Course Description In this course, we will explore the question of the actual and potential connections between democracy and education. Our focus of attention will be placed on a critical examination of democratic theory and its implications for the civic education roles and contributions of teachers, adult educators, community development practitioners, and community organizers. We will survey and deal critically with a range of competing conceptions of democracy, variously described as classical, republican, liberal, radical, marxist, neomarxist, pragmatist, feminist, populist, pluralist, postmodern, and/or participatory. Using narrative inquiry as a means for illuminating and interpreting contemporary practice, we will analyze the implications of different conceptions of democracy for the practical work of civic education.

Democracy and education.

物件導向軟體之架構(Object-Oriented Software Construction)探討

This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library.

As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

The C programming language

コンピュータ・サイエンス : ACM computing surveys

Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include “computational thinking” as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.

/pdf/defining-computational-thinking-for-mathematics-and-science-cgvm5wfm2h.pdf

Defining Computational Thinking for Mathematics and Science Classrooms

Text books, including books for general audiences, invariably mention bubble sort in discussions of elementary sorting algorithms. We trace the history of bubble sort, its popularity, and its endurance in the face of pedagogical assertions that code and algorithmic examples used in early courses should be of high quality and adhere to established best practices. This paper is more an historical analysis than a philosophical treatise for the exclusion of bubble sort from books and courses. However, sentiments for exclusion are supported by Knuth [17], "In short, the bubble sort seems to have nothing to recommend it, except a catchy name and the fact that it leads to some interesting theoretical problems." Although bubble sort may not be a best practice sort, perhaps the weight of history is more than enough to compensate and provide for its longevity.

/pdf/bubble-sort-an-archaeological-algorithmic-analysis-1nptb92dtq.pdf

Bubble sort: an archaeological algorithmic analysis

➧1 In fall 2008 a group of computer scientists and educators convened in Atlanta under the auspices of an NSF-funded conference, Computational Thinking and Fluency in the 21st Century, to discuss the future of computer science education and to identify emerging models. It was widely agreed that students require increasing skills in computing across all disciplines and that a new high school course on a national scale would be an important step towards developing and providing access to these skills. The CS Principles Project has since developed as a collaborative effort involving computer science educators and the College Board with support from the National Science Foundation. Professional organizations including the Computer Science Teachers Association (CSTA) and the Association for Computing Machinery (ACM) have played prominent roles as well in supporting the development of the course and its place within the high school CS curriculum (see Reforming K-12 Computer Science Education ... What Will Your Story Be?, this issue) and the larger CS 10K project (see Transforming High School Computing: A Call to Action, this issue). Support for the project from the computer science education community has led the College Board to commit to making the CS Principles course a new Advanced Placement offering in the comA New Introductory Computing Course for Everyone

The CS principles project

The field of software patterns has seen an explosion in interest in the last three years. Work to date has been on the recognition, cataloging, and finding of patterns with little attention to the use of patterns, especially by students and practitioners not well-versed in object-oriented technologies. This project addresses pattern use through the development of several programming and pedagogical frameworks that supply support for using patterns throughout a computer science curriculum. Although we do not claim that patterns are Brooks' silver bullet [10], their use can help cope with the accidental complexity of software development and, we argue, their use is essential for a successful adoption of object-oriented techniques in academic computer science programs. This project addresses practical concerns of the computer science and software engineering communities in using, teaching, and learning patterns. In this paper we argue that patterns are an essential programming and pedagogical tool and report on our work in making them accessible to the educational community.

https://users.cs.duke.edu/~ola/patterns/talks/sigcse98.pdf

Design patterns: an essential component of CS curricula

Theorem provers based on model elimination have exhibited extremely high inference rates but have lacked a redundancy control mechanism such as subsumption. In this paper we report on work done to modify a model elimination theorem prover using two techniques, caching and lemmaizing, that have reduced by more than an order of magnitude the time required to find proofs of several problems and that have enabled the prover to prove theorems previously unobtainable by top-down model elimination theorem provers.

Caching and Lemmaizing in Model Elimination Theorem Provers

We have developed an application-based approach to introductory courses in computer science. This approach follows an apprenticeship model of learning, where students begin by reading, studying, and extending programs written by experienced and expert programmers. Applications play a central role since programming constructs are motivated and introduced in the context of applications, not the other way around as is the tradition in most texts and courses. Under our applied approach, (1) students are able to learn from interesting real-world examples, (2) the synthesis of different programming constructs is supported using incremental examples, and (3) good design is stressed vis code and concept reuse. In this paper, we provide several examples of our method as well as pointers to all the material we have developed which is freely available electronically. The philosophy underlying this method transcends a particular programming language, but we present our examples using C++ since that is the language used in the CS 1 and CS 2 courses at Duke. This method has been used with equal success using ISETL at Dickinson.

Owen Astrachan

Papers

Bubble sort: an archaeological algorithmic analysis

The CS principles project

Design patterns: an essential component of CS curricula

Caching and Lemmaizing in Model Elimination Theorem Provers

AAA and CS 1: the applied apprenticeship approach to CS 1