97 AUTONOMY AS A PERSONAL RESOURCE FOR STUDENTS OCCUPATIONAL WELL-BEING Kristina Paradnikė1, Rita Bandzevičienė Mykolas Romeris University, Lithuania Abstract. Background. The awareness of resources that help to overcome life challenges and flourish even in the conditions of uncertainty is critically important for young individuals transitioning from school to labor market. Autonomy, as self-governance, based on the basis of personal interests, integrated goals and values, is linked with a number of positive constructs. Those include performance, creativity, greater sense of personal reward and energy, engagement in pro-social activities and etc. Thus, autonomy might be a promising personal resource for successful functioning and occupational well-being manifested as satisfaction with life, engagement and academic major satisfaction. Purpose. The purpose of the study was to analyze the role of students’ autonomy when predicting satisfaction with life, engagement and academic major satisfaction. Method. The sample consisted of 148 college students (97.3% male, 2.7% female; mean age 19.69 ± 1.30). The Short version of Utrecht Work Engagement Scale – student version (Schaufeli et al., 2002), Satisfaction With Life Scale (Diener et al., 1985), Academic Major Satisfaction Scale (Nauta, 2007) and Dis- positional Index of Autonomous Functioning scale (Weinstein et al., 2012) were used in the study. Results. Only one of the components of autonomy, authorship/self-con- gruence in particular, had significant positive relationship with study variables and was a significant predictor of study engagement, satisfaction with life and academic major satisfaction. Conclusion. Our findings suggest that at least to some extent au- tonomy might serve as an important resource of students’ well-being while struggling in academic settings. Keywords: autonomy, engagement, academic major satisfaction, satisfaction with life, students. 1 Address for correspondence: Mykolas Romeris University, Faculty of Social Technologies, Institute of Psychology, Ateities st. 20, LT-08303 Vilnius, Lithuania, Phone: (8 5) 271 4625 Fax: (8 5) 267 6000, E-mail: kristina.paradnike@gmail.com. SCIENTIFIC PUBLICATIONS International Journal of Psychology: Biopsychosocial Approach 2015 / 17 ISSN 1941-7233 (Print), ISSN 2345-024X (Online) http://dx.doi.org/10.7220/2345-024X.17.6 98 Kristina Paradnikė, Rita Bandzevičienė INTRODUC TION Today, the complexity of reality results in limitations on human ca- pacities to control themselves and the circumstances of their lives. Indi- viduals as well as the world they live in constantly experience change and unpredictability (Pryor, 2010). Individuals can no longer plan to be working 30 years developing a career within the boundaries of one job or even one organization (Savickas, 2012). Thus, the awareness of resources that help to overcome life challenges and flourish even in the conditions of uncertainty is critically important. We believe that autonomy might serve as a personal resource that is linked to students’ occupational well- being manifested as satisfaction with life, engagement and academic major satisfaction. Although the topic of human autonomy has been under discussion for a substantially long time (Ryan & Deci, 2006), there is enough evidence to believe it still might play an important role in this age of chaos and possibilities brought on by globalization and digital revolution. Hence, the purpose of the study was to reveal the role of students’ autonomy when predicting satisfaction with life, engagement and academic major satisfaction. BACKGROUND Psychological Resources. In response to current labor market chal- lenges, there are many recent attempts to define possible personal or contextual resources that are necessary for performance, career sat- isfaction and optimal functioning. Hirschi (2012) summarizes various constructs of career self-management behaviors and proposes four criti- cal career resources which are necessary for career development in the modern context: human capital resources (e.g. education, transferable skills, and cognitive ability), social resources (e.g. networks and social support), identity resources (e. g. self-concept clarity, goal congruence, and goal clarity) and psychological resources (e.g. optimism, hope, and self-efficacy). In spite of the variety of attempts to explain resources, it is now clear that people need certain resources to adapt (Savickas, 2012) and they strive to obtain, protect, and foster those resources they value (Hobfoll, 2012). 99 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach Previous studies suggest that various constructs might serve as psychological resources in predicting work and career behavior and outcomes as well as higher psychological functioning. For example, such resources devoted to coping with uncertainty as optimism, flex- ibility, persistence, curiosity and risk taking are linked with students’ career exploration and certainty with career decisions (Kim, Jang, Jung, Lee, Puig, & Lee, 2014); hope is linked with students’ psychological well- being (Shorey, Little, Snyder, Kluck, & Robitschek, 2007); finally, enhanc- ing graduates’ career adaptability can increase their chances for finding a qualitatively good job (Koen, Klehe, & Van Vianen, 2012). It is evident that students benefit from a variety of positive constructs that serve as resources in career development. Accordingly, we propose that auton- omy might be a significant psychological career resource and play an important role in students’ occupational well-being. Autonomy as a Resource. Autonomy, like previously mentioned psy- chological resources (e.g. hope, flexibility, or adaptability), has a huge impact on personality functioning and wellness (Ryan & Deci, 2006). Ryan and Deci (2006) define autonomy as regulation by the self or as self-governance, while its opposite, heteronomy, refers to controlled regulation or regulation that occurs without endorsement from oneself (Ryan & Deci, 2006). Humans are active and growth-oriented organisms and they possess a natural developmental tendency toward autonomy (Deci & Ryan, 2000). Autonomous individuals tend to regulate their be- havior in congruence with their interests, goals and values, and they have a sense of choice about their behavior and a sense of control of their ac- tions (Weinstein & Ryan, 2011). It is evident that autonomy is linked with a number of positive constructs such as creative thinking (Liu, Zhang, Zhang, Lee, Wang, & Brownell, 2013), greater sense of personal reward and energy (Weinstein, Przybylski, & Ryan, 2012), test performance (Van- steenkiste, Simons, Lens, Sheldon, & Deci, 2004), engagement in pro- social activities (Gagné, 2003) and etc. Thus, naming autonomy as one of the promising personal or psychological career resources seems quite reasonable since the evidence suggest that autonomy is linked with a diversity of positive consequences. Of those possible consequences, we are particularly interested in students’ satisfaction with life, study 100 Kristina Paradnikė, Rita Bandzevičienė engagement, and satisfaction with academic major. These constructs in- dicate students’ occupational well-being and are likely to have an impact on students’ career development. Engagement and Autonomy. The concept of study engagement rises from definition and operationalization of work engagement (Schaufeli, Salanova, González-Romá, & Bakker, 2002). Analogous to work en- gagement, study engagement is defined as positive and fulfilling state of mind and is characterized by three components: vigor (being full of energy while studying), dedication (being strongly involved and ex- periencing a sense of enthusiasm while studying) and absorption (con- centrating totally and being fully immersed in one’s studies) (Schaufeli et al., 2002). Previous studies have mainly focused on a variety of organiza- tion-related resources that facilitate work engagement such as support- ing employees’ autonomy, giving performance feedback, and providing opportunities for development (Freeney & Fellenz, 2013; Schaufeli, Bak- ker, & Van Rhenen, 2009). Studies have proved the benefits of contextual and personal factors that might influence study engagement as well. For instance, positive emotions boost study engagement through such per- sonal resources as academic self-efficacy, study-related hope and study- related optimism (Ouweneel, Le Blanc, & Schaufeli, 2011); such resource as ability to cope proactively alleviates the impact of stress on study en- gagement (Gan, Yang, Zhou, & Zhang, 2007); task autonomy and teacher support enhance study engagement (Salanova, Schaufeli, Martínez, & Bresó, 2010) and etc. In accordance to the notion that autonomy support is positively linked with both study and work engagement (Salanova et al., 2010; Freeney & Fellenz, 2013; Schaufeli et al., 2009), we hypothesize that autonomy is an important personal resource itself and is a predictor of study engagement. Academic Major Satisfaction and Autonomy. In organizational behav- ior research, the importance of career success, both for individuals and organizations, is well-established. Subjective career success is usually operationalized by self-referent criteria such as individual’s satisfaction of current career or job situation, goals and aspirations. Also, individuals 101 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach evaluate their career success in reference to the expectations and out- comes attained by other people and in reference to their personal aspi- rations (Heslin, 2003). However, according to Nauta (2007), for students, satisfaction with their academic major is a more adjacent construct to evaluate. Academic major satisfaction represents global satisfaction with one’s chosen major and is operationalized as happiness with aca- demic major and unwillingness to change it (Nauta, 2007). Previous studies suggest that career-related optimism (McIlveen, Beccaria, & Burton, 2013) and increased ability to make occupational choices de- spite perceived constraints lead to greater academic major satisfaction (Jadidian & Duffy, 2012). Also, increased career decision self-efficacy is a significant predictor of self-determined motivation, satisfaction with the course, and satisfaction with the major (Komarraju, Swanson, & Na- dler, 2014). We presume that more autonomous students also make more autonomous career choices, which results in higher satisfaction with chosen specialties. In other words, we hypothesize that greater au- tonomy will predict higher academic major satisfaction. Satisfaction with Life and Autonomy. Theoreticians and practitioners urge to find and evaluate the most important indicators and factors of individual well-being (Diener, Oishi, & Lucas, 2003). One of those indica- tors is general life satisfaction, which represents how individuals assess their satisfaction with life as a whole according to their chosen criteria (Diener, Emmons, Larsen, & Griffin, 1985). There are thousands of stud- ies where life satisfaction and both its antecedents and its outcomes are investigated. However, only a few measure the links between autonomy and satisfaction with life. The results of those few studies indicate the importance of autonomy and autonomy support to happiness and well-being. For example, greater autonomy is linked with greater posi- tive affect, self-esteem, life-satisfaction, sense of clear meaning in life, and value for personal growth (Weinstein et al., 2012). Also, autonomy is one of the universal, basic needs (Ryan & Deci, 2006). The perception of significant support for this need by others results in higher subjec- tive well-being (Ratelle, Simard, & Guay, 2013) and life satisfaction (Nie- miec, Lynch, Vansteenkiste, Bernstein, Deci, & Ryan, 2006). In addition, more autonomous students experience higher levels of well-being on 102 Kristina Paradnikė, Rita Bandzevičienė daily basis (Weinstein et al., 2012). With regard to previous studies, we hypothesize that autonomy might be a predictor of students’ satisfac- tion with life. R ATIONALE OF CURRENT STUDY Occupational well-being of employees is operationalized as job sat- isfaction, low level of emotional exhaustion and job-related enthusiasm (Zacher, Jimmieson, & Bordia, 2014; Cheung & Lun, 2015; Li, Xu, Tu, & Lu, 2014). Based on this operationalization, we propose that high level of study engagement, satisfaction with academic major, and students’ satisfaction with life are three noteworthy indicators of students’ occu- pational well-being. Since study engagement is linked with students’ academic performance (Salanova et al., 2010), intrinsic motivation (Siu, Bakker, & Jiang, 2014), achievement (Bigna et al., 2014), and satisfaction with life (Mokgele & Tothmann, 2014), information about the anteced- ents of engagement, as an indicator of occupational well-being, seems to be crucial. In addition to engagement, satisfaction with life and sat- isfaction with academic major might also be taken into consideration when representing students’ occupational well-being. Given that life satisfaction is related to important career outcomes, such as career sat- isfaction, performance, turnover intentions (Erdogan, Bauer, Truxillo, & Mansfield, 2012) and college retention (Frisch et al., 2005), the impor- tance of exploring possible antecedents of satisfaction with life seems to be unquestionable. In addition, students’ satisfaction with academic major is another important construct when considering occupational well-being. It represents subjective career success, when job (or career) satisfaction is too distant for students to evaluate and is also connected to a variety of positive outcomes such as performance and grades (Nauta, 2007). To conclude, we suggest that high level of study engage- ment, satisfaction with academic major, and students’ satisfaction with life indicate occupational well-being of students. The purpose of the cur- rent study is to explore the links between autonomy, as a resource, and those three constructs. 103 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach ME THOD Par ticipants The participants were 148 students from The Faculty of Electronics and Informatics of Vilniaus kolegija/University of Applied Sciences. The sample consisted of students awarding Professional Bachelor’s degree in Informatics, Informatics Engineering, Electronics Engineering, Com- puter Engineering and Telecommunications Engineering. Since the ab- solute majority of faculty students are male, the sample was dominated by male students (97.3 % male, 2.7 % female students). The age of par- ticipants ranged from 18 to 26 (M = 19.69, SD = 1.30). Among the par- ticipants, 12.20 % have had work experience in their occupational field, 68.70 % have worked in some other field, and only 19 % of participants had no work experience. Procedure Data collection was conducted in December, 2014. The administra- tion of the institution was informed about the date, time and procedure of the research. All participants were informed that participation was voluntary. The questionnaires were administered by researchers and were completed in lectures during regular lecture hours. The partici- pants were not paid for participation. Measures The Lithuanian versions of the instruments were prepared with per- mission from the authors of the measures. After translation into Lithu- anian using the translation/back-translation procedure, Confirmatory Factor Analysis (CFA) with the Maximum Likelihood estimation in Mplus 6 (Muthén and Muthén, 1998–2010) was performed in order to check the factor structure of the Lithuanian version of the measures. Model fit was ascertained using various indices (Byrne, 2012): the Comparative Fit Index (CFI) and the Tucker-Lewis Index (TLI) should exceed .90, and the Root Mean Square Error of Approximation (RMSEA) should be less than .08. Study engagement was measured with the short version of Utrecht Work Engagement Scale – student version (UWES-S-9; Schaufeli et al., 2002) that consists of three subscales: (a) vigor (3 items), a sample item is “When I’m doing my work as a student, I feel bursting with energy”, 104 Kristina Paradnikė, Rita Bandzevičienė (b) dedication (3 items), a sample item is “My studies inspire me”, and (c) absorption (3 items), a sample item is “I am immersed in my stud- ies.” All items were scored on a seven-point Likert scale from 0 (never) to 6 (always/every day). Cronbach’s alphas were .72 for vigor, .80 for dedica- tion and .70 for absorption subscale. The results of CFA indicate that the three-factor structure (with correlation between two items) provided an adequate fit to the data, χ2 = 30.596 (p < .05), df = 23; CFI = .987, TLI = .980; RMSEA = .047 [.001; .088]. Satisfaction with life was measured with the Satisfaction With Life Scale (SWLS; Diener et al., 1985) that consists of 5 items. A sample item is “I am satisfied with my life.“ Subjects responded to items using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Re- sponses were summed up to produce a total SWLS score, with higher scores indicating more life satisfaction. The Cronbach’s alpha in the pre- sent study was .81. The results of CFA indicate that the one-factor struc- ture provided an adequate fit to the data, χ2 = 6.568 (p < .05), df = 5; CFI = .994, TLI = .988; RMSEA = .046 [.001; .130]. Satisfaction with academic major was assessed with the Academic Major Satisfaction Scale (AMSS) developed by Nauta (2007). The scale consists of six items with a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). A sample item is “Overall, I am happy with the major I’ve chosen.” Total scores were calculated by aver- aging responses to the six items. Cronbach’s alpha was .88 in this study. The results of CFA indicate that the one-factor structure (with correla- tion between two items) provides an adequate fit to the data, χ2 = 5.783 (p < .05), df = 7; CFI = 1.000, TLI = 1.005; RMSEA = .001 [.001; .090]. The autonomy of students was measured with the Dispositional Index of Autonomous Functioning scale (IAF, Weinstein et al., 2012) which con- sists of three subscales: authorship/self-congruence (5 items, e.g. “My decisions represent my most important values and feelings“), interest- taking (5 items; reversed; e.g. “I am interested in understanding the rea- sons for my actions“), and susceptibility to control (5 items, e.g. “I believe certain things so that others will like me“). All items were scored on a five- point Likert-type scale from 1 (not at all true) to 5 (completely true). Higher means of the authorship/self-congruence and interest-taking subscales and lower scores of susceptibility to control subscale indicate greater autonomy. Cronbach’s alphas were .80, .87, and .71, respectively. The re- 105 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach sults of CFA indicate that the three-factor structure (with correlation be- tween two pairs of items) provides an adequate fit to the data, χ2 = 147.31 (p > .05), df = 85; CFI = .926, TLI = .909; RMSEA = .070 [.051; .089]. RESULTS Table 1 shows means, standard deviations, and correlations among all the study variables. Authorship/self-congruence was positively re- lated to all study variables: vigor (r = .48, p < .01); dedication (r = .44, p < .01); absorption (r = .38, p < .01); satisfaction with life (r = .33, p < .01), and academic major satisfaction (r = .21, p < .01). Neither susceptibility to control nor interest-taking had significant correlations with any study variables, except with each other (r = −.46, p < .01) and authorship/self- congruence (respectively r = −.26, p < .01, and r = .19, p < .05). Table 1. Summar y Data and Intercorrelations Among all Variables 1 2 3 4 5 6 7 8 1. Vigor − .71** .69** .45** .36** .48** − .10 .02 2. Dedication − .59** .40** .58** .44** − .14 .13 3. Absorption − .35** .35** .38** − .15 .15 4. SWLS − .33** .33** − .04 − .12 5. AMSS − .21** − .01 − .01 6. Authorship / self-congruence − − .26** .19* 7. Susceptibility to control − − .46** 8. Interest-taking − M 2.72 3.10 2.64 21.61 3.84 3.30 2.93 3.07 SD 1.08 1.15 1.12 6.35 0.76 0.70 0.76 1.02 Note. SWLS − Satisfaction With Life Scale (Diener et al., 1985); AMSS − Academic Major Satisfaction Scale (Nauta, 2007). N = 148 * p < .05, **p < .01. We predicted that autonomy would serve as a personal resource and have a positive effect on study engagement, satisfaction with life and academic major satisfaction. Regression analyses were used to examine the relation of the autonomy dimensions to indicators of students’ oc- cupational well-being. To decrease the amount of variance explained by 106 Kristina Paradnikė, Rita Bandzevičienė non-significant correlates, we included only the variables significantly related to factor variables. Specifically, only the authorship/self-congru- ence was entered to regression equation. We expected to find significant interactions between the authorship/self-congruence and other study variables. Authorship/self-congruence was a significant predictor of vigor (R 2 = .23, F(1, 146) = 42.44, p < .01, 95% confidence interval (CI) [.11, .35]); dedication (R2 = .20, F(1, 146) = 35.60, p < .01, 95% CI [.09, .32]); and ab- sorption (R2 = .14, F(1, 146) = 24.39, p < .01, 95% CI [.04, .24]). Also, author- ship/self-congruence accounted for significant variance in satisfaction with life (R2 = .11, F(1, 146) = 17.52, p < .01, 95% CI [.02, .20]) and academic majors satisfaction (R 2 = .05, F(1, 146) = 3.88, p < .05, 95% CI [.02, .11]) (see Table 2). However, it appears that the predictive value of authorship/self- congruence is the highest when predicting vigor and dedication, as in all other cases the accounted variance is lower than 20 percent. Table 2. Summar y of Multiple Regression Analyses Predicting Academic Major Satisfaction, Satisfaction with Life, and Study Engagement Predictor Factor β B R 2 Equation 1: Authorship/self-congruencea Academic major satisfactionb .21 0.23 .05* Equation 2: Authorship/self-congruencea Satisfaction with lifec .33** 2.97 .11** Equation 3: Authorship/self-congruencea Engagement: Vigord .48** 0.73 .23** Equation 4: Authorship/self-congruencea Engagement: Dedicatione .44** 0.73 .20** Equation 5: Authorship/self-congruencea Engagement: Absorptionf .38** 0.60 .14** Note. β – estimated value of standardized regression coefficient (Beta); B – es- timated value of unstandardized regression coefficient; R 2 – R squared (coefficient of determination). N = 148. The table depicts 5 separate regression equations, where Authorship/self-congru- ence (a) is a predictor of outcome variables (b, c, d, e, f ). * p < .05, **p < .01. 107 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach Since the assumption of the study was that autonomy would serve as a resource for students’ study engagement, satisfaction with life and academic major satisfaction as indicators of occupational well-being, we performed a multivariate analysis with the Maximum Likelihood estimation in Mplus 6 (Muthén and Muthén, 1998–2010) in order to check whether autonomy predicts other study variables. We included only authorship/self-congruence as a predictor of factor variables. We checked the fit of two possible models. Model 1 included authorship/ self-congruence as a predictor and study engagement (indicated by vigor, dedication, and absorption), satisfaction with life and academic major satisfaction as outcome variables. Model 2 excluded academic major satisfaction as an outcome variable since in the linear regression analysis the predictive value of authorship/self-congruence accounted only for 5 percent of the variance of academic major satisfaction. Table 3 shows the results of comparison of the both models. Table 3. Comparison of Model 1 and Model 2 Model χ2 Δχ2 df CFI TLI RMSEA [90% CI] Model 1 26.85 (p < .05) 25.86 6 .94 .86 .153 [.097−.214] Model 2 0.99 (p > .05) 4 1 1 .001 [.001−.048] Note. χ2 – chi-square test statistic; Δχ2 – delta chi square; df – degrees of free- dom; CFI – Comparative Fit Index; TLI − Tucker-Lewis Index; RMSEA – root mean square error of approximation; CI = confidence interval. N = 148. Figure 1. Results (standardized estimates) of the structural equation modeling predicting study engagement and satisfaction with life (Model 2). N = 148. **p < .01. Study Engagement Authorship/ Self-congruence Satisfaction with Life Vigor Dedication Absorption .39** .56** .91** .80** .77** 108 Kristina Paradnikė, Rita Bandzevičienė Figure 1 represents the Model 2, which was more adequate as indi- cated by various indices: the Comparative Fit Index (CFI) and the Tucker- Lewis Index (TLI) should exceed .90, and the Root Mean Square Error of Approximation (RMSEA) should be less than .08 (Byrne, 2012). The results of Model 2 indicate that authorship/self-congruence positively predict both study engagement and satisfaction with life. Au- thorship/self-congruence accounts for 15 percent of variance of satisfac- tion with life and 31 percent of variance of study engagement. These results support the assumption that at least one dimension of autonomy might serve as a resource or a predictor of positive occupational out- comes of students. DISCUSSION Today, transition from the academic setting to the ‘real’ world of fluid careers requires more effort, deeper self-knowledge, and greater confi- dence than ever before (Savickas, 2012). Individuals need to be able to manage their careers and encounter job or career demands in a quite chaotic environment, which requires a lot of personal resources. The purpose of our study was to assess the role of such possible personal resource as autonomy when predicting students’ satisfaction with life, engagement and academic major satisfaction. Weinstein and colleagues (2012) suggest that autonomy includes interest-taking, absence of susceptibility to control and authorship or self-congruence (Weinstein et al., 2012). In our study, authorship or self- congruence was positively related to all study outcome variables. Also, authorship or self-congruence was a significant predictor of the facets of engagement (vigor, dedication, and absorption) and satisfaction with life both in the linear regression equations and in the structural equa- tion model. Thus, experiencing oneself as the author of behavior and being responsible for one’s actions might play a significant role in stu- dents’ satisfaction with life and study engagement. The results support the presumption that at least to some extent autonomy might serve as a resource or a predictor of positive occupational outcomes of students. The results of the current study are in line with previous studies, where autonomy was linked with various positive outcomes (Liu et al., 2013; Gagné, 2003; Vansteenkiste et al., 2004). 109 2015, 17, 97–115 p.International Journal of Psychology: A Biopsychosocial Approach However, without experimental or longitudinal studies, the causal- ity between variables is unclear. Also, although we predicted that higher levels of autonomy could predict higher levels of students’ engagement and life satisfaction, and the hypothesis was confirmed, it is not always clear whether well-being or life satisfaction is an outcome of resources or antecedent. In some studies, life satisfaction plays a mediating role between resources and outcomes or serves as a resource itself. For ex- ample, in some studies, the frequency of recognition and praise received by college students and their level of personal growth initiative is medi- ated by perceived life satisfaction (Stevic & Ward, 2008). On the contrary, in other studies, personal growth initiative is proven to be an antecedent of optimal functioning (Weigold, Porfeli, & Weigold, 2013) and predic- tor of if life satisfaction (Yang & Chang, 2014). Similarly, we assume that satisfaction with life might be a resource itself in some cases, and this should be taken in consideration while interpreting the results of our study. In addition, some studies prove that engagement is linked with career and job satisfaction in employees’ and students’ samples (Barnes & Collier, 2013; Høigaard, Giske, & Sundsli, 2012; Rayton & Yalabik, 2014; Sovet, Sang, Park, & Jung, 2014; etc.). Thus, it is possible that it could also predict academic major satisfaction and vice versa. Nevertheless, our findings suggest that to some extent autonomy might serve as a means to succeed in the conditions of the present-day changing world and in the times of changing career paths. The current study extends the exist- ing literature on career resources (Hirshi, 2012; King, 2004; Sturges, 2008; etc.) with a notion that autonomy is connected to well-being in the oc- cupational field in a sample of students. Limitations and Future Directions. The results and conclusions from the present study need to be considered in light of a number of limita- tions. Firstly, the study included participants from a narrow occupational field – computer and engineering sciences. In earlier studies it was argued that different occupational sectors could encounter different challenges (Bakker & Sanz-Vergel, 2013). Hence, it seems reasonable to investigate if the patterns found in the current study would replicate in different samples. Also, the sample of the current study contained a dispropor- tionate number of men. However, such a sample might seem to be novel since the studies of career field often include female-predominant samples of social science students (Duffy, Douglass, Autin, & Allan, 2014). 110 Kristina Paradnikė, Rita Bandzevičienė Nevertheless, gender is an important consideration in the career devel- opment area (Patton & Creed, 2001). Thus, future studies should consider samples with a more equal gender balance. Although the findings of the current study have provided some new insights into the links among autonomy, study engagement, and academic and life satisfaction, this study had the limitation of adopting a cross-sectional design. Career resources might change over time and the existence of resources in one area promotes the development of re- sources in the other areas (Hirschi, 2012). Thus, in future studies, a lon- gitudinal approach would be beneficial in understanding how the vari- ables change and develop over time. Also, an experimental approach could give evidence of causality between variables. Moreover, one possi- ble direction for future research could be expanding the current study to other career stages. This could establish a more complete understanding of the role of personal career resources during the life span. 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Šiandienos neapibrėžtumo ir neužtikrintumo sąlygomis nepaprastai svarbu suprasti, kurie ištekliai padeda įveikti gyvenimo sunkumus ir gerai pasiruošti konkuruoti darbo rinkoje. Autonomija, arba funkcionavimas vadovaujantis asmeniniais interesais, vertybėmis ir tikslais, gali būti reikšmingas asmeninis išteklius, susijęs su sėkmingu funkcionavimu akademinėje aplinkoje. Ankstesnių tyrimų duomenimis, autonomija susijusi su tokiais pozityviais konstruktais kaip atlikimas, kūrybiškumas, įsitraukimas į prosocialias veiklas ir kt. Taigi šiame tyrime keliama prielaida, kad autonomija susijusi su studentų profesinę gerovę atspindinčiais konstruktais – įsitraukimu į studijas, pasitenkinimu jomis ir gyvenimu. Tikslas. Siekta ištirti autonomijos ir studentų įsitraukimo į studijas, pasitenkinimo gyvenimu bei studijomis sąsajas. Tiriamieji ir metodai. Tyrime dalyvavo 148 kolegijos studentai (97,3 proc. vaikinų, 2,7 proc. merginų, kurių amžiaus vidurkis – 19,69, SD – 1,30). Tyrime naudoti instrumentai: Utrechto įsitraukimo į darbą skalė – trumpoji studentų versija (Schaufeli et al., 2002), pasitenkinimo gyvenimu skalė (Diener et al., 1985), Pasitenkinimo pasirinktu studijų dalyku skalė (Nauta, 2007) ir Dispozicinės autonomijos indekso skalė (Weinstein et al., 2012). Rezultatai. Teigiamai su kitais tyrimo kintamaisiais buvo susijęs tik vienas autonomijos komponentas – autorystė arba savikongruencija. Regresinė analizė atskleidė, kad autorystė arba savikongruencija buvo reikšminga ir prognozuojant studentų įsitraukimą į studijas, pasitenkinimą gyvenimu ir pasitenkinimą pasirinktomis studijomis. Išvados. Remiantis tyrimo rezultatais galima teigti, kad autonomija bent iš dalies yra reikšmingas išteklius, susijęs su studentų gerove akademinėje aplinkoje. Pagrindiniai žodžiai: autonomija, įsitraukimas, pasitenkinimas studijomis, pasitenkinimas gyvenimu, studentai. Received: May 15, 2015 Accepted: October 19, 2015