58 research outputs found

    Factors Influencing girls\u27 choice of Information Technology careers

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    Many western nations have experienced declining numbers of women in the information technology (IT) workforce (Trauth, Nielsen, & von Hellens, 2003). Between 1996 and 2002, women in the U.S. IT workforce declined from 41% to 34.9% (ITAA, 2003). This can hamper diversity and reduce the talent pool that can address needs of diverse end-users (Florida & Gates, 2002). Why do women choose IT careers or reject them? Multidisciplinary research on career genderization reveals gender imbalance (Trauth, Nielsen, & von Hellens, 2003). Career decisions against math, science, and technology (MST) are often made as early as age 11 without understanding long-term implications (AAUW, 2000). We examine influences on girls’ choice of IT careers, modeling social, structural, and personal variables that affect IT career choice. Using Ahuja’s (2002) classification of social and structural influences on women’s IT careers, Beise, Myers, VanBrackle, and Chevli-Saroq’s (2003) model of women’s career decisions, and individual differences suggested by Trauth (2002), we extend literature to children and adolescents’ career choices. Social influences bias internal and external gender perceptions and stereotyping, role models, peers, media, and family. Institutional support such as teachers and counselors, access to technology, and same-sex versus coeducational schools are structural influences. While both can influence career decisions, social factors have the most influence on children’s early perceptions. Both factors can introduce gender-stereotyping effects on career choices. Gender stereotyping explains how girls perceive their role in society based on subtle societal cues. It can limit opportunities for both sexes. We also examine personality traits and external influences that make children unique. Their individual differences draw them to activities and content areas such as problem solving and interaction with people. Finally, ethnic culture can exert an influence on social and structural variables. Figure 1 from Adya and Kaiser (2005) presents our career choice model that is discussed in the next section

    Why I Chose Computer Science? Women in India

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    In many developed countries like the United States, the percentage of women earning a bachelor’s degree in computer science (CS) is relatively low. In contrast, in many developing countries like India there has been a significant increase in the number of women pursuing a bachelor’s degree in CS. This is despite the prevalence of patriarchy in India. This paper uncovers why women in India are attracted to CS education. It is based on 60 in-depth interviews conducted with female students majoring in CS at four institutions of higher education in India in 2007-08. The findings suggest that Indian women perceive CS as a woman-friendly field

    Improving the Learning Environment in Beginning Programming Classes: An Experiment in Gender Equity

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    The under-representation of women in computing is well documented. This imbalance creates numerous problems including challenges of staffing and equity as well as more subtle problems such as a lack of balanced perspective on innovation and social implications. While there is universal agreement that females are equally capable of succeeding in a technical arena, there is a diversity of opinions as causes and solutions to this problem. One particularly interesting theory proposed by DePalma is based on trend differences between computing and other science disciplines. DePalma suggests that the positive trends in other science fields can likewise be achieved in computing if similar science pedagogies are implemented. This paper reports on an empirical study conducted to test some of DePalma’s recommendations. While our investigation is preliminary, it does provide positive support for the theory that techniques that work in other science disciplines may also prove effective in computing. The results of our findings are presented along with a discussion and implications for future work

    THE IMPACT OF E-SERVICE AND E-RECOVERY TOWARD REPURCHASE INTENTION MEDIATED BY CUSTOMER LOYALTY A STUDY OF ITEMKU E-COMMERCE

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    The purpose of this study is to determine whether there is an effect of e-service quality and e-recovery on repurchase intention in Itemku e-commerce using customer loyalty as a mediating variable. This research was conducted from June 12, 2022, to June 19, 2022. The survey method was conducted using a Likert scale. The population is Itemku application users who have made a purchase at least once in the last five months. The researcher distributed 137 questionnaires to the majority respondents using purposive sampling method. Data analysis techniques using software SmartPLS version 3.2.9 PLS (Partial Least Square) with structural equation analysis (SEM). The results of the study show that the variables of e-service quality and e-recovery which are mediated by customer loyalty have an effect on repurchase intention

    A MODEL FOR EVALUATING ONLINE GAME PLAYERS: A STUDY OF ENJOYMENT, INTERACTION, FLOW EXPERIENCE, AND MOTIVATION TOWARDS ATTITUDE AND INTENTION BEHAVIOR IN CHINA

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    The purpose of this research is to find out the factors that affect online players. This study's variables are human-Game Interaction, utilitarian motivation, hedonic motivation, flow experience, perceived enjoyment, attitude, and intention. The researchers observed these variables and put forward four hypotheses to determine the influencing factors. The researchers used China's "League of Legends" as the research model. 300 respondents select this data through a questionnaire survey on two large-scale communication platforms in China. The first platform is the official forum of "League of Legends" in China, and the second platform is the most used game social software "QQ" in China. ". The researchers used convenience sampling and judgmental sampling to investigate. All data were analyzed using statistical software, and linear regression and multiple linear regression were used to find the most significant factors affecting players’ attitudes and intentions. Use descriptive statistics to provide average and demographic percentages. Besides, the researchers use inferential statistics to test the effects of variables. The results show that human-game interaction has a significant positive correlation with utilitarian motivation and hedonic motivation. Utilitarian motivation, hedonic motivation, flow experience, and perceived enjoyment have a positive impact on the player’s attitude. However, flow experience, perceived enjoyment, and attitude have no influence on the intentions of online player
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