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American Government
Unrestricted Use
CC BY
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 American Government is designed to meet the scope and sequence requirements of the single-semester American government course. This title includes innovative features designed to enhance student learning, including Insider Perspective features and a Get Connected Module that shows students how they can get engaged in the political process. The book provides an important opportunity for students to learn the core concepts of American government and understand how those concepts apply to their lives and the world around them. American Government includes updated information on the 2016 presidential election.Senior Contributing AuthorsGlen Krutz (Content Lead), University of OklahomaSylvie Waskiewicz, PhD (Lead Editor)

Subject:
Political Science
Social Science
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
Date Added:
01/06/2016
Bean Bar Graph (PreK - 1st Grade) Agricultural STEM Actvity
Conditional Remix & Share Permitted
CC BY-SA
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0.0 stars

In this activity, kids will work on two fundamental early math skills – sorting/classifying, and graphing. There will also be some great fine motor skill practice! Includes place-based discussion questions, activity instructions, extension activities, songs, and student graph worksheets.

NGSS: K-LS1-1, 1-LS1-1, partially meets K-ESS3-1 (book and discussion)

Common Core: MP.4

Time: 45 minutes

Matierals: bag of dried beans ("16 bean soup"), paper bowls, glue, chart paper, the book "One Bean" or similar book about growing food plants, especially beans.

Subject:
Agriculture
Career and Technical Education
Early Childhood Development
Education
Elementary Education
Mathematics
Measurement and Data
Material Type:
Activity/Lab
Lesson Plan
Author:
Columbia Gorge STEM Hub
Date Added:
08/07/2020
Design and Analysis of Algorithms
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.

Subject:
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Demaine, Erik
Devadas, Srini
Lynch, Nancy
Date Added:
02/01/2015
Design and Analysis of Algorithms
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Moshkovitz, Dana
Tidor, Bruce
Date Added:
02/01/2012
Foundations of Software Engineering
Conditional Remix & Share Permitted
CC BY-NC-SA
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This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program.
This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J. In 2005, ocean engineering subjects became part of Course 2 (Department of Mechanical Engineering), and the 13.470J designation was dropped in lieu of 2.159J.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Amaratunga, Kevin
Date Added:
09/01/2000
Introduction to Algorithms
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

Subject:
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Demaine, Erik
Devadas, Srini
Rivest, Ronald
Date Added:
02/01/2008
Introduction to Algorithms
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems.

Subject:
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Demaine, Erik
Ku, Jason
Solomon, Justin
Date Added:
02/01/2020
Introduction to Algorithms
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Demaine, Erik
Devadas, Srini
Date Added:
09/01/2011
Introduction to Algorithms (SMA 5503)
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Demaine, Erik
Leiserson, Charles
Date Added:
09/01/2005
Introduction to Computer Science II
Unrestricted Use
CC BY
Rating
0.0 stars

This course is a continuation of the first-semester course titled Introduction to Computer Science I. It will introduce the student to a number of more advanced Computer Science topics, laying a strong foundation for future academic study in the discipline. The student will begin with a comparison between Java--the programming language utilized last semester--and C++, another popular, industry-standard programming language. The student will then discuss the fundamental building blocks of Object-Oriented Programming, reviewing what they have learned learned last semester and familiarizing themselves with some more advanced programming concepts. The remaining course units will be devoted to various advanced topics, including the Standard Template Library, Exceptions, Recursion, Searching and Sorting, and Template Classes. By the end of the class, the student will have a solid understanding of Java and C++ programming, as well as a familiarity with the major issues that programmers routinely address in a professional setting. Upon successful completion of this course, the student will be able to: Demonstrate an understanding of the concepts of Java and C++ and how they are used in Object-Oriented Programming; Demonstrate an understanding of the history and development of Object-Oriented Programming; Explain the importance of the C++ Standard Template Library and how basic components are used; Demonstrate a basic understanding of the importance of run-time analysis in programming; Demonstrate an understanding of important sorting and search routines in programming; Demonstrate an understanding of the generic usage of templates in programming for C++ and Java; Compare and contrast the features of Java and C++. (Computer Science 102; See also: Mathematics 303)

Subject:
Applied Science
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Introduction to Computer Science and Programming in Python
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

6.0001 Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Bell, Ana
Grimson, Eric
Guttag, John
Date Added:
09/01/2016
Introduction to Computers and Engineering Problem Solving
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This course presents the fundamentals of object-oriented software design and development, computational methods and sensing for engineering, and scientific and managerial applications. It cover topics, including design of classes, inheritance, graphical user interfaces, numerical methods, streams, threads, sensors, and data structures. Students use Java® programming language to complete weekly software assignments.
How is 1.00 different from other intro programming courses offered at MIT?
1.00 is a first course in programming. It assumes no prior experience, and it focuses on the use of computation to solve problems in engineering, science and management. The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where the computer is the system; it focuses on engineering problems where the computer is part of the system, or is used to model a physical or logical system.
1.00 teaches the Java programming language, and it focuses on the design and development of object-oriented software for technical problems. 1.00 is taught in an active learning style. Lecture segments alternating with laboratory exercises are used in every class to allow students to put concepts into practice immediately; this teaching style generates questions and feedback, and allows the teaching staff and students to interact when concepts are first introduced to ensure that core ideas are understood. Like many MIT classes, 1.00 has weekly assignments, which are programs based on actual engineering, science or management applications. The weekly assignments build on the class material from the previous week, and require students to put the concepts taught in the small in-class labs into a larger program that uses multiple elements of Java together.

Subject:
Applied Science
Computer Science
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Cassa, Christopher
Gonzalez, Marta
Kocur, George
Date Added:
02/01/2012
Introduction to Sociology 2e
Unrestricted Use
CC BY
Rating
0.0 stars

Introduction to Sociology 2e adheres to the scope and sequence of a typical, one-semester introductory sociology course. It offers comprehensive coverage of core concepts, foundational scholars, and emerging theories, which are supported by a wealth of engaging learning materials. The textbook presents detailed section reviews with rich questions, discussions that help students apply their knowledge, and features that draw learners into the discipline in meaningful ways. The second edition retains the book’s conceptual organization, aligning to most courses, and has been significantly updated to reflect the latest research and provide examples most relevant to today’s students. In order to help instructors transition to the revised version, the 2e changes are described within the preface.

Subject:
Social Science
Sociology
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
Date Added:
02/01/2012
Kindergarten - Elementary Science and Integrated Subjects: Tackling Trash
Unrestricted Use
CC BY
Rating
0.0 stars

Elementary Science and Integrated Subjects is a statewide Clime Time collaboration among ESD 123, ESD 105, and the Office of Superintendent of Public Instruction. Development of the resources is in response to a need for research- based science lessons for elementary teachers that are integrated with English language arts, mathematics and other subjects such as social studies. The template for Elementary integration can serve as an organized, coherent and research-based roadmap for teachers in the development of their own NGSS aligned science lessons.  Lessons can also be useful for classrooms that have no adopted curriculum as well as to serve as enhancements for  current science curriculum. 

Subject:
Ecology
Education
Elementary Education
Environmental Science
Material Type:
Activity/Lab
Author:
Georgia Boatman
Barbara Soots
Ellen Ebert
Kimberley Astle
Washington OSPI OER Project
Date Added:
06/04/2020
Preschool/Kindergarten Halloween Math Worksheets
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This resource was designed for preschool and kindergarten students to have paper/pencil practice and/or assessment for four early math skills: number to quantity (1-10), patterning (AB, AAB, ABB, ABC), sorting by size, and organizing by size.The South Carolina State Standards that are addressed by each activity are included on each worksheet.

Subject:
Mathematics
Material Type:
Activity/Lab
Assessment
Homework/Assignment
Author:
Jennifer Cagle
Date Added:
10/01/2022