Standards in this Framework
Standards Mapped
Mapped to Course
| Standard | Lessons |
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CSF.AP.1.a
Identify real-world problems that are classification and prediction problems. |
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CSF.AP.1.b
Decompose a problem or process into sub-components. |
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CSF.AP.1.c
Implement abstractions to improve program modularity, reusability, and readability. |
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CSF.AP.1.d
Identify computing-based solutions to address a computational problem. |
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CSF.AP.2.a
Create programs using a text-based programming language. |
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CSF.AP.2.b
Document programs to improve the ability to trace, test, and debug. |
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CSF.AP.2.c
Trace the execution of an algorithm and predict its results. |
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CSF.AP.2.d
Analyze the outcomes of programs to identify logic and syntax errors. |
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CSF.AP.2.e
Use multiple test cases to verify and refine the program. |
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CSF.AP.2.f
Revise and improve an algorithm to resolve errors or produce desired outcomes. |
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CSF.AP.2.g
Use version control and incorporate user feedback to refine program. |
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CSF.AP.3.a
Read and interpret algorithms and programs expressed using plain language, pseudocode, and text-based programming languages. |
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CSF.AP.3.b
Create design documents using plain language, pseudocode, or diagrams. |
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CSF.AP.3.c
Read and write algorithms and programs that accept multiple input values, use variables, and produce output. |
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CSF.AP.3.d
Read and write algorithms and programs that include predefined functions and procedures with parameters and returns. |
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CSF.AP.3.e
Compare several implementations of the same algorithm using different control structures. |
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CSF.AP.4.a
Determine appropriate data structures to address program specifications. |
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CSF.AP.4.b
Apply basic computations on numeric and non-numeric data types. |
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CSF.AP.4.c
Read and write programs that create, store, and manipulate primitive data. |
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CSF.AP.4.d
Read and write programs that create, store, and manipulate linear collections of primitive data types: arrays or list. |
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CSF.AP.4.e
Read and write programs that use relational, logical, and arithmetic expressions. |
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CSF.AP.4.f
Read and write programs that traverse and manipulate data structures. |
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CSF.AP.5.a
Define and describe neural network learning algorithms. |
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CSF.AP.5.b
Illustrate and describe a neural network structure. |
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CSF.AP.5.c
Identify and discuss examples of computing technologies that utilize neural networks. |
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CSF.AP.5.d
Compare and contrast a decision tree learning algorithm and a neural network learning algorithm. |
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CSF.AP.6.a
Identify and describe characteristics of block-based and text-based coding languages. |
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CSF.AP.6.b
Analyze the advantages and disadvantages of block-based and text-based coding languages. |
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CSF.AP.6.c
Analyze the advantages and disadvantages of various text-based coding languages. |
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CSF.AP.7.a
Define the concept and role of a search algorithm. |
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CSF.AP.7.b
Define the concept and role of a sort algorithm. |
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CSF.AP.7.c
Compare and contrast bubble sort, quick sort, and merge sort. |
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CSF.AP.7.d
Compare and contrast linear search and binary search. |
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CSF.AP.7.e
Evaluate and determine the best search or sort algorithm to use based on intended results. |
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CSF.AP.8.a
Identify project management frameworks and methodologies that emphasize iteration. |
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CSF.AP.8.b
Discuss the significance of communication and methods of communication when working collaboratively. |
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CSF.AP.8.c
Distribute roles and responsibilities and adhere to predetermined timeline and/or project scope. |
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CSF.AP.8.d
Collaboratively plan, design, and revise programs. |
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CSF.AP.8.e
Provide constructive feedback through peer review. |
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CSF.AP.8.f
Use project management tools to support collaboration. |
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CSF.AP.8.g
Justify and explain design choices, including constraints, and audiences. |
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CSF.AP.8.h
Reflect and discuss collaborative experience with team. |
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CSF.CSY.1.a
Provide real-world examples of abstraction in computing. |
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CSF.CSY.1.b
Explain the role of abstraction to simplify complex systems. |
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CSF.CSY.1.c
Identify and describe levels of abstraction between application software, system software, and hardware layers. |
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CSF.CSY.2.a
Describe how computers receive visual data from various sensors and tools. |
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CSF.CSY.2.b
Describe image processing techniques to include filtering, segmentation, and feature extraction. |
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CSF.CSY.2.c
Explain how computers use pattern recognition and classify data to interpret and make decisions. |
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CSF.CSY.2.d
Discuss ethical considerations related to the use of visual data and computer vision technologies. |
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CSF.CSY.3.a
Describe the parts of a network diagram and how they are related. |
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CSF.CSY.3.b
Explain the relationship between nodes, links, and other components of graphs. |
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CSF.CSY.3.c
Explain how a computer can solve a maze, find a route on a map, and use reasoning to solve problems. |
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CSF.CSY.4.a
Compare and contrast the learning process of humans and computers. |
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CSF.CSY.4.b
Identify mathematical models used by supervised learning to produce classifications and predictions. |
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CSF.CYB.1.a
Describe ways data and computing systems can be threatened by malware, ransomware, social engineering, phishing, and other cyberattacks. |
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CSF.CYB.1.b
Compare strategies to protect data and computing systems from malware, ransomware, social engineering, phishing, and other cyberattacks. |
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CSF.CYB.2.a
Identify common targets and perpetrators of cyberattacks. |
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CSF.CYB.2.b
Identify ways data is automatically collected and generated that may or may not be evident to users. |
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CSF.CYB.2.c
Describe potential vulnerabilities when using publicly available networks. |
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CSF.CYB.2.d
Assess the impact of cyber threats on systems and people with diverse backgrounds, technical knowledge, or threat profiles. |
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CSF.CYB.3.a
Evaluate tradeoffs between usability and security. |
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CSF.CYB.3.b
Analyze scenarios to determine tradeoffs between usability and security. |
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CSF.CYB.3.c
Propose recommendations for optimizing balance between usability and security in a given computing system. |
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CSF.DA.1.a
Describe the types of data that business, industry, and government entities collect and maintain. |
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CSF.DA.1.b
Identify privacy and consumer protection issues that impact data representation. |
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CSF.DA.1.c
Identify real-world problems that can be addressed through data analysis. |
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CSF.DA.1.d
Compare two real-world datasets to identify how the values of features are encoded and represented. |
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CSF.DA.1.e
Formulate questions to decompose a problem and develop a data project plan. |
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CSF.DA.2a
Identify methods for collecting and storing data of different data sizes. |
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CSF.DA.2b
Evaluate the technical and ethical implications of collecting and storing data from the perspectives of users, programmers, companies, and communities. |
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CSF.DA.2c
Identify impacts of bias in data collection and storage practices. |
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CSF.DA.2d
Analyze the impact of data quality, quantity, diversity, and other factors on the accuracy and reliability of data visualizations. |
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CSF.DA.2e
Research emerging technologies that have the capability to construct reasoning from stakeholder data. |
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CSF.DA.3a
Evaluate the quality of training data: completeness, accuracy, consistency, and relevance. |
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CSF.DA.3b
Analyze and discuss the ethical implications and social and economic impact of training data choices. |
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CSF.DA.4a
Explain the use of training data and the role it has in the development of machine learning models. |
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CSF.DA.4b
Explain the use of reasoning models and the role it has in the development of machine learning models. |
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CSF.DA.4c
Identify and discuss the similarities and differences between training data and reasoning models in artificial intelligence systems. |
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CSF.DA.5a
Formulate questions that require data collection. |
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CSF.DA.5b
Identify appropriate data to address a predetermined question. |
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CSF.DA.5c
Define the stages of the data cycle and the interrelationship between each stage. |
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CSF.DA.5d
Identify and explain constraints of a data-driven approach. |
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CSF.DA.5e
Create a computational artifact of the data analysis results. |
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CSF.IC.1a
Identify the societal impacts of computing technologies and the various aspects of daily life and industry. |
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CSF.IC.1b
Evaluate the effect of advances in information technology on the economy, environment, and ethics, including advancements of AI, quantum computing, and technologies. |
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CSF.IC.1c
Examine the environmental impact of computing technologies. |
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CSF.IC.1d
Propose strategies to address the ethical impacts and potential challenges of computing technologies. |
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CSF.IC.2a
Identify digital tools and applications designed to monitor or regulate screen time usage. |
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CSF.IC.2b
Evaluate the impact of screen time management on productivity and well-being. |
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CSF.IC.2c
Examine and discuss the impact of screen time and social media on academic or workplace performance. |
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CSF.IC.3a
Examine correlations between historical developments in computing technologies and changes in society. |
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CSF.IC.3b
Appraise contributions of pioneers in the field of computer science. |
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CSF.IC.3c
Explore the impact of Moore’s Law on scientific and mathematical advancements. |
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CSF.IC.4a
Research and explain the preparation and job outlook for computer science careers. |
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CSF.IC.4b
Examine current and future computer science career pathways involving emerging technologies. |
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CSF.NI.1a
Identify the roles of computing devices: routers, switches, servers, and clients. |
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CSF.NI.1b
Explain the role of Internet protocols: Hypertext Transfer Protocol Secure (HTTPS) and Transmission Control Protocol/Internet Protocol (TCP/IP) to provide reliable and secure data. |
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CSF.NI.1c
Analyze and create network topology diagrams. |
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CSF.NI.1d
Model how computing devices communicate via networks using TCP/IP protocols. |
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CSF.NI.1e
Identify common problems that impact network functionality. |
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CSF.NI.1f
Identify solutions to resolve common network issues. |
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