# 19

Standards in this Framework

Standards Mapped

# 100%

Mapped to Course

Standard Lessons
CIS.HS.8.1.a
Identify component parts or subproblems of a simple problem.
1. 1.7 Top Down Design and Decomposition in Karel
CIS.HS.8.1.b
Identify subproblems that make up a larger computational problem.
1. 1.7 Top Down Design and Decomposition in Karel
CIS.HS.8.1.c
Explain how solutions to multiple subproblems work together to solve a larger problem.
1. 1.7 Top Down Design and Decomposition in Karel
CIS.HS.8.1.d
Define the term algorithm and explain its relationship to computational solutions.
1. 1.17 Karel Algorithms
CIS.HS.8.2.a
Define abstraction in terms of computer science and provide an example of how abstraction is used to manage complexity.
1. 1.9 Abstraction
CIS.HS.8.2.b
Represent equivalent data using different encoding schemes (e.g., binary, unicode, Morse code, student-created codes).
1. 8.3 Encoding Text with Binary
CIS.HS.8.2.c
Use abstraction to manage complexity or avoid duplication of effort.
1. 1.9 Abstraction
CIS.HS.8.2.d
Use and extend existing procedures within a program based on their documentation.
1. 5.7 JavaScript vs Karel
CIS.HS.8.2.e
Identify repetitive elements of program code and develop functionally equivalent versions that reduce redundant code or hide the complexity of a task.
1. 1.5 Functions in Karel
2. 5.1 Functions and Parameters 1
3. 5.2 Functions and Parameters 2
4. 5.3 Functions and Parameters 3
CIS.HS.8.3.a
Create variables to store data in a program.
1. 3.4 Variables
CIS.HS.8.3.b
Use and update data stored in variables.
1. 3.4 Variables
CIS.HS.8.3.c
Develop programs that use sequences of statements, loops, and conditional statements.
1. 4.7 For Loops in JavaScript
2. 4.9 For Loop Practice
CIS.HS.8.3.d
Design and develop computational artifacts that address personally- or socially relevant concerns.
1. 21.1 Intro to Design Thinking
2. 21.2 Prototype
3. 21.3 Test
CIS.HS.8.4.a
Filter or transform data using a computational tool.
1. 16.2 Visualizing and Interpreting Data
CIS.HS.8.4.b
Explain the results of a data-driven investigation and a reproducible process for computing the results.
1. 16.1 Getting Started with Data
2. 16.2 Visualizing and Interpreting Data
3. 16.3 Data Collection & Limitations
4. 17.1 Present a Data-Driven Insight
CIS.HS.8.4.c
Use and modify a computer simulation to understand a real-world system.
1. 7.9 Simulation
CIS.HS.8.4.d