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Article

How Do Students Become Good Workers? Investigating the Impact of Gender and School on the Relationship between Career Decision-Making Self-Efficacy and Career Exploration

by
Shi Chen
1,
Huaruo Chen
1,2,
Hairong Ling
1 and
Xueying Gu
1,*
1
School of Education Science, Nanjing Normal University, Nanjing 210046, China
2
Center for Research and Reform in Education, Johns Hopkins University, Baltimore, MA 21286, USA
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(14), 7876; https://doi.org/10.3390/su13147876
Submission received: 16 June 2021 / Revised: 4 July 2021 / Accepted: 12 July 2021 / Published: 14 July 2021
(This article belongs to the Special Issue Sustainable Career Development)
Browse Figure
Versions Notes

Abstract

:
In the field of vocational psychology, career decision-making self-efficacy (CDMSE) and career exploration (CE) are considered the crucial factors for developing a sustainable career. This study investigated the relationship between CDMSE and CE among Chinese high-school students, as well as the moderating effects of gender and school. From 2019 to 2021, 24,273 students from 13 different high schools were recruited in the study (male = 15,050, female = 9223; urban schools = 12,327, rural schools = 11,946). The results showed that (i) male students scored significantly higher than female students in both CDMSE and CE, (ii) students from urban schools scored significantly higher than students from rural schools in both CDMSE and CE, (iii) CDMSE positively predicted CE, and (iv) school moderated the relationship between CDMSE and CE, with the effect of CDMSE on CE stronger among rural school students; a moderating effect of gender was not found. These findings indicate that promoting CDMSE can lead high-school students, especially rural school students, to engage more in CE to ensure sustainable career development under the protean and boundaryless career orientation.

1. Introduction

Sustainable careers were defined as “the sequences of an individual’s different career experiences, reflected through a variety of patterns of continuity over time, thereby crossing several social spaces, characterized by individual agency, herewith providing meaning to the individual” [1] (p. 7). According to the definition of sustainable careers, time, social space, agency and meaning are the four core elements. Time indicates the influences of various career activities and events occurring in the past, present and future; social space emphasizes the importance of external environments on sustainable careers; agency illustrates the impacts of individual differences on sustainable careers; and meaning represents that sustainable careers including both skills development and the meaning of career experiences [1,2]. From a sustainable career perspective, sustainable career development contributes to the personal survival and self-realization value [3]. While living in the ear of a boundaryless and protean career, individuals, especially teenagers, increasingly face the various challenges of developing career sustainability throughout their whole life [4,5]. High-school students are at the stage of exploration [6], which allows for diverse career exploration (CE) activities to promote career-related abilities to make crucial career decisions and identify their future career sustainability [7]. Under the new college-entrance examination policy in China since 2018, career-guidance education for high-school students has attracted more attention from career researchers, educators, and practitioners. Besides, the whole world is suffering from the COVID-19 pandemic, and the considerable changes in the environment have made career development more difficult for students [8]. While facing challenges and difficulties, high-school students urgently need career guidance from schools and family. However, for most Chinese high-school students and educators, career-guidance education is still in its infancy. Some issues about career guidance in China have been discussed, including a shortage of local theoretical career models and career assessments; a lack of professional career educators, practitioners, and counselors; and negative attitudes and beliefs toward career guidance [9]. In addition, compared with Western countries, Chinese society has many differences and unique difficulties, so no Western career education system can be copied completely.
According to the Social Cognitive Career Theory (SCCT), individual input, self-efficacy and environment are three pivotal factors in career development process [10]. The effectiveness of SCCT in promoting sustainable careers has been proved by previous studies [11]. While students try to transit school life to work life, career decision-making self-efficacy (CDMSE) is considered as a crucial factor for students to make appropriate career decisions and enhance career sustainability. CDMSE has been shown to predict the development of career interests in career-related activities [12], career goal formation [13], and engagement in CE activities [14]. A SCCT model of career self-management (CSM) considers career exploration as an adaptive mechanism of individual agency that allows individuals to strengthen career adaptabilities and manage adaptions in sustainable career development [15]. CE is viewed another vital factor for students to make sustainable career-related plans [16], and students who want to do so must actively engage in exploring career options and make subsequent career choices [17]. As mentioned above, sustainable career perspective emphasizes individual and environmental factors related to career development, both CDMSE and CE could be regarded as the individual factors, and the construct of the two factors are often related to the external environment. Numerous studies have concentrated on how CDMSE affects CE, and the positive relationship between them has been tested widely [18,19,20]. However, few studies have focused on that relationship in Chinese students, especially high-school students. Additionally, individual agency and social space have impacts on sustainable careers; therefore, we wonder if gender (male versus female) and school setting (urban versus rural) moderate the relationship between CDMSE and CE?
The main purpose of the present study was to investigate the relationship between CDMSE and CE among Chinese high-school students. Specifically, there were four goals: (i) testing the gender difference in CDMSE and CE, (ii) testing the school difference in CDMSE and CE, (iii) testing the moderating effect of gender on the relationship, and (iv) testing the moderating effect of school on the relationship. In general, this study develops and examines a model that posits to improve CE as the result of CDMSE, aiming to develop foundations of CE and career sustainability for Chinese high school students.

2. Research Theory and Hypothesis

2.1. Career Decision-Making Self-Efficacy

SCCT originated from Bandura’s social cognitive theory to further describe the impacts of self-efficacy in an individual’s career behaviors [21]. SCCT interprets the interaction effects between personal and environmental factors that contribute to career decisions, and it considers career decision-making as a process with different factors and choices [22]. In the SCCT model, CDMSE is identified as a vital construct in understanding individuals’ career decision-making processes [23]; it affects individuals’ sustainable career development, long-term targets, vocational identity, and other career behaviors [24]. CDMSE can be defined as an individual’s belief or confidence that they can make appropriate decisions related to their career development, and it has five dimensions: self-appraisal, gathering information, goal selection, planning, and problem-solving [25]. In various studies, CDMSE served as a crucial factor of an individual’s vocational behaviors and outcomes [26,27,28,29], and these findings demonstrate a link between sustainable career development and CDMSE. A meta-analysis showed a positive relationship between CDMSE and career development and a negative relationship between CDMSE and career indecision [30]. An individual with higher CDMSE could better understand various changes related to themself, adjust career behaviors, and have a stronger resolution toward difficulties [31,32]. CDMSE is especially important for high-school students given that adolescents are supposed to make critical career decisions [33]. High-school students with high confidence about their capacity to make sustainable career decisions would have more interest in setting career goals, devoting more time to CE, and probably making sustainable career decisions [34].
SCCT provides several factors that impact CDMSE, such as personal factors (e.g., age and gender), contextual factors (e.g., perceived social supports), and experiential factors (e.g., learning sources) [14]. Although there have been numerous investigations of the relationship between CDMSE and other variables, most did not account for gender in the CDMSE of high-school students, and the results of the few studies of gender difference in CDMSE were inconsistent. For example, Gu et al. investigated the CDMSE of Chinese high-school students and found no gender difference [35], and Jiang recruited undergraduate students from China and South Korea and detected no gender difference [36]. In contrast, according to Abdinoor, young women reported a higher level of CDMSE than young men [27], and according to Kim and Lee, male college students had higher confidence in career decision-making than female students [37]. Similar to gender difference, few studies have assessed the school difference (rural versus urban) in CDMSE. According to Anderson and Brown, there was no significant difference in CDMSE between urban and rural school students [38]. Another study also revealed that urban school students had the same level of CDMSE as rural school students [39]. In recent studies, researchers preferred to recruit participants from a single area (either urban or rural). Therefore, the present study was designed to separately investigate the impacts of gender and school in CDMSE.
Hypothesis 1a.
Male high-school students would score significantly higher than female high-school students in CDMSE.
Hypothesis 1b.
No school difference would be found in CDMSE.

2.2. Career Exploration

CE is also considered a pivotal factor that positively affects sustainable career development among high-school and university students [15]. It refers to an individual’s behaviors and thoughts that gather information related to the progress of their career development, and the two key components of CE are self-exploration and environmental exploration [40]. Self-exploration is an exploratory behavior that aims to clarify an individual’s characteristics including interests, skills, experiences, personality traits, values, abilities, and career development status [41]; environmental exploration is also an exploratory behavior, one that aims to clarify environmental characteristics including job paths, job requirements, education, and training [19]. Although CE behaviors occur at all ages and stages of career development, CE is considered to be most important during late adolescence and early adulthood as first significant life decisions are being approached [39]. There is a consensus in vocational psychology that adolescents engage more in CE; for example, research has indicated that adolescents (i.e., 10th-grade students) engage in more occupational exploration than do children (i.e., 6th-grade students) [42].
For high-school students, engaging more in CE would bring many benefits. It is expected that the higher the level of CE, the lower the level of career indecision [43]. High-school students who exhibit more CE behavior also tend to be more concentrated toward achievement goals [15]. CE is also negatively related to career anxiety; to avoid an increase in career anxiety, anxious students should explore their career environment more [17]. A positive relationship was found between CE and career adaptability, including the four elements of career concern, career curiosity, career confidence, and career control [44]: (i) CE activities could help individuals develop abilities to gather useful information in a different situation, thereby positively affecting career curiosity; (ii) CE helps individuals focus on their future careers, thereby promoting career concern; (iii) the information collected during CE can be used to make mature career decisions, thereby enhancing career control; and (iv) CE involves multiple career tasks, thereby providing chances for individuals to improve their career skills and confidence. In summary, encouraging high-school students to exhibit more CE behavior would help their sustainable career development in the long run [45].
Previous studies found gender differences in CE, with most findings showing that males had a significantly higher CE level than females [46,47]. However, few studies examined school setting differences. Meanwhile, CE was found to be associated with family socioeconomic status (SES), with students with higher SES having a higher CE level [48]. The present study is the first to investigate gender and school differences in CE among Chinese high-school students.
Hypothesis 2a.
Male high-school students would score significantly higher than would female high-school students in CE.
Hypothesis 2b.
Urban school students would score significantly higher than rural school students in CE.

2.3. Relationship between CDMSE and CE

Numerous studies have indicated a positive relationship between CDMSE and CE. For instance, Chiesa et al. recruited 280 Italian high-school students, and the results indicated that CE was positively related to CDMSE [34]. However, the relationship between CDMSE and CE has yet to attract the attention of Chinese career researchers and educators. Therefore, the present study also concentrates on the relationship between CDMSE and CE among Chinese high-school students. In the field of vocational psychology, gender is often studied as a moderator. For example, gender has a moderating effect on parenting styles and CDMSE [49,50]. It also has a moderating effect on the relationship between thinking style and CDMSE [51]. Although the moderating effect of gender on the relationship between CDMSE and CE is worth investigating, no study has done so. Based on the literature review, the study formed another three hypotheses.
Hypothesis 3.
CDMSE would positively predict CE.
Hypothesis 4.
School would moderate the relationship between CDMSE and CE.
Hypothesis 5.
Gender would moderate the relationship between CDMSE and CE.

3. Materials and Methods

3.1. Participants and Procedure

All participants were freshmen from 13 different high schools (10th-grade students) in Jiangsu Province, China. Six of the schools were in rural settings and seven were urban. The participants were recruited based on the following reasons. First, high-school students are in the CE stage, when they have various career-related tasks to complete. Second, the principles of these 13 high schools considered career education as necessary for students to develop careers and were interested in designing a native career-education system. From January 2019 to January 2021, when the first semester of the 10th grade ended, students in these schools were asked to voluntarily fill the questionnaires via a website link that the researchers set. Participants were informed that the data were collected only for scientific research and that their answers and personal information would be kept strictly confidential. Specifically, we used an anonymous survey to ensure the accuracy of the responses, and using an anonymous survey could reduce the effect of common-method variance [52]. The data with a response time of less than 10 min were removed. Ethical approval to conduct the investigation was granted by the authors’ departmental ethics committee.
Finally, 24,273 students (Mage = 15.27, SD = 0.34) were recruited in the present study. Of the entire sample, there were 5357 participants in 2019 (22.07%), 9133 in 2020 (37.87%), and 9783 in 2021 (40.30%); 15,050 participants were male (62.00%) and 9223 were female (38.00%); 12,327 (50.78%) participants studied in urban schools, and 11,946 (49.21%) studied in rural schools.

3.2. Instruments

3.2.1. Career Decision-Making Self-Efficacy Scale—Short Form

The Career Decision-making Self-efficacy Scale—Short Form (CDMSE-SF) was designed to assess individuals’ confidence in their ability to make appropriate decisions related to their career development [53]. CDMSE-SF was revised into a Chinese version by two bilingual academics with doctoral degrees using a blind translation-back-translation method, and the internal reliability coefficient for Chinese CDMSE-SF was 0.88 [54]. The Chinese CDMSE-SF was administrated in the present study (the details of Chinese CDMSE-SF can be seen in Appendix A Table A1), and it contains 25 items related to 5 subscales: (i) self-appraisal, (ii) gathering information, (iii) goal selection, (iv) planning, and (v) problem-solving. Sample items include, “Make a plan for your goals for the next five years” and “How confident are you that you could determine what your ideal job would be”. The participants were asked to rate the items using a 5-point Likert scale ranging from 1 (no confidence at all) to 5 (complete confidence). Higher scores indicated higher confidence in career decision-making. In the present study, the coefficient of internal consistency for each subscale ranged from 0.871 to 0.923, that for the whole scale was 0.914, and the correlations between all subscales ranged from 0.479 to 0.658 (p < 0.001).

3.2.2. Career Exploration Survey

The Career Exploration Survey (CES) was designed to assess individuals’ engagement in CE activities [55]. The survey was revised into a Chinese version, it was translated from the original English version by two Chinese master degree students with good English using a blind translation-back-translation method, the coefficient of internal consistency of the Chinese CE was 0.87, and the Confirmative Factor Analysis results supported the goodness-of-fit of construct validity was acceptable [56]. The Chinese CES was used in the present study (the details of Chinese CES can be seen in Appendix A Table A2), it consists of five items on self-exploration and six items on environmental exploration. Sample items include, “To what extent have you behaved in obtaining information on specific jobs or companies over the last three months” and “To what extent have you reflected on how your past integrates with your future career in the last three months”. The participants were asked to rate the items using a 5-point Likert scale ranging from 1 (does not apply) to 5 (fully applies). Higher scores indicated the more frequent exploration done by participants. In the present study, the coefficients of internal consistency for the self-exploration and environmental exploration scales were 0.846 and 0.813, respectively, and for the whole CES was 0.871. The correlation between the self-exploration and environmental exploration scales was 0.463 (p < 0.001).

3.3. Data Analysis

This study used SmartPLS (SmartPLS GmbH, Boenningstedt, Germany) and SPSS 23.0 (IBM, New York, NY, USA) to analyze all the data. First, SmartPLS was used to address the impact of common-method variance [57]. SPSS 23.0 was used to obtain descriptive statistics, correlation analysis, significance test of difference, and regression analysis among various variables; it was also used to analyze the reliability of the two measurements. SPSS Process was also used to test whether school and gender moderated the relationship between CDMSE and CE [58].

4. Results

4.1. Common-Method Variance Testing

Although we used an anonymous survey to avoid the impact of common-method variance, a negative impact may still exist. Partial least squares (PLS) can be used to address the issue of common-method variance. In the present study, we loaded all 36 items (25 from CDMSE-SF and 11 from CES) on the corresponding latent constructs, and the convergent validity was investigated via the average variance extracted (AVE). Table 1 gives the main PLS results. The values of AVE are higher than the critical value of 50%, meaning that the latent variables in the present model explained on average more than 50% of the variances of the corresponding indicators; and all the values of loading are higher than 0.50. Therefore, there was no significant effect of common-method variance in the present study.

4.2. Descriptive Statistics, Correlations, and Significance Test of Difference

The descriptive statistics and correlations among CDMSE and CE are given in Table 2. The skewness and kurtosis of all the variables range from −1 to 1, and the Shapiro–Wilk test was not significant (p > 0.05); therefore, we have not violated the statistical assumption of normality [59]. Regarding CDMSE scores, participants scored highest on problem-solving (M = 3.736, SD = 0.660) and lowest on gathering information (M = 3.178, SD = 0.835). All five CDMSE dimensions were positively correlated with each other (p < 0.001). Regarding participants’ CE scores, participants performed better in self-exploration (M = 3.793, SD = 0.522) than in environmental exploration (M = 2.915, SD = 0.448), and self-exploration was positively correlated with environmental exploration (r = 0.463, p < 0.001). CE was positively correlated with CDMSE (r = 0.508, p < 0.001).
The independent-samples t-test was used to explore the gender differences and school differences among all variables, and the Cohen’s d and effect size were also calculated [60]. Results indicated that gender differences were found for all the variables (see Table 3). Male students scored significantly higher than female students in the CDMSE and CE, supporting Hypotheses 1a and 2a.
School differences were also found in all variables (see Table 4). Participants from urban schools performed better than participants from rural schools in CDMSE and CE. Therefore, Hypothesis 2a was proved, but Hypothesis 2b was not supported.

4.3. Hierarchical Regression Analysis

This study separately tested the moderating roles of school and gender between CDMSE and CE. The results of hierarchical regression analysis are given in Table 5. Model 1 was the relationship between CDMSE and CE moderated by school. In step 1, CE was regressed on CDMSE and school (0 = urban school, 1 = rural school); in step 2, the interaction term of CDMSE multiplying school was entered into the regression model. The results indicated that the interaction effect of CDMSE and school was significant (β = −0.02, p < 0.001), and the adjusted R-square was significant (ΔR2 = 0.50, p < 0.001). The moderating role of school was examined. Model 2 was the relationship between CDMSE and CE moderated by gender. In step 1, CE was regressed on CDMSE and gender (0 = male, 1 = female); in step 2, the interaction term of CDMSE multiplying gender was entered into the regression model. However, the moderating role of gender was not significant (β = 0.00, p > 0.05). In summary, Hypotheses 3 and 4 were confirmed, but Hypothesis 5 was not supported.
Figure 1 shows the moderating effect of school on the relationship between CDMSE and CE. For students from urban schools, the changes in the relationship between CDMSE and CE were weaker than the changes for the students from rural schools.

5. Discussion

5.1. Gender Difference in Career Exploration and Career Decision-Making Self-Efficacy

In the present study, gender differences were found in all the variables. Regarding CDMSE, male high-school students scored significantly higher than female students in all subscales and the total scale of CDMSE-SF, suggesting that male high-school students are more confident in career decision-making than female students. The same results were also found in previous studies. Brew and Ngman-Wara investigated 273 senior high-school students from three schools, and the results indicated that male students had a higher CDMSE level [61]. Mau explained that in an Asian context, females have lower social status than males, and females are at a general disadvantage in making decisions, and also lack confidence in making career decisions [62]. Additionally, from the perspective of personality traits, male students’ personality traits were relatively stable and extraverted, which lead male students more positive and nimble in career-related activities, whereas female students’ personality traits were comparably unstable and introverted, which lead female students more negative and lacking in confidence in the process of career decision-making [63].
Regarding CE, male students also scored significantly higher, meaning that male high-school students engaged more in CE activities. The same findings were obtained in several other studies. Salim and Preston conducted surveys among 824 high-school students and found that boys scored significantly higher in CE than did girls [46]. An and Lee found that males recorded significantly higher scores in CE than did females [47]. It was shown that male students perceived more career barriers and less social support [64,65], therefore male students must engage more in CE to reduce career barriers and to search for more social support. Identifying gender differences in the CDMSE and CE of Chinese high-school students suggests the necessity and importance of developing specific career education depending on gender.

5.2. School Difference in Career Exploration and Career Decision-Making Self-Efficacy

In the present study, comparing CDMSE among different schools revealed that the CDMSE of urban high-school students was significantly higher than that of rural students. This finding is consistent with previous studies [63,66]. Based on SCCT, some contextual factors and experiential factors would impact the formation of CDMSE. Compared with rural school students, their urban peers have more advantages in perceived social support, family socioeconomic status, educational resources, etc., which would lead to a higher level of CDMSE [67]. Students from rural areas often experience more unique barriers to successful career readiness, including a lack of school and community resources, postsecondary educational chances, employment options, and access to professional services [38]. This study also found that urban students had a significantly higher level in CE than rural school students. It was considered that students from urban schools had higher family SES than students from rural schools, and higher-SES students would perceive lower resource scarcity and in turn adopt more adaptive career behaviors such as CE [48]. For these reasons, career educators and researchers should consider the needs of rural school students and be mindful of the unique career behaviors of students from different backgrounds.

5.3. Relationship between Career Exploration and Career Decision-Making Self-Efficacy

In the present study, a significant positive relationship between CE and CDMSE was found, and CDMSE was a significant predictor of CE among high-school students. Most previous studies reported similar results [61,68,69]. Furthermore, this study found that when students came from rural schools, the improvement of CE was more obvious, whereas when students came from urban schools, the improvement of CE was relatively small. This finding indicated that while enhancing CDMSE via some approaches, it seems that rural school students are more likely to improve CE. Some factors other than CDMSE probably affect CE, such as personality traits, anxiety, career barriers, future time perspective, and some external factors [70]. However, the moderating effect of gender was not found on the relationship between CDMSE and CE. The results of the independent-samples t-test indicated that male students had higher scores in CDMSE and CE than female students, the improvement of CE was the same regardless of male or female. Although male students and female students may have different career barriers or social support in the process of career decision-making, all students share the similar attitude and belief to develop a sustainable career [71]; therefore, while career interventions were delivered to all the high school students to strengthen their CDMSE, the level of CE of both male students and female students would be increased by the same level.

5.4. Implications for Practice

The present study yielded four main results: (i) male high-school students performed better in CDMSE and CE than female students, (ii) students from urban schools had a higher level of CDMSE and engaged more in CE compared to students from rural schools, (iii) CDMSE was a significant predictor of CE, and (iv) school played a moderating role in the relationship between CDMSE and CE. Based on these findings, this study makes several suggestions to further promote CE and career sustainability of Chinese high-school students.
Promoting CDMSE is a possible way to strengthen CE. A meta-analysis indicated that a career intervention had positive effects in enhancing CDMSE [70], and efficient career interventions should include some basic features [72]: (i) individuals would gather more information about self and environment, (ii) individuals would gain expectations for achieving the career goals that they set, (iii) individuals would find more social support for their career development, and (iv) the intervention should have practical tools to assist individuals to navigate CE. Therefore, this study recommends that Chinese high schools provide professional and persistent career interventions for students. However, as mentioned in Section 1, Chinese high-school educators do not have much experience in developing career interventions for high-school students. What should they do? Given that CDMSE is a crucial predictor of various vocational outcomes, many career researchers and counselors have begun to investigate the antecedents of CDMSE to provide better career interventions for students. According to Lent, personal and contextual factors affect CDMSE in a complexly interactive way [13]. For instance, given that a proactive personality positively predicts CDMSE, career educators could explore high-school students’ difficulties in developing CDMSE by measuring this trait [26]. On the other hand, perceived support from influential and important people (e.g., family members) is likely to have more impact on CDMSE than other contextual factors, and this impact is more significant during adolescence [73]; therefore, it is essential to construct a bridge between high schools and parents, and high schools must strengthen parents’ awareness about their children’s sustainable career development rather than academic scores.
This study also suggests that career educators, counselors, and researchers should pay more attention to female and rural students. As the present results show, compared with male students, female high-school students more urgently need career interventions to build confidence in making mature career decisions and exhibit more CE behavior. Future career interventions should consider rural high school and urban high school students’ unique demands and difficulties in the career development process to ensure the career sustainability under the boundaryless and protean career orientation [74]. These suggestions could be adapted to female high school students.

5.5. Limitations and Future Research Design

Notwithstanding the various findings and practical suggestions described above, the present study still has some limitations. First, it used a cross-sectional design that could not causally explain the relationships among all the variables. Future research should adopt a longitudinal design to test the relationship between CDMSE and CE [75]. Second, the participants in the present study were all from Jiangsu, China. However, culture may impact the relationships among such variables [76], so the results may not be generalized to a Western cultural environment. For example, Chinese students were more likely to take advice from significant others, while American students preferred making career-related decisions by themselves [77]; the effect of emotional intelligence on CDMSE was also found to be greater among Chinese students than South Korean students [36]. Future research should recruit students from a variety of cultural backgrounds. Moreover, other variables such as contextual indicators could also be tested as moderators [26]. Future research should consider other moderators in the relationship between CDMSE and CE.

6. Conclusions

The results of the present study demonstrate that it is important and necessary to investigate the status of CDMSE and CE among Chinese high-school students and assess the relationship between these two variables. To further promote high-school students’ CE, high schools should provide career education to improve students’ CDMSE. Career educators and counselors must also pay more attention to the career development of females and rural high-school students. Additionally, future research could explore other career-related factors that may affect the CDMSE and CE of high-school students.

Author Contributions

S.C. was PI for the project; X.G., H.C. and H.L. collected the data. S.C. and H.C. did the statistical analyses; S.C. and X.G. interpreted the outcomes and wrote the paper. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Jiangsu Province University’s Advantageous Discipline Construction Project, grant number “PAPD”.

Institutional Review Board Statement

The study was approved by the Institutional Review Board of Nanjing Normal University.

Informed Consent Statement

Informed consent was obtained from all individual participants included in the study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the authors with the permission of Nanjing Normal University.

Acknowledgments

The authors would like to thank S.W. (working in Fu Jen Catholic University) for his great support in data analysis and M.T. (working in University of Cincinnati) for her great support in writing revision.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Career Decision-Making Self-efficacy Scale—Short Form.
Table A1. Career Decision-Making Self-efficacy Scale—Short Form.
No.Items
1Change majors if you did not like your first choice.
2Change occupations if you are not satisfied with the one you enter.
3Identity some major or career alternatives if you are unable to get your first choice.
4Find information about graduate or professional schools.
5Determine steps to take if you are having academic trouble with your major
……
21Select one major from a list you are considering.
22Determine the kind of information about occupation that interest you.
23Use the internet to find information about occupation that interest you.
24Talk with a person already employed in a field you are interested in.
25Decide what you value most in an occupation.
Table
Table A2. Career Exploration Survey.
Table A2. Career Exploration Survey.
No.Items
Environmental Exploration:
To what extent have you behaved in the following ways over the last 3 months?
1Investigated career possibilities.
2Went to various career orientation programs.
3Obtained information on specific jobs or companies.
4Initiated conversations with knowledge individuals in my career area.
5Obtained information on the labor market and general job opportunities in my career area.
6Sought information on specific areas of career interest.
Self-Exploration:
To what extend have you done the following in the past 3 months?
1Reflected on how my past integrates with my future career.
2Focused my thoughts on me as a person.
3Contemplated my past.
4Been retrospective in thinking about my career.
5Understood a new relevance of past behavior for my future career.

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Sustainability 13 07876 g001 550
Figure 1. Moderating effect of school on the relationship between career decision-making self-efficacy and career exploration.
Figure 1. Moderating effect of school on the relationship between career decision-making self-efficacy and career exploration.
Sustainability 13 07876 g001
Table
Table 1. Psychometrics of constructs.
Table 1. Psychometrics of constructs.
Number of ItemsLoading RangeAVE
CES110.675–0.8270.614
CDMSE-SF250.589–0.8340.576
VE = Average Variance Extracted; CDMSE = Career Decision-making Self-efficacy—Short Form; CES = Career Exploration Survey. Convergent validity: loading > 0.50 and AVE > 0.50.
Table
Table 2. Means, standard deviations, and correlations among all variables (N = 24,273).
Table 2. Means, standard deviations, and correlations among all variables (N = 24,273).
MSDSkewnessKurtosis12345678
1. SA3.6700.667−0.2030.516-
2. GI3.1780.8350.0340.0440.658 ***-
3. GS3.6250.653−0.1050.4070.643 ***0.606 ***-
4. P3.7140.703−0.2800.4290.657 ***0.624 ***0.638 ***-
5. PS3.7360.660−0.2410.2860.578 ***0.479 ***0.559 ***0.588 ***-
6. CDMSE17.9252.9080.0480.6510.753 ***0.734 ***0.727 ***0.749 ***0.765 ***-
7. SE3.7930.522−0.7020.8430.504 ***0.498 ***0.451 ***0.531 ***0.401 ***0.579 ***-
8. EE2.9150.448−0.032−0.3130.583 ***0.560 ***0.560 ***0.482 ***0.402 ***0.628 ***0.463 ***-
9. CE6.7080.879−0.2510.4560.540 ***0.522 ***0.598 ***0.586 ***0.468 ***0.508 ***0.709 ***0.796 ***
*** p < 0.001; CDMSE = Career Decision-making Self-efficacy; CE = Career Exploration; EE = environmental exploration; GI = Gathering Information; GS = Goal Selection; P = Planning; PS = Problem-solving; SA = Self-appraisal; SE = Self-exploration.
Table
Table 3. Gender differences in all variables.
Table 3. Gender differences in all variables.
VariableMale (n = 15,050)Female (n = 9223)tCohen’s dEffect Size
MSDMSD
Self-appraisal3.7200.6833.6000.63113.738 ***0.1760.088
Gathering Information3.2160.8633.1280.7848.871 ***0.1140.057
Goal Selection3.6680.6653.5610.63012.891 ***0.1650.082
Planning3.7580.7143.6480.68012.358 ***0.1590.079
Problem-Solving3.7880.6623.6640.64815.766 ***0.2020.101
CDMSE18.1472.98017.5652.75215.180 ***0.1950.097
Self-Exploration3.8050.5093.7740.5633.066 **0.0400.020
EE2.9410.4722.8730.4064.890 ***0.1540.077
Career Exploration6.7460.8196.6460.8104.783 ***0.1230.061
*** p < 0.001, ** p < 0.01; CDMSE = Career Decision-making Self-efficacy; EE = Environmental Exploration.
Table
Table 4. School differences in all variables.
Table 4. School differences in all variables.
VariableUrban School (n = 12,327)Rural School (n = 11,946)tCohen’s dEffect Size
MSDMSD
Self-Appraisal3.7230.6753.6170.65212.473 ***0.1600.080
Gathering Information3.1960.8623.1600.8063.371 ***0.0430.021
Goal Selection3.6670.6633.5820.64110.005 ***0.1280.064
Planning3.7580.7153.6690.6919.914 ***0.1270.063
Problem-Solving3.8100.6633.6610.64817.733 ***0.2280.113
CDMSE18.1542.95917.6892.83612.494 ***0.1600.080
Self-Exploration3.8330.5043.7530.5777.909 ***0.1020.050
EE2.9290.4732.9000.4222.185 *0.0300.014
Career Exploration6.7620.8176.6520.8385.141 ***0.0660.033
*** p < 0.001, * p < 0.05; CDMSE = Career Decision-making Self-efficacy; EE = Environmental Exploration.
Table
Table 5. Hierarchical regression analysis with CDMSE predicting CE (N = 24,273).
Table 5. Hierarchical regression analysis with CDMSE predicting CE (N = 24,273).
CE
βt95% CIΔR2
Model 1 (Moderator: School)
Step 1
CDMSE0.3855.66 ***[0.38, 0.39]
School0.074.81 ***[0.04, 0.09]
Step 2 0.50 ***
CDMSE × School−0.02−4.13 ***[−0.03, −0.01]
Model 2 (Moderator: Gender)
Step 1
CDMSE0.3955.79 ***[0.38, 0.39]
Gender0.128.39 ***[0.10, 0.15]
Step 2 0.00
CDMSE × Gender0.00−0.13[−0.10, 0.10]
*** p < 0.001; CDMSE = Career Decision-making Self-efficacy; CE = career exploration; CI = confidence interval.
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Chen, S.; Chen, H.; Ling, H.; Gu, X. How Do Students Become Good Workers? Investigating the Impact of Gender and School on the Relationship between Career Decision-Making Self-Efficacy and Career Exploration. Sustainability 2021, 13, 7876. https://doi.org/10.3390/su13147876

AMA Style

Chen S, Chen H, Ling H, Gu X. How Do Students Become Good Workers? Investigating the Impact of Gender and School on the Relationship between Career Decision-Making Self-Efficacy and Career Exploration. Sustainability. 2021; 13(14):7876. https://doi.org/10.3390/su13147876

Chicago/Turabian Style

Chen, Shi, Huaruo Chen, Hairong Ling, and Xueying Gu. 2021. "How Do Students Become Good Workers? Investigating the Impact of Gender and School on the Relationship between Career Decision-Making Self-Efficacy and Career Exploration" Sustainability 13, no. 14: 7876. https://doi.org/10.3390/su13147876

APA Style

Chen, S., Chen, H., Ling, H., & Gu, X. (2021). How Do Students Become Good Workers? Investigating the Impact of Gender and School on the Relationship between Career Decision-Making Self-Efficacy and Career Exploration. Sustainability, 13(14), 7876. https://doi.org/10.3390/su13147876

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