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   Kargarmoakhar, Maral ; Ross, Monique ; Hazari, Zahra ; Weiss, Mark ; Georgiopoulos, Michael ; Christensen, Ken ; Solis, Tiana ( June 2020 , 2020 ASEE Virtual Annual Conference)

   The number of female students in computing fields remain low despite the millions of dollars spent on research for attracting more female students. In order to attract more female students to these male dominated fields, we first have to understand in which educational years we are losing female students. For the purpose of this study, we utilized the data from [title blinded for anonymity] an NSF funded study. Approximately, 1650 students from three large public universities in Florida participated in this survey. The survey contained 39 questions around identity, field of study, as well as fields they wanted to pursue during middle school, high school, and college. The responses gathered through the Qualtrics survey system were analyzed in R by the research team. The research questions that guided this study were: (1) To what extent are female students interested in computing related fields at middle school, the beginning of high school, and the beginning of college? (2) How have these occupational pursuits changed over time? Do they differ for gender? The results of the study indicated a majority of female students that were attracted to the computing fields during middle school remained in those fields during high school and college years. However, there was no significant flow from other majors to the computing fields observed during the different educational years. 

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2. Generative computing: African-American cosmetology as a link between computing education and community wealth

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3. NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing for Undergraduates - Version II - Big Data, Energy, and Distributed Computing

   https://doi.org/10.1145/3545947.3569594  

   Prasad, Sushil ; Weems, Charles ; Sussman, Alan ; Gupta, Anshul ; Estrada, Trilce ; Vaidyanathan, Ramachandran ; Ghafoor, Sheikh ; Kant, Krishna ; Stunkel, Craig ( March 2022 , ACM)

   This special session will report on the updated NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing released in Nov 2020 by the Center for Parallel and Distributed Computing Curricu- lum Development and Educational Resources (CDER). The purpose of the special session is to obtain SIGCSE community feedback on this curriculum in a highly interactive manner employing the hybrid modality and supported by a full-time CDER booth for the duration of SIGCSE. In this era of big data, cloud, and multi- and many-core systems, it is essential that the computer science (CS) and computer engineering (CE) graduates have basic skills in par- allel and distributed computing (PDC). The topics are primarily organized into the areas of architecture, programming, and algo- rithms topics. A set of pervasive concepts that percolate across area boundaries are also identified. Version 1 of this curriculum was released in December 2012. That curriculum guideline has over 140 early adopter institutions worldwide and has been incorpo- rated into the 2013 ACM/IEEE Computer Science curricula. This Version-II represents a major revision. The updates have focused on enhancing coverage related to the topical aspects of Big Data, Energy, and Distributed Computing. The session will also report on related CDER activities including a workshop series on a PDC institute conceptualization, developing a CE-oriented version of the curriculum, and identifying a minimal set of PDC topics aligned with ABET’s exposure-level PDC require- ments. The interested SIGCSE audience includes educators, authors,publishers, curriculum committee members, department chairs and administrators, professional societies, and the computing industry. 

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4. Resilient mobile distributed computing framework: a coded computing and named data networking approach

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5. Integrating Parallel and Distributed Computing in Early Computing Classes

   https://doi.org/10.1145/3545947.3569623  

   Ghafoor, Sheikh ; Weems, Charles ; Sussman, Alan ; Vaidyanathan, Ramachandran ; Prasad, Sushil ( March 2022 , ACM)

   Parallel and distributed computing (PDC) has become pervasive in all aspects of computing, and thus it is essential that students include parallelism and distribution in the computational thinking that they apply to problem solving, from the very beginning. Computer science education is still teaching to a 20th century model of algorithmic problem solving. Sequence, branch, and loop are taught in our early courses as the only organizing principles needed for algorithms, and we invest considerable time in showing how best to sequentially process large volumes of data. All computing devices that students use currently have multiple cores as well as a GPU in many cases. Most of their favorite applications use multiple cores and numbers of distributed processors. Often concurrency offers simpler solutions than sequential approaches. Industry is desperate for software engineers who think naturally in terms of exploiting these capabilities, rather than seeing them as an exotic upper-level topic that gets layered over a sequential solution. However, we are still teaching students to solve problems using sequential thinking. In this workshop we overview key PDC concepts and provide examples of how they may naturally be incorporated in early computing classes. We will introduce plugged and unplugged curriculum modules that have been successfully integrated in existing computing classes at multiple institutions. We will highlight the upcoming summer training workshop, for which we have funding to support attendance, as well as other CDER (Center for Parallel and Distributed Computing Curriculum Development and Educational Resources) activities. 

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