scholarly journals On the Study of the n-dimensional Boolean Cube in the Undergraduate Programs in Computer Science

2021 ◽  
Author(s):  
Valentin Bakoev
Keyword(s):  
Computer Science ◽  
Boolean Cube ◽  
Undergraduate Programs

Retaining Women in Undergraduate Information Technology Programs

2011 ◽  
pp. 1081-1086
Author(s):  
Tona Henderson
Keyword(s):  
Information Technology ◽  
Computer Science ◽  
Random Sample ◽  
Research Question ◽  
Phase 1 ◽  
First Year ◽  
Research Association ◽  
Decision To Leave ◽  
Undergraduate Programs ◽  
Experiences Of Women

While the experiences of women in computer science (CS) are well documented (Cohoon, 2001, 2002; Computing Research Association, 2002; Margolis & Fisher, 2001), information technology is a relatively new discipline (Denning, 2001; Mitchell, 2002) and does not enjoy the same level or scope of inquiry. This study focuses on women in undergraduate IT programs and attempts to identify the factors involved in the attrition of women from these programs. In Phase 1 of this study, all freshman IT and CS women as well as a random sample of IT men at an eastern university (15,000 students) were interviewed and asked about their experiences in the IT program. These interviews were qualitatively analyzed, and the results are currently being used to develop a national survey of women in undergraduate IT programs. The primary research question of this study is, What factors are most influential in the decision of female students in IT undergraduate programs to enter these programs, and, where applicable, what factors most influence their decision to leave the programs during their first year of study?

Retention in Computer Science Undergraduate Programs in the U.S.

2018 ◽  
Author(s):  
Chris Stephenson ◽  
Alison Derbenwick Miller ◽  
Christine Alvarado ◽  
Lecia Barker ◽  
Valerie Barr ◽  
...  
Keyword(s):  
Computer Science ◽  
Undergraduate Programs ◽  
The U.S

Computer science

2020 ◽  
Author(s):  
Sergey Gurikov
Keyword(s):  
Higher Education ◽  
Computer Science ◽  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Educational Institutions ◽  
Federal State ◽  
Educational Standards ◽  
Information And Communication ◽  
State Educational ◽  
Undergraduate Programs

The textbook covers the theoretical and practical foundations of the computer science course. The content of the book, examples and tasks are aimed at training a specialist with a modern set of competencies in the field of computer science and information and communication technologies. The textbook has an applied orientation and meets the requirements of the Federal state educational standards of higher education of the latest generation. For students of higher educational institutions studying undergraduate programs, it will also be useful for students of secondary vocational education institutions, teachers, and people who want to study computer science independently.

scholarly journals Undergraduate data science degrees emphasize computer science and statistics but fall short in ethics training and domain-specific context

2021 ◽  
Vol 7 ◽  
pp. e441
Author(s):  
Jeffrey C. Oliver ◽  
Torbet McNeil
Keyword(s):  
Science Education ◽  
Computer Science ◽  
Domain Knowledge ◽  
Data Science ◽  
The United States ◽  
Current Data ◽  
Data Intensive ◽  
Domain Specific ◽  
Interdisciplinary Field ◽  
Undergraduate Programs

The interdisciplinary field of data science, which applies techniques from computer science and statistics to address questions across domains, has enjoyed recent considerable growth and interest. This emergence also extends to undergraduate education, whereby a growing number of institutions now offer degree programs in data science. However, there is considerable variation in what the field actually entails and, by extension, differences in how undergraduate programs prepare students for data-intensive careers. We used two seminal frameworks for data science education to evaluate undergraduate data science programs at a subset of 4-year institutions in the United States; developing and applying a rubric, we assessed how well each program met the guidelines of each of the frameworks. Most programs scored high in statistics and computer science and low in domain-specific education, ethics, and areas of communication. Moreover, the academic unit administering the degree program significantly influenced the course-load distribution of computer science and statistics/mathematics courses. We conclude that current data science undergraduate programs provide solid grounding in computational and statistical approaches, yet may not deliver sufficient context in terms of domain knowledge and ethical considerations necessary for appropriate data science applications. Additional refinement of the expectations for undergraduate data science education is warranted.

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