6,624 research outputs found

    Blue - A Language for Teaching Object-Oriented Programming

    Get PDF
    Teaching object-oriented programming has clearly become an important part of computer science education. We agree with many others that the best place to teach it is in the CS1 introductory course. Many problems with this have been reported in the literature. These mainly result from inadequate languages and environments. Blue is a new language and integrated programming environment, currently under development explicitly for object-oriented teaching. We expect clear advantages from the use of Blue for first year teaching compared to using other available languages. This paper describes the design principles on which the language was based and the most important aspects of the language itself

    CS Circles: An In-Browser Python Course for Beginners

    Full text link
    Computer Science Circles is a free programming website for beginners that is designed to be fun, easy to use, and accessible to the broadest possible audience. We teach Python since it is simple yet powerful, and the course content is well-structured but written in plain language. The website has over one hundred exercises in thirty lesson pages, plus special features to help teachers support their students. It is available in both English and French. We discuss the philosophy behind the course and its design, we describe how it was implemented, and we give statistics on its use.Comment: To appear in SIGCSE 201

    Quantum Algorithm Implementations for Beginners

    Full text link
    As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers. While currently available quantum computers have less than 100 qubits, quantum computing hardware is widely expected to grow in terms of qubit count, quality, and connectivity. This review aims to explain the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional. We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succinct and self-contained fashion. We show how these algorithms can be implemented on IBM's quantum computer, and in each case, we discuss the results of the implementation with respect to differences between the simulator and the actual hardware runs. This article introduces computer scientists, physicists, and engineers to quantum algorithms and provides a blueprint for their implementations

    A Multimedia Interactive Environment Using Program Archetypes: Divide-and-Conquer

    Get PDF
    As networks and distributed systems that can exploit parallel computing become more widespread, the need for ways to teach parallel programming effectively grows as well. Even though many colleges and universities provide courses on parallel programming [1], most of those courses are reserved for graduate students and advanced undergraduates. There is a demand for ways to teach fundamental parallel programming concepts to people with just a working knowledge of programming. By using the idea of a software archetype, and providing a learning environment that teaches both concept and coding, we hope to satisfy this need. This paper presents an overview of the multimedia approach we took in teaching parallel programming and offers Divide-and-Conquer as an example of its use

    Teaching programming with computational and informational thinking

    Get PDF
    Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming. There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming. Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving. Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related. In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming
    • 

    corecore