The Experts below are selected from a list of 25113 Experts worldwide ranked by ideXlab platform
Diana Franklin - One of the best experts on this subject based on the ideXlab platform.
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SIGCSE - Assessing Children's Understanding of the Work of Computer Scientists: The Draw-a-Computer-Scientist Test
Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 2017Co-Authors: Alexandria K. Hansen, Hilary A. Dwyer, Ashley Iveland, Mia Talesfore, Lacy Wright, Danielle B. Harlow, Diana FranklinAbstract:We developed the Draw-A-Computer-Scientist-Test (DACST) to better understand elementary school students' conceptions of Computer Scientists and the nature of their work. By understanding how young children perceive Computer Scientists, we can broaden their ideas about the activities and images of Computer Scientists. We administered the DACST to 87 fourth-grade students (ages 8-9) as a pre- and post-assessment to a Computer science curriculum. All students attended the same school and were taught by the same female teacher. Before the curriculum, we found that students most often drew male Computer Scientists working alone, and featured actions that were connected to technology in general (e.g., typing, printing), but not specific to Computer science. After the curriculum, more female students drew female Computer Scientists than before, and the featured actions were more specific to Computer science (e.g., programming a game). We also share insights about the classroom-learning environment that may have contributed to changes in students' understanding of Computer Scientists and their work.
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assessing children s understanding of the work of Computer Scientists the draw a Computer Scientist test
Technical Symposium on Computer Science Education, 2017Co-Authors: Alexandria K. Hansen, Hilary A. Dwyer, Ashley Iveland, Mia Talesfore, Lacy Wright, Danielle B. Harlow, Diana FranklinAbstract:We developed the Draw-A-Computer-Scientist-Test (DACST) to better understand elementary school students' conceptions of Computer Scientists and the nature of their work. By understanding how young children perceive Computer Scientists, we can broaden their ideas about the activities and images of Computer Scientists. We administered the DACST to 87 fourth-grade students (ages 8-9) as a pre- and post-assessment to a Computer science curriculum. All students attended the same school and were taught by the same female teacher. Before the curriculum, we found that students most often drew male Computer Scientists working alone, and featured actions that were connected to technology in general (e.g., typing, printing), but not specific to Computer science. After the curriculum, more female students drew female Computer Scientists than before, and the featured actions were more specific to Computer science (e.g., programming a game). We also share insights about the classroom-learning environment that may have contributed to changes in students' understanding of Computer Scientists and their work.
Andre Scedrov - One of the best experts on this subject based on the ideXlab platform.
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the work of dean rosenzweig a tribute to a Scientist and an innovator
Foundations of Software Engineering, 2007Co-Authors: Andre ScedrovAbstract:Dean Rosenzweig, who passed away in January 2007, was a distinguished mathematician and Computer Scientist. We highlight his contributions to modeling, analysis, and testing of network security protocols, and his work on information technology used in the Zagreb Stock Exchange.
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ESEC/SIGSOFT FSE - The work of Dean Rosenzweig: a tribute to a Scientist and an innovator
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software , 2007Co-Authors: Andre ScedrovAbstract:Dean Rosenzweig, who passed away in January 2007, was a distinguished mathematician and Computer Scientist. We highlight his contributions to modeling, analysis, and testing of network security protocols, and his work on information technology used in the Zagreb Stock Exchange.
David Goldberg - One of the best experts on this subject based on the ideXlab platform.
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what every Computer Scientist should know about floating point arithmetic
ACM Computing Surveys, 1991Co-Authors: David GoldbergAbstract:Floating-point arithmetic is considered as esoteric subject by many people. This is rather surprising, because floating-point is ubiquitous in Computer systems: Almost every language has a floating-point datatype; Computers from PCs to superComputers have floating-point accelerators; most compilers will be called upon to compile floating-point algorithms from time to time; and virtually every operating system must respond to floating-point exceptions such as overflow. This paper presents a tutorial on the aspects of floating-point that have a direct impact on designers of Computer systems. It begins with background on floating-point representation and rounding error, continues with a discussion of the IEEE floating point standard, and concludes with examples of how Computer system builders can better support floating point.
Allen B. Downey - One of the best experts on this subject based on the ideXlab platform.
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Think Python: How to Think Like Computer Scientist. Ed.2
O\u27Reilly Media, 2019Co-Authors: Allen B. DowneyAbstract:If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studie
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How to Think Like a Computer Scientist
2013Co-Authors: Christopher L. Nantais, Allen B. DowneyAbstract:The goal of this book, and this class, is to teach you to think like a Computer Scientist. I like the way Computer Scientists think because they combine some of the best features of Mathematics, Engineering, and Natural Science. Like mathematicians, Computer Scientists use formal languages to denote ideas (speci- cally computations). Like engineers, they design things, assembling components into systems and evaluating tradeos among alternatives. Like Scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a Computer Scientist is problem-solving. By that I mean the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called \The way of the program." On one level, you will be learning to program, which is a useful skill by itself. On another level you will use programming as a means to an end. As we go along, that end will become clearer
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python for software design how to think like a Computer Scientist
2012Co-Authors: Allen B. DowneyAbstract:Python for Software Design is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.
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Think Java: How to think like a Computer Scientist
2011Co-Authors: Allen B. Downey, Chris MayfieldAbstract:Currently used at many colleges, universities, and high schools, this hands-on introduction to Computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a Computer Scientist. Youll learn how to programa useful skill by itselfbut youll also discover how to use programming as a means to an end. Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what youve learned. Learn one concept at a time: tackle complex topics in a series of small steps with examples Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately Determine which development techniques work best for you, and practice the important skill of debuggingLearn relationships among input and output, decisions and loops, classes and methods, strings and arrays Work on exercises involving word games, graphics, puzzles, and playing cards
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How to think like a Computer Scientist: Learning with Python
2002Co-Authors: Jeffrey Elkner, Allen B. Downey, Chris MeyersAbstract:The goal of this book is to teach you to think like a Computer Scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, Computer Scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like Scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a Computer Scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. Thats why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.
Alexandria K. Hansen - One of the best experts on this subject based on the ideXlab platform.
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SIGCSE - Assessing Children's Understanding of the Work of Computer Scientists: The Draw-a-Computer-Scientist Test
Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 2017Co-Authors: Alexandria K. Hansen, Hilary A. Dwyer, Ashley Iveland, Mia Talesfore, Lacy Wright, Danielle B. Harlow, Diana FranklinAbstract:We developed the Draw-A-Computer-Scientist-Test (DACST) to better understand elementary school students' conceptions of Computer Scientists and the nature of their work. By understanding how young children perceive Computer Scientists, we can broaden their ideas about the activities and images of Computer Scientists. We administered the DACST to 87 fourth-grade students (ages 8-9) as a pre- and post-assessment to a Computer science curriculum. All students attended the same school and were taught by the same female teacher. Before the curriculum, we found that students most often drew male Computer Scientists working alone, and featured actions that were connected to technology in general (e.g., typing, printing), but not specific to Computer science. After the curriculum, more female students drew female Computer Scientists than before, and the featured actions were more specific to Computer science (e.g., programming a game). We also share insights about the classroom-learning environment that may have contributed to changes in students' understanding of Computer Scientists and their work.
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assessing children s understanding of the work of Computer Scientists the draw a Computer Scientist test
Technical Symposium on Computer Science Education, 2017Co-Authors: Alexandria K. Hansen, Hilary A. Dwyer, Ashley Iveland, Mia Talesfore, Lacy Wright, Danielle B. Harlow, Diana FranklinAbstract:We developed the Draw-A-Computer-Scientist-Test (DACST) to better understand elementary school students' conceptions of Computer Scientists and the nature of their work. By understanding how young children perceive Computer Scientists, we can broaden their ideas about the activities and images of Computer Scientists. We administered the DACST to 87 fourth-grade students (ages 8-9) as a pre- and post-assessment to a Computer science curriculum. All students attended the same school and were taught by the same female teacher. Before the curriculum, we found that students most often drew male Computer Scientists working alone, and featured actions that were connected to technology in general (e.g., typing, printing), but not specific to Computer science. After the curriculum, more female students drew female Computer Scientists than before, and the featured actions were more specific to Computer science (e.g., programming a game). We also share insights about the classroom-learning environment that may have contributed to changes in students' understanding of Computer Scientists and their work.