• Course Overview

    AP Computer Science Principles is an introductory college-level computing course that introduces students to the breadth of the field of computer science. Students learn to design and evaluate solutions and to apply computer science to solve problems through the development of algorithms and programs. They incorporate abstraction into programs and use data to discover new knowledge. Students also explain how computing innovations and computing systems—including the internet—work, explore their potential impacts, and contribute to a computing culture that is collaborative and ethical.

     

    Click here to access AP Central information about this course.

     

    Computer Science A Equivalent Course 

    (Score: 3) COSC 1436 Programming Fundamentals I   /Sem. Hr. 4

    (Score: 4 or 5) COSC 1436-7 Programming Fundamentals I & II   /Sem. Hr. 8

     

     

    Course Content

    Based on the Understanding by Design® (Wiggins and McTighe) model, the AP Computer Science Principles Course and Exam Description provides a clear and detailed description of the course requirements necessary for student success. The course is designed to be equivalent to a first-semester introductory college computing course. The major areas of study in the course are organized around big ideas that encompass ideas foundational to studying computer science.

    The AP Computer Science Principles course framework is organized into five big ideas. As always, you have the flexibility to organize the course content as you like.

    Big Idea Exam Weighting (Multiple-Choice Section)

    Big Idea 1: Creative Development

    10%–13%

    Big Idea 2: Data

    17%–22%

    Big Idea 3: Algorithms and Programming

    30%–35%

    Big Idea 4: Computer Systems and Networks

    11%–15%

    Big Idea 5: Impact of Computing

    21%–26%

    Computational Thinking Practices

    The AP Computer Science Principles course framework included in the course and exam description outlines distinct skills from computational thinking practices that students should practice and develop throughout the year—skills that will help them learn to think and act like computer scientists. Emphasis is placed on creativity and collaboration as pedagogical strategies to be used to develop a diverse, appealing, and inclusive classroom environment.

    Computational Thinking Practice Description Exam Weighting (Multiple-Choice Section)

    1. Computational Solution Design

    Design and evaluate computational solutions for a purpose.

    18%–25%

    2. Algorithms and Program Development

    Develop and implement algorithms.

    20%–28%

    3. Abstraction in Program Development

    Develop programs that incorporate abstractions.

    7%–12%

    4. Code Analysis

    Evaluate and test algorithms and programs.

    12%–19%

    5. Computing Innovations

    Investigate computing innovations.

    28%–33%

    6. Responsible Computing

    Contribute to an inclusive, safe, collaborative, and ethical computing culture.

    Not assessed