaptability total score accounted for 19.6% of the variance in life satisfaction.
Table 6. Convergent Validity and Discriminant Validity
CR | AVE | MSV | MaxR(H) | Work
volition |
Career
adaptability |
Life
Satisfaction |
||
Work volition | 0.861 | 0.512 | 0.387 | 0.876 | 0.716 | |||
Career
Adaptability |
0.949 | 0.825 | 0.284 | 0.966 | 0.533 | 0.908 | ||
Life satisfaction | 0.886 | 0.610 | 0.387 | 0.892 | 0.622 | 0.481 | 0.781 |
*Values on the diagonal (highlighted) are square root of the AVE while off-diagonals are correlations
At the initial Confirmatory factor analysis (CFA) recognized B2 (Discrimination will not affect my ability to choose a job) which was one of the indicators of work volition was produced lowest factor loading (i.e.436) value and created issue and eliminated and gained the values. CFA analysis viewed as applicable when there are some empirical studies which provide certain knowledge about the underpinning latent variable structure (Byrne 2009). Hence a CFA was conducted using IBM AMOS 22 software and was judged the fit indices including: Chi-square (χ2 1057, N=174) and probability level .001.
A structural equation model originated through AMOS was utilized to test the relationships. Hair et al. (2010) suggested that an accepted model should comprised of the value of the CMIN/df is <3. Tucker and Lewis (1973) noted that index (TLI), the Confirmatory Fit Index (CFI) (Bentler, 1990) is >.9. Additionally, if the AMOS computed value of the standard root mean square residual (RMR) <.05 and the root mean square error approximation (RMSEA) is within the range of .05 and .08 the developed model considered as an adequate fitting model. All the fit indices included in table 7 are within the acceptable range.
Table 7. Model Fit Summary
Model | NPAR | CMIN | DF | P | CMIN/DF |
Default model | 79 | 1162.207 | 587 | .000 | 1.980 |
Model | RMR | GFI | AGFI | PGFI | |
Default model | .048 | .921 | .956 | .903 | |
Model | NFI Delta1 |
RFI rho1 |
IFI Delta2 |
TLI rho2 |
CFI |
Default model | .721 | .701 | .839 | .897 | .902 |
Model | RMSEA | LO 90 | HI 90 | PCLOSE | |
Default model | .075 | .069 | .082 | .000 |
Fig.2: Structural equation model
Table 8 use to indicate the hypothesized relationships, β value, standardized estimates, t-value, p-value and the derived decision. This research paper assessed the effect of career adaptability, work volition on life satisfaction of undergraduates. The effect of career adaptability on life satisfaction of undergraduates was positive and significant since the p-value is less than .001 H1 is supported. The effect of career adaptability on work volition was positive and significant effect since the p-value is less than .001 H2 was supported. Further, H3 was supported since there is a positive significant effect between work volition and life satisfaction as the p-value is less than .001.
Table 8. Hypotheses Testing
H | Hypothesized relationship | Estimates
Β |
Standardized estimates | t-value | p-value | Decision |
H1 | Career Adaptability-> Life satisfaction | .287 | .067 | 4.282 | .000 | Supported |
H2 | Career Adaptability-> Work volition | .405 | .094 | 4.322 | .000 | Supported |
H3 | Work volition-> Life satisfaction | .684 | .138 | 4.970 | .000 | Supported |
The mediation test Figure 3 shows the total, direct and indirect effect of introducing mediator (work volition) on the relationship between career adaptability and life satisfaction of university undergraduates. The model fit is good: χ 2 /df 2.781, RMSEA 0.076, IFI 0.902, TLI 0.880, GFI 0.89 and CFI 0.901. From Table 09 shows total effect without introducing work volition as the mediator was having significant effect between career adaptability and life satisfaction among university undergraduates. Then, after introduced work volition as the mediator direct effect between career adaptability, life satisfaction reduced to .26. But same is still significant as the p-value<.05. Further, indirect effect of career adaptability and life satisfaction .355 became significant since p-value <0.05 (after bootstrapping received the two trailed significance =.010). Therefore, it is concluded that there is a mediating effect of work volition between career adaptability and life satisfaction where H4 was supported. Since both the direct and indirect effect were significant and work volition is partially mediating the relationship between career adaptability and life satisfaction as to how table 9 further illustrates.
Table 9. The Mediator Results Between Career Adaptability And Life Satisfaction
Bootstrapping | |||||
Bias corrected
90% |
Percentile 90% | ||||
Model | Estimates | SE | One tailedp-value | Lower Upper | Lower Upper |
Total effect
Career adaptability->Life satisfaction |
.615 | .477 | .000 | .24 .58 | .23 .57 |
Direct effect
Career adaptability-> life satisfaction |
.260 | .202 | .011 | .16 .52 | .16 .52 |
Indirect effect
Career adaptability->life satisfaction |
.355 | .275 | .0005 | .006 .14 | .002 .13 |
Fig.3 Unstandardized estimates prior to introduce mediator (Work volition)
Fig. 4 Unstandardized estimates after introducing mediator (Work volition)
Introduce gender as the moderator
Fig.5 Unconstraint model
Fig.6 Fully constraint model
Moderator effect-
Prior to calculate whether gender is having moderator effect obtained the estimates CMIN/DF (2.832), GIF (.982), AGI (.872), NFI (.937), RFI (.907), IFI (.958), TLI (.938) and CFI (.958) proceed with confirmatory factor analysis.
Table 10. Moderator Effect Analysis
Model | Chi Square value | Df |
Unconstraint model | 102.877 | 38 |
Fully constraint model | 115.148 | 46 |
After obtaining the values in table 13 using the stat tool package available in excel ran the calculation and received p-value 0.126 which is greater than alpha implied that there is measurement model invariance where it allows the moderating effect can further analyze using AMOS.
Table 12. A Comparison of Gender Difference As The Moderator Between Career Adaptability And Life Satisfaction
Male | Female | ||||||
Estimate | P | Estimate | P | z-score | |||
Total_CC | <— | CA | 1.150 | 0.000 | 0.894 | 0.000 | -1.599 |
Total_CB | <— | CA | 1.001 | 0.000 | 0.922 | 0.000 | -0.536 |
Total_CD | <— | CA | 0.859 | 0.000 | 1.005 | 0.000 | 0.939 |
LS3 | <— | LS | 1.541 | 0.000 | 1.192 | 0.000 | -1.153 |
LS4 | <— | LS | 1.630 | 0.000 | 1.134 | 0.000 | -1.719 |
LS5 | <— | LS | 1.365 | 0.000 | 1.119 | 0.000 | 0.863 |
Notes: *** p-value < 0.01; ** p-value < 0.05; * p-value < 0.10 |
Z- score shows that there is no any significant effect of (gender) becoming a male undergraduate or a female undergraduate for the relationship between career adaptability and life satisfaction. As a result, H5 was not supported and gender does not have any moderating effect between career adaptability and life satisfaction.
DISCUSSION
This research paper focuses on the effects of career adaptability, work volition and life satisfaction of undergrads who enrolled in Social Sciences and Humanities in State universities, Sri Lanka. Career adaptability is having a positive relationship with life satisfaction of undergraduates and first hypothesis is supported. Parola, & Marcionetti (2022) stated that career adaptability is a critical factor to accomplish positive adaptation results of life satisfaction among university undergraduates. Cabras & Mondo (2018) suggested that university undergraduates who are firmly known about career adaptability are highly satisfied with their life and it inspires their willingness to work. This further confirm the existing career construction model of adaptation (Savickas & Porfeli, 2012). However, the results of the research brought a strange outcome in the regression analysis the relationship between career adaptability and life satisfaction has only 19.6% contribution. That implies there are other unknown predictors influence on life satisfaction of undergraduates which was out of the scope of this research paper. According to the analysis all first three hypotheses were supported and recognized work volition has a positive moderate effect with career adaptability, and undergraduates’ perceived life satisfaction. his finding projects that at least one of the potential reasons that those with higher career adaptability are more confident in undergraduates’ willingness to work greater feelings of life satisfaction. Similarly, fourth hypothesis was supported, as work volition partially mediated the relationship between career adaptability and life satisfaction. This implies to indicate that those with higher career adaptability felt more satisfied life, impart because of an increased sense of willingness to work. Even though this mediating effect related findings are new it also supported by previous literature (Jadidian & Duffy, 2012). These findings enable to understand why work volition is so useful to the perceived life satisfaction of undergraduates and also emphasize the need to explore more potential reasons for these relations given why work volition acted only as a partial mediator.
Another intention of this research paper was to examine whether gender differences examined and reported for career adaptability to aid in the understanding of the different perceptions in the capacity of making occupational choices among two groups. According to the findings of this research there’s no any moderating effect of gender. Therefore, gender does not have significant influence in career adaptability or life satisfaction. Hence, it supports certain empirical findings which indicated that men and women have been found to be similar in their overall levels of life satisfaction(Diener, et.al.,1999), A study conducted among 3rd and 4th year undergraduates in the Rajarata university shows that there is no significant difference between gender on their life satisfaction also produce similar results(Weerasinghe & Fernando 2018).Zeng et al. (2022) stated in their study conducted among Chinese university students, that gender moderates career adaptability and life satisfaction which concludes that gender factor’s effect will vary according to the context.
CONCLUSION
In conclusion this research paper used to recognize the effects of career adaptability, work volition, and gender on social sciences and humanities undergraduates’ life satisfaction within state universities, Sri Lanka. The research was a quantitative study which was conducted on with 174 undergraduates of faculty of social sciences and humanities (98 male, 76 female) in state universities in Sri Lanka. All the participants participated in this study voluntarily. Participants ranged in age between 24 and 27 years and all are final year undergraduates. Career Adaptability Scale, Life Satisfaction Scale, work volition scale was used to develop the measurement tool (questionnaire) in this study. After the data cleaning procedure, the data is successfully used for further analysis. Descriptive statistics, Pearson correlation, simple regression analysis were performed to examine the effect of the total score of career adaptability and subscale scores of career adaptability of undergraduates on perceived life satisfaction. All analyses were conducted using SPSS version 22 and AMOS. Additionally, all the validity and reliability issues were examined and adjusted the models until they bring desirable model fit indices. First three hypotheses were supported with the Pearson correlation analysis. Hypothesis 04 also supported and it denotes that work volition partially mediates career adaptability and life satisfaction by performing bootstrapping method in AMOS. Another critical finding of this research was that the gender does not have any moderating effect on the relationship between career adaptability and life satisfaction. Hence, fifth hypothesis was not supported.
PRACTICAL IMPLICATIONS
Descriptive statistics disclosed that female undergraduates are less aware about the relevance of degree programme for their future occupations. Further, the relationship between career adaptability, work volition and life satisfaction are possessing moderate positive relationship. The findings of the present study underline that importance of career counseling for undergraduates that state universities should pursue four dimensions of career adaptability (career concern, control, curiosity, & confidence) which positively enhance the life satisfaction of the undergraduates. The result of this research shows that total career adaptability only 19.6% make an influence on life satisfaction of the university undergraduates. It is worthwhile to further examine what are the other factors that cause an impact on undergraduates’ life satisfaction.
REFERENCES
- Ariyawansa, R. (2013). Employability of Graduates of Sri Lankan Universities. Sri Lankan Journal of Human Resource Management. 2. 10.4038/sljhrm.v2i1.5107.
- Brown, S. D., & Lent, R. W. (2019). Social cognitive career theory at 25: Progress in studying the domain satisfaction and career self-management models. Journal of Career Assessment, 27(4), 563-578.
- Byrne, B. M. (2009). Structural equation modeling with Mplus: Basic concepts, applications, and programming. routledge.
- Cabras, C., & Mondo, M. (2018). Future orientation as a mediator between career adaptability and life satisfaction in university students. Journal of Career Development, 45(6), 597-609.
- Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71 75.
- Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological bulletin, 125(2), 276.
- Duffy, R. D., Diemer, M. A., Perry, J. C., Laurenzi, C., & Torrey, C. L. (2012). The construction and initial validation of the Work Volition Scale. Journal of Vocational Behavior, 80(2), 400-411.
- Duffy, R. D., Diemer, M. A., & Jadidian, A. (2012). The development and initial validation of the Work Volition Scale–Student Version. The Counseling Psychologist, 40(2), 291-319.
- Duffy, R. D., Bott, E. M., Torrey, C. L., & Webster, G. W. (2013). Work volition as a critical moderator in the prediction of job satisfaction. Journal of Career Assessment, 21(1), 20-31.
- Duffy, R. D., Autin, K. L., & Bott, E. M. (2015). Work volition and job satisfaction: Examining the role of work meaning and person–environment fit. The Career Development Quarterly, 63(2), 126-140.
- Douglass, R. P., & Duffy, R. D. (2015). Strengths use and life satisfaction: A moderated mediation approach. Journal of Happiness Studies, 16(3), 619-632.
- Dwivedi, A., & Rastogi, R. (2016). Future time perspective, hope and life satisfaction: A study on emerging adulthood. Journal of Business Research, 5(1), 17-25.
- Fujita, F., Diener, E., & Sandvik, E. (1991). Gender differences in negative affect and well-being: the case for emotional intensity. Journal of personality and social psychology, 61(3), 427.
- Gunasekara, N.S. and Jayasekara, A.J.,(2021) the impact of happiness on the academic performance of undergraduates.(an investigation of undergraduates of the faculty of humanities and social sciences, University of Ruhuna, Sri Lanka). International Journal of Humanities, Arts & Social Studies (IJHAS), 6(3).
- Haring, M. J., Stock, W. A., & Okun, M. A. (1984). A research synthesis of gender and social class as correlates of subjective well-being. Human relations, 37(8), 645-657.
- Huebner, E. S., Valois, R. F., Paxton, R. J., & Drane, J. W. (2005). Middle school students’ perceptions of quality of life. Journal of Happiness studies, 6(1), 15-24.
- Jadidian, A., & Duffy, R. D. (2012). Work volition, career decision self-efficacy, and academic satisfaction: An examination of mediators and moderators. Journal of Career Assessment, 20(2), 154-165.
- Liyanage, P., Kumara, U., & Withanawasam, M. (2016). Employability of the Management Graduates in Sri Lanka: A case study.
- Manathunga, M.M.S.U. and Kappagoda, U.W.M.R.S.S.C.B., 2020. Factors affecting the life satisfaction of undergraduates in Rajarata University of Sri Lanka.
- Neto, F., & Barros, J. (2007). Satisfaction with life among adolescents from Portuguese immigrant families in Switzerland. Swiss Journal of Psychology, 66(4), 215-223.
- Pallant, J. (2005). SPSS Survival Manual; a Step by Step Guide to Data Analysis Using SPSS Version 12, second ed. Open University Press, UK.
- Parola, A., & Marcionetti, J. (2022). Career decision-making difficulties and life satisfaction: The role of career-related parental behaviors and career adaptability. Journal of Career Development, 49(4), 831-845.
- Paschali, A., & Tsitsas, G. (2009). Stress and life satisfaction among university students-a pilot study. Annals of General Psychiatry. Retrieved July 6, 2011 from http://www.annals-general-psychiatry.com/content/9/S1/S96.
- Ratnayake, R. M. C. S., & Elvitigala, D. Y. C. (2020). A Study on Career Aspirations of Undergraduates in Sri Lanka. In Proceedings of the International Conference on Business & Information (ICBI).
- Savickas, M. L. (1997). Career adaptability: An integrative construct for life‐span, life‐space theory. The career development quarterly, 45(3), 247-259.
- Savickas, M. L. (2002). Career construction. Career choice and development, 149, 205.
- Savickas, M. L. (2005). The theory and practice of career construction. Career development and counseling: Putting theory and research to work, 1, 42-70.
- Savickas, M. L., & Porfeli, E. J. (2012). Career Adapt-Abilities Scale: Construction, reliability, and measurement equivalence across 13 countries. Journal of vocational behavior, 80(3), 661-673.
- Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: new procedures and recommendations. Psychological methods, 7(4), 422.
- University grant commission (2022). Sri Lanka university statistics 2022 https://www.ugc.ac.lk/downloads/statistics/stat_2022/Chapter%203.pdf
- Weerasinghe, I.M.S. and Fernando, R.L.S., 2018. University facilities and student satisfaction in Sri Lanka. International Journal of Educational Management.
- Weligamage, S. S. (2007). Gender and Type of Residence as Determinants of Undergraduates’ Academic Performance.
- Wood, W., Rhodes, N., & Whelan, M. (1989). Sex differences in positive well-being: A consideration of emotional style and marital status. Psychological bulletin, 106(2), 249.
- Yatigammana, K., & Wijayarathna, G. (2021). Students’ Perceptions of Online Lecture Delivery Modes: Higher Education During Covid-19 Pandemic and Beyond. International Journal of Emerging Technologies in Learning (iJET), 16(21), 58-73.
- Zeng, Q., He, Y., Li, J., Liang, Z., Zhang, M., Yi, D., & Quan, J. (2022). Hope, future work self and life satisfaction among vocational high school students in China: The roles of career adaptability and academic self-efficacy. Personality and Individual Differences, 199, 111822.