Women in Technology: A Program to Increase Career Awareness

1980 ◽  
Vol 58 (6) ◽  
pp. 445-448 ◽  
Author(s):  
Diane Tarmy Rudnick ◽  
Ellen J. Wallach
1975 ◽  
Vol 23 (4) ◽  
pp. 365-366 ◽  
Author(s):  
Lawrence Hackney ◽  
Calvin E. Williams
Keyword(s):  

2019 ◽  
Vol 6 (2) ◽  
pp. 125-132
Author(s):  
Elia Firda Mufidah

Street children are still a problem that needs to be moved. There are still many street children who drop out of school and do not understand what is related to the work taken. Game-based tutoring is in accordance with guiding principles and games so that children can be interested in joining this service. This research method uses pretest-posttest one group pre-experimental design. This study aims to find out how to use this program. This program aims to increase awareness. The Wilcoxon Career Awareness Test Results were obtained by Asymp. Sig = 0.043. Asymp comparison. Sig = 0.043 <α = 0.05 then Ho is accepted and H1 is rejected. Associated with a significant priority on the career awareness scores of street children before the implementation of assistance based on street children's awareness planning. The results of this study are increased career awareness of street children


2021 ◽  
Author(s):  
EmilyKate McDonough ◽  
Kayle S Sawyer ◽  
Jessica Wilks ◽  
Berri Jacque

To meet the demand of the growing science and health sectors in the United States, there is a critical necessity to engage more people in science, technology, engineering, and math (STEM). To broaden participation in STEM, we must understand the factors that shape perspectives and beliefs around career selection. Good measurement of these factors is crucial to quantify how effectively educational interventions impact student attitudes towards STEM. Adolescents are particularly suited for quantifying intervention efficacy because students build their identities during these formative years and make important career choices. To better quantify intervention efficacy at the high school level, we developed an instrument entitled Student Attitudes Surrounding STEM (SASS), which builds upon the social cognitive career theory (SCCT) framework for understanding career selection. Questionnaire responses were collected from 932 high school students, and split into samples of 400 for exploratory factor analysis and 532 for confirmatory factor analysis. The questions clustered into six factors: self-efficacy experience, self-efficacy academic, outcome expectations, interests, negative perceptions of scientists, and career awareness. The SASS exhibited adequate construct validity as determined by fit indices and theoretical considerations. Furthermore, the instrument demonstrated criterion validity, internal consistency, and test-retest reliability. This tool represents a novel integration of three latent variables into SCCT, negative perceptions of scientists, career awareness, and an experience factor for self-efficacy.


1995 ◽  
Vol 79 (570) ◽  
pp. 30-35
Author(s):  
Canary C. Hogan
Keyword(s):  

Author(s):  
Laurie O. Campbell ◽  
Joshua H. Truitt ◽  
Christine P. Herlihy ◽  
Jarrad D. Plante

There is known gender disparity and inequity of women leaders in technology and STEM fields. A rapid gender decline in these burgeoning fields has sparked a national renewed interest in purposefully attracting and mentoring more women to roles in technology leadership. The gender disparity is not only in attracting young women to consider a technology or STEM career but it is in women staying engaged once they choose a career in these areas. Efforts have been made to improve the sustainability of women in technology leadership roles. Books, articles, and manuscripts have been written, formal and informal meetings and corporate awareness programs have been conducted and mentorship programs abound to attract girls to consider technology as a career choice. Further, identifying women role models has been a strategy employed to promote gender awareness. Within the chapter, the qualitative content analysis study investigates four women roles models and identifies leadership characteristics of these known women leaders in technology. It answers the following questions: What are the leadership characteristics of known women role models in technology? What do these leaders value? How do their differences impact their leadership in the field? Finally, what have they identified as propelling them towards innovation and discovery?


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