Factors Influencing girls\u27 choice of Information Technology careers

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

Contemporary developments in teaching and learning introductory programming: Towards a research proposal

The teaching and learning of introductory programming in tertiary institutions is problematic. Failure rates are high and the inability of students to complete small programming tasks at the completion of introductory units is not unusual. The literature on teaching programming contains many examples of changes in teaching strategies and curricula that have been implemented in an effort to reduce failure rates. This paper analyses contemporary research into the area, and summarises developments in the teaching of introductory programming. It also focuses on areas for future research which will potentially lead to improvements in both the teaching and learning of introductory programming. A graphical representation of the issues from the literature that are covered in the document is provided in the introduction

Initiating and Sustaining Female Networks in Computer Science and IT

Over the last decade, several networks and communities for women in IT have been initiated. It has been known that specific needs for support exist where members of a minority have difficulties in finding like-minded people in their everyday environment. This paper investigates different forms of female networks in Computer Science and IT. In particular, it analyses forms of network initiation, which often involve face-to-face meetings at regular events like conferences or, increasingly, at summer universities for female students. We conducted three studies to identify the attendees' expectations and needs for support using questionnaires, interviews, and a wiki analysis. This paper aims at identifying effective strategies for initiating female networks

Disrupting Illicit Supply Networks: New Applications of Operations Research and Data Analytics to End Modern Slavery

Report from a 2017 National Science Foundation workshop on promising research directions for applications of operations research and data analytics toward the disruption of illicit supply networks like human trafficking. The workshop was funded by the NSF’s Operations Engineering (ENG) and the Law & Social Sciences Program (SBE) under grant # CMMI-1726895. The report addresses the opportunity to apply advances from the fields of operations research, management science, analytics, machine learning, and data science toward the development of disruptive interventions against illicit networks. Such an extension of the current research agenda for trafficking would move understanding of such dynamic systems from descriptive characterization and predictive estimation toward improved dynamic operational control.Bureau of Business Researc

Time and Organizational Improvisation

This paper argues that the apparent contradiction in current conceptualizations of time in organizations (e.g., Chronos vs. Kairos) is only apparent, and that a synthesis between these opposing poles is both possible and desirable. We propose improvisation (where time to plan converges with time to act) as a vehicle for articulating a dialectical view of time-based organizational phenomena, while focusing on the three major time-related problems organizations have to solve: scheduling, synchronization, and allocation. The paper discusses how improvisation helps to synthesize even time and event time in scheduling processes, internal pacing and external pacing in synchronization processes, and linear and cyclical time in allocation processes. Methodological and practical obstacles to synthesis are also discussed.Improvisation, Planning, Time

Colonial Legacies, Postcolonial Biologies: Gender and the Promises of Biotechnology

Three decades of work in the feminist studies of science and technology have shaped our evolving understandings of the relationships between sex, gender, and biotechnology. Sex, and gender are most often reduced to binary categories, severely limiting our conceptions not only of human diversity, but those of science and technology. Using two case study set in India, transnational surrogacy and the Indian Genome Variation Project, this paper explores how popular positions around biotechnology are reduced to binary positions promoting and opposing biotechnology as the solution for the economic and social development of India. By locating surrogacy and genomics within the larger geopolitical, historical, economic and cultural transformations of postcolonial India, the paper argues that both technologies are far more complex in their impact on women and gender. Why does technology become the major site of hope for the future? Why does genomics become the site for the promises of good health? Why has India become a site for reproductive tourism, and transnational surrogacy in particular? Drawing on the social studies of science, the paper argues that technology and human bodies are never neutral but always prefigured with a gender, race, caste and sexuality. Surrogacy and genomics should be understood within these colonial and postcolonial histories of science and technology

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Ethics of Artificial Intelligence

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn