scholarly journals School based experiences as contributors to career decision-making: findings from a cross-sectional survey of high-school students

2015 ◽  
Vol 42 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Natal’ya Galliott ◽  
Linda J. Graham
Keyword(s):  
High School ◽  
Decision Making ◽  
High School Students ◽  
Career Decision ◽  
Career Decision Making ◽  
Cross Sectional Survey ◽  
School Students ◽  
Cross Sectional ◽  
School Based

scholarly journals CAREER DECISION-MAKING ATTRIBUTION AND SELF EFFICACY: THE MODERATING ROLE OF EMOTIONAL INTELLIGENCE

2020 ◽  
Vol 19 (1) ◽  
pp. 1-14
Author(s):  
Rose Mini Agoes Salim ◽  
Shahnaz Safitri
Keyword(s):  
High School ◽  
Decision Making ◽  
Emotional Intelligence ◽  
High School Students ◽  
Short Form ◽  
Career Decision ◽  
Career Decision Making ◽  
School Students ◽  
Moderating Role

It is known that gifted high-school students tend to have difficulty in choosing career due to their wide-range interests and capabilities. In order to successfully making an appropriate career choice, having a high level of career decision making self-efficacy (CDMSE) is an important precondition. CDMSE is the belief in one’s ability to successfully complete the task necessary to make career-related decisions. Of several factors known to be affecting CDMSE, previous study has shown that career decision-making attribution (CDMA) could affect students CDMSE. However, the CDMA effect on CDMSE in gifted student is seemed to be related to personal trait of students, namely emotional intelligence (EI). Therefore, this study aims to examine the moderating role of EI on the impact of gifted high-school student CDMA on CDMSE. Subjects in this study were gifted high school students (N = 165; 52.12% males; M-age = 16.20 years old) in Jakarta. The measurement tools used are CDMSE Scale Short-Form, Assessment of Attribution for Career Decision Making, and Trait Emotional Intelligence Questionnaire Short-Form (TEIQue-SF) adapted into Indonesian language. The data were analyzed using simple regression analysis with Hayes PROCESS model. It was found that there is a direct effect of CDMA on CDMSE with (F (1,163) = 10.6661, p = .0033 < .001), in which CDMA serves as a predictor of CDMSE. We also found that EI can serve as a predictor of CDMSE (F (1,163) = 10.6661, p = .0007<.001. However, EI did not moderate the CDMA-CDMSE relation. Discussion, limitations, and suggestions for further research are listed. 

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