Computer Science and Educational Software Design

EBook Description: Truly interdisciplinary approach to combine the viewpoints of computer scientists and educational actors Provides practical and context-related hints on how to deal with the peculiarities of educational software design and development Complemented by several examples illustrating issues and propositions Based on the author�s more than 20 years� experience in projects on technology-enhanced learning Developing educational software requires thinking, problematizing, representing, modeling, implementing and analyzing pedagogical objectives and issues, as well as conceptual models and software architectures. Computer scientists face the difficulty of understanding the particular issues and phenomena to be taken into account in educational software projects and of avoiding a na�ve technocentered perspective. On the other hand, actors with backgrounds in human or social sciences face the difficulty of understanding software design and implementation issues, and how computer scientists engage in these tasks. Tchounikine argues that these difficulties cannot be solved by building a kind of �general theory� or �general engineering methodology� to be adopted by all actors for all projects: educational software projects may correspond to very different realities, and may be conducted within very different perspectives and with very different matters of concern. Thus the issue of understanding each others� perspectives and elaborating some common ground is to be considered in context, within the considered project or perspective. To this end, he provides the reader with a framework and means for actively taking into account the relationships between pedagogical settings and software, and for working together in a multidisciplinary way to develop educational software. His book is for actors engaged in research or development projects which require inventing, designing, adapting, implementing or analyzing educational software. The core audience is Master�s and PhD students, researchers and engineers from computer science or human and social sciences (e.g., education, psychology, pedagogy, philosophy, communications or sociology) interested in the issues raised by educational software design and analysis and in the variety of perspectives that may be adopted. In addition, it is also of interest for teachers engaged in, for example, ICT-based innovations.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.
01- Goals of the course; what is computation; introduction to data types, operators, and variables
02- Operators and operands; statements; branching, conditionals, and iteration
03- Common code patterns: iterative programs
04- Decomposition and abstraction through functions; introduction to recursion
05- Floating point numbers, successive refinement, finding roots
06- Bisection methods, Newton/Raphson, introduction to lists
07- Lists and mutability, dictionaries, pseudocode, introduction to efficiency
08- Complexity; log, linear, quadratic, exponential algorithms
09- Binary search, bubble and selection sorts
10- Divide and conquer methods, merge sort, exceptions
11- Testing and debugging
12- More about debugging, knapsack problem, introduction to dynamic programming
13- Dynamic programming: overlapping subproblems, optimal substructure
14- Analysis of knapsack problem, introduction to object-oriented programming
15- Abstract data types, classes and methods
16- Encapsulation, inheritance, shadowing
17- Computational models: random walk simulation
18- Presenting simulation results, Pylab, plotting
19- Biased random walks, distributions
20- Monte Carlo simulations, estimating pi
21- Validating simulation results, curve fitting, linear regression
22- Normal, uniform, and exponential distributions; misuse of statistics
23- Stock market simulation
24- Course overview; what do computer scientists do?

A Foundation for Computer Science

This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline.
Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems." The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study.

Science in the Age of Computer Simulation

Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Eric Winsberg seeks to answer these questions in Science in the Age of Computer Simulation.
Scrutinizing these issue with a philosophical lens, Winsberg explores the impact of simulation on such issues as the nature of scientific evidence; the role of values in science; the nature and role of fictions in science; and the relationship between simulation and experiment, theories and data, and theories at different levels of description. Science in the Age of Computer Simulation will transform many of the core issues in philosophy of science, as well as our basic understanding of the role of the digital computer in the sciences.

Computer Science: An Activity-Based Approach

The dynamic evolution of the field of computer science (CS) also poses educational and pedagogical challenges, such as issues of CS teacher recruitment, pre-service teacher preparation, support for teachers' ongoing professional development, and the design of teaching and learning material.

This unique Guide to Teaching Computer Science presents both a conceptual framework and detailed implementation guidelines for general CS teaching. The content is clearly written and structured to be applicable to all levels of CS education and for any teaching organization, without limiting its focus to instruction of any specific curriculum, programming language or paradigm.

Topics and features:
Presents an overview of curriculum topics in CS, and of research in CS education
Examines strategies for teaching problem-solving, pupil evaluation, and for dealing with pupils� misunderstandings
Provides learning activities throughout the book
Proposes active-learning-based classroom teaching methods, as well as methods for lab-based teaching
Discusses various types of questions that a CS instructor, tutor, or trainer can use for a range of teaching situations
Investigates thoroughly issues of lesson planning and course design
Describes frameworks by which prospective CS teachers gain their first teaching experience

Drawing on the authors� experience of more than two decades of teaching and research in CS education, this concise, thorough and easy-to-follow book is eminently suitable for use as either a teaching guide for all CS instructors or as a textbook for CS teacher training programs.

Dr. Orit Hazzan is an associate professor in the Department of Education in Technology and Science at Technion � Israel Institute of Technology, Haifa, Israel. Dr. Tami Lapidot is Executive Manager of Machshava � the Israeli National Center for Computer Science Teachers, Haifa, Israel. Dr. Noa Ragonis is a lecturer in the Department of Computer Science at Beit Berl College, Israel.

1.Introduction to Computer Science and Programming

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.

Discrete Mathematics for Computer Science

An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems. Based on their teaching experiences, the authors offer an accessible text that emphasizes the fundamentals of discrete mathematics and its advanced topics. This text shows how to express precise ideas in clear mathematical language. Students discover the importance of discrete mathematics in describing computer science structures and problem solving. They also learn how mastering discrete mathematics will help them develop important reasoning skills that will continue to be useful throughout their careers.

Collection of Computer Science

Insane Collection of Computer Science

Advances in Computer Science and Engineering, ebook

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling.

Discrete Mathematics for Computer Science

An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems. Based on their teaching experiences, the authors offer an accessible text that emphasizes the fundamentals of discrete mathematics and its advanced topics. This text shows how to express precise ideas in clear mathematical language. Students discover the importance of discrete mathematics in describing computer science structures and problem solving. They also learn how mastering discrete mathematics will help them develop important reasoning skills that will continue to be useful throughout their careers.

1.Discrete Mathematics for Computer Science

An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems. Based on their teaching experiences, the authors offer an accessible text that emphasizes the fundamentals of discrete mathematics and its advanced topics. This text shows how to express precise ideas in clear mathematical language. Students discover the importance of discrete mathematics in describing computer science structures and problem solving. They also learn how mastering discrete mathematics will help them develop important reasoning skills that will continue to be useful throughout their careers.

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