ENTER NAME OF COURSE HERE .edu



Introduction to Computational ThinkingCS 1014 I -- Catalog DescriptionAn exploration of basic ideas of computational thinking focusing on the perspectives, thought processes, and skills that underlie computational approaches to problem formulation and problem solving. Application of computational tools to investigate complex, large-scale problems in a variety of knowledge domains. Basic introduction to algorithms and a practical programming language. Brief examination of the societal implications of computational systems. (3H, 3C)Course Number:1014ADP TITLE:Intro Computational Thinking II - Learning ObjectivesHaving successfully completed this course, the student will be able to:Formulate problems and find solutions using computational thinking in their field of study.Give examples of the application of, and discuss the significance of, computational thinking in at least two different knowledge domains. Apply computational methods to model and analyze complex or large-scale phenomena.Evaluate the social and political impact of computing and information technologies. III - Justification Reflecting the ubiquity, malleability, and power of modern computing systems many have considered what mode of thinking best facilitates the use of computing in all disciplines and how this mode of thinking can be acquired. The phrase “computational thinking” has come to be taken as the term of art used in discussions among educators, scientists, and policy makers to refer to this mode of thinking. The National Research Council identified a number of motivations for developing competence in computational thinking. These are:Succeeding in a technological society.Increasing interest in the information technology professions.Maintaining and enhancing U.S. economic competitiveness.Supporting inquiry in other disciplines.Enabling personal empowerment.While these motivations reflect a national perspective, the compelling need for Virginia Tech graduates to have an increasingly sophisticated grasp of computational thinking was recognized in the ongoing general education curriculum revisions in the area of Quantitative and Computational Thinking.This course provides students with an intellectual perspective on the core ideas of computation and the methodology central to the practice of computing by: (a) engaging students with computational models in a variety of disciplines, (b) exposing the core elements of computation and algorithms that underlie these models, and (c) working with data streams that have real-world characteristics (real-time, complex, and/or large scale). In addition, the social, political, and ethical impacts and implications are briefly examined.This course is proposed at the 1000 level because it does not require any particular college level background (e.g., in programming, mathematics, or statistics), thus creating a learning environment open to all students regardless of prior experience in computing. Furthermore, the conceptual and practical skills gained through this course will significantly enrich the student’s learning experience in various fields of study, underpin the use of computationally-oriented problem solving, and encourage additional study of computational techniques and skills.IV - Prerequisites and CorequisitesNone. V - Texts and Special Teaching AidsThere is no printed textbook required for this course. Instead, free on-line interactive materials, tutorials, and project resources will be provided. The current on-line electronic book developed for this course can be found at (use the browse as a guest option next to the Login button at the bottom to view the contents). This electronic book includes: explanation and use of a computational modeling system (e.g. NetLogo) with examples in a variety of disciplines, presentation and exercises related to algorithmic constructs in two or more forms (e.g., flowchart, visual programming language (e.g. Blockly), text programming language (e.g. Python)) with emphasis on manipulating real-world/realistic data, descriptions of the structure of data and the corresponding algorithmic techniques to manipulate that data,tutorial description and examples of using a freely-available, multi-platform system (e.g. Spyder) for programming in a modern programming language with capability to easily produce a variety of data visualizations, andexplanation and examples of the social impacts of computing technology.Also provided for the course will be freely-available, multi-platform software with interfaces for accessing data streams that are real-time, complex, or large scale, and systems for creating and executing programs in a practical programming language.VI – Syllabus Percent of CourseComputational models 20Basic components of a computational modelUsing models in different domainsRole of computation in problem-solvingFundamental components of algorithms 20Decision IterationSequenceStateCalculationManipulating Data 45Mapping the structure of a complex data streamAlgorithmic manipulation of a data streamAlgorithmic representation in a programming languageProducing simple visualizations using a standard library Societal impact of computing 15TOTAL 100VII – Old (Current) SyllabusN/AVIII - Core Curriculum GuidelinesIt is requested that this course count in Area 5 of the current Curriculum for Liberal Education (CLE).With regard to the new Pathways General Education Curriculum, this course satisfies four of the six indicators of learning for the outcome in Quantitative and Computational Thinking. ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download