Standards in this Framework
| Standard | Description |
|---|---|
| ALG.1.a.h.1 | Optimize algorithmic representations using abstraction and encapsulation to improve clarity, reusability, and efficiency. |
| ALG.1.a.h.2 | Model computational algorithms using structured visual formats such as flowcharts or pseudocode to demonstrate problem-solving processes. |
| ALG1.b.h.1 | Describe the differences between deterministic algorithms and probabilistic algorithms. |
| ALG1.b.h.2 | Communicate how abstraction and encapsulation shape data flow and transformation in complex algorithms. |
| ALG.1.c.h.1 | Develop algorithms using variables, data, and storage systems that solve real-world problems with authenticity and efficiency. |
| ALG.1.c.h.2 | Design and justify algorithmic decisions - such as the use of sequence, selection, or iteration - to optimize clarity, performance, and accuracy. |
| ALG.2.a.h.1 | Design and evaluate algorithms for diverse users, incorporating feedback and considering fairness, impact, and potential harms. |
| ALG.2.a.h.2 | Evaluate and refine algorithms based on diverse user feedback, prioritizing accessibility, fairness, and the identification of potential harm or unintended consequences. |
| ALG.3.a.h.1 | Develop two or more algorithms to solve the same problem and explain which one works best. |
| ALG.3.a.h.2 | Use metrics or test cases to evaluate correctness, clarity, and efficiency in different solutions. |
| ALG.3.a.h.3 | Explain how improving an algorithm's structure or logic can lead to better results or faster performance. |
| ALG.3.b.1.h | Improve algorithms by organizing repeated actions or steps into functions, modules, or reusable parts. |
| ALG3.b.2.h | Use abstraction - like lists, objects, or procedures - to make algorithms clearer and more efficient. |
| ALG.4.a.h.1 | Evaluate how algorithm decisions affect different users and communities by identifying potential bias, ethical concerns, and unintended consequences in both deterministic and probabilistic models. |
| ALG4.b.h.1 | Redesign an algorithm to address fairness, accessibility, or bias by analyzing its impact and implementing targeted improvements for equity. |
| PRO.1.a.h.1 | Analyze the purpose and structure of code segments, including the role of variables, selection, iteration, and procedures. |
| PRO.1.a.h.2 | Convert an algorithm written in pseudocode into a program that uses sequence, selection, iteration, and procedures with parameters. |
| PRO.2.a.h.2 | Compare and contrast fundamental data types and their uses. |
| PRO.2.b.h.1 | Design and implement programs that utilize complex data types and variables to efficiently store, manipulate, and maintain data integrity, including the use of scope, type conversion, and memory management principles. |
| PRO.2.c.h.1 | Create programs that use data structures and iteration to store, access, manipulate, and generalize solutions. |
| PRO.3.a.1.h | Use a systematic approach and debugging tools to independently debug a program (e.g., setting breakpoints, inspecting variables with a debugger). |
| PRO.4.a.h.1 | Define project goals based on user needs or requirements and develop a detailed plan with milestones and deadlines - using methods like Agile or SCRUM to guide iterative progress. |
| PRO.4.b.h.1 | Maintain detailed documentation of code and decision-making process, use version control tools (e.g., Git). |
| PRO.4.b.h.2 | Communicate progress through reports, presentations, or team meetings. |
| PRO.4.c.h.1 | Evaluate the effectiveness of solutions, reflect on team and individual contributions. |
| PRO.4.c.h.2 | Revise project using structured feedback and performance testing results. |
| DA.1.a.h.1 | Generate data that fits specific parameters (e.g., random samples, normal distributions) and interpret patterns and variability using computational tools (e.g., spreadsheets, programs, or simulations). |
| DA.1.a.h.2 | Develop and apply data dictionaries to describe datasets, including attribute names and types, allowable values or ranges, and logical relationships among variables, supporting data integrity and reuse. |
| DA.1.b.h.1 | Compare and convert common data formats and structures (e.g., tall vs. wide), selecting and justifying appropriate formats for different types of data analysis and computational processes. |
| DA.1.b.h.2 | Convert between binary, decimal, and hexadecimal number systems and explain how sequences of data can represent different forms (e.g., numbers, text, sound, images, instructions) in digital systems. |
| DA.1.c.h.1 | Differentiate data types (nominal, ordinal, discrete, continuous), give examples of their use, and explain how their characteristics guide data cleaning and error detection. |
| DA.2.a.h.1 | Use computational tools to transform, clean, and organize data addressing issues like missing, out-of-range, or anomalous values; and evaluate how these approaches impact data analysis and communication of findings. |
| DA.2.a.h.2 | Restructure data using computational methods (e.g., converting between tall and wide formats, flattening hierarchical data) to support specific types of analysis. |
| DA.2.a.h.3 | Analyze and optimize data storage and compression techniques for various digital formats, evaluating tradeoffs among file size, quality, resolution, and computational efficiency in real-world applications. |
| DA.2.b.h.1 | Assess data quality by checking for logical consistency, verifying expected data types and ranges, and determining if the dataset is appropriate and reliable for the intended analysis. |
| DA.3.a.h.1 | Formulate data questions involving multiple variables and refine them based on available or computationally collected data to support analysis, classification, or prediction. |
| DA.3.a.h.2 | Design and apply appropriate computational data collection processes (e.g., surveys, sensors, mobile GPS, open datasets) for answering questions, solving problems, or informing simulations. |
| DA.3.a.h.3 | Assess and synthesize multiple datasets and digital sources, identifying limitations and drawing evidence-based conclusions while considering ethical implications, data provenance, and potential misrepresentation of data. |
| DA.3.b.h.1 | Create and use computational models or simulations (e.g., epidemics, ecosystems, spread of information) to interpret data, test hypotheses, and evaluate outcomes, exploring how AI uses data patterns and how data properties influence results. |
| DA.3.c.h.1 | Evaluate and create data visualizations with attention to clarity, accessibility, accuracy, and visual integrity to effectively communicate patterns, trends, and insights. |
| DA.3.c.h.2 | Construct formal data reports that justify conclusions using evidence, models, and visualizations for acknowledging limitations, potential biases, and tradeoffs (e.g., data representation, compression, or storage formats). |
| DA.4.a.h.1 | Evaluate the societal and environmental consequences of large-scale data collection, storage, and processing, considering issues such as energy consumption, data ownership, and digital equity. |
| DA.4.a.h.2 | Evaluate how data-driven technologies, including Artificial Intelligence and Machine Learning, influence society examining impacts such as privacy, surveillance, misinformation, disinformation, and automated decision-making. |
| DA.4.b.h.1 | Analyze how biased or incomplete training data in Artificial Intelligence/Machine Learning systems can produce harmful or unfair outcomes, reinforcing stereotypes and social inequalities. |
| DA.4.b.h.2 | Evaluate data from AI and machine learning systems by analyzing algorithmic biases, data provenance, model limitations, and ethical implications to determine the validity and impact of information. |
| DA.4.c.h.1 | Compare and contrast laws, policies, and frameworks that aim to ensure ethical and responsible data use, including regulations related to consent, data privacy, fairness, and transparency. |
| DA.4.c.h.2 | Develop and justify actionable solutions to real-world problems using data investigations and modeling techniques, clearly communicating both benefits and potential ethical concerns. |
| CSS.1.a.h.1 | Explain digital tools are used in areas like healthcare, industry, and robotics to solve problems and support important work. |
| CSS.1.a.h.2 | Explain how operating systems manage hardware and software, including memory, storage, and connected devices. |
| CSS.1.a.h.3 | Evaluate risks and protections related to computing system security, including how users, organizations, and designers manage vulnerabilities, data, and device access. |
| CSS.1.b.h.1 | Create and use specific factors to evaluate a computer system based on the task it needs to perform, such as running a game, browsing the web, or doing graphic design, considering processing power, storage, battery life, cost, and software compatibility. |
| CSS.1.b.h.2 | Compare different software solutions or platforms for a task, and justify a selection based on factors like user needs, accessibility, collaboration features, cost, and security. |
| CSS.1.c.h.1 | Diagnose and resolve more complex computer and software problems by following a structured process - for example, freeing up storage, checking background programs, running security scans, or analyzing error logs. |
| CSS.1.c.h.2 | Create or modify troubleshooting guides to help others identify and fix hardware or software issues. |
| CSS.2.a.h.1 | Create a visual model (diagram) showing how hardware, software, and networks work together to complete a task or solve a problem. |
| CSS.2.a.h.2 | Explore how networks are set up (routers, cables, and switches) and investigate ways to make them work better and faster. |
| CSS.2.b.h.1 | Explain how the Internet is made up of smaller networks. Compare it to other network types based on structure, performance, and scalability. |
| CSS.3.a.h.1 | Explain how cyber-attacks - such as phishing, malware, or ransomware - can harm individuals or organizations by stealing or damaging data. |
| CSS.3.a.h.2 | Analyze how cyber-attacks can affect companies and governments, causing problems like financial loss, data theft, and broken trust. |
| CSS.3.a.h.3 | Describe the steps organizations take to respond to security incidents, including detection, containment, recovery, and communication. |
| CSS.3.b.h.1 | Create a diagram of a computer system that includes security features (e.g., encryption, login systems), showing how the design reflects user's needs through testing and improvement. |
| CSS.3.b.h.2 | Examine how networks can be at risk (vulnerabilities) and describe ways to reduce those risks (mitigation), such as firewalls, updates, or access controls. |
| CSS.3.b.h.3 | Demonstrate how encryption and decryption techniques protect digital information, and explain how these ensure confidentiality, integrity, and access control. Use simulations to model symmetric and asymmetric encryption. |
| CSS.3.b.h.4 | Evaluate how security policies (like password rules, two-factor authentication, or acceptable use policies) balance protection and user experience in schools, companies, or public systems. |
| CSS.4.h.1 | Discuss how collecting and analyzing personal data affects individuals, including how businesses, governments, and platforms use data for ads, surveillance, or content recommendations. |
| CSS.4.b.h.1 | Investigate how computing systems and physical technologies (e.g. data centers, servers, mobile devices) affect society, the environment, and the economy - considering both benefits and harms. |
| CSS.4.b.h.2 | Discuss the benefits and challenges of global technology use, including how it affects culture, communication, and online interaction. |
| CSS.4.b.h.3 | Evaluate how responsible and harmful uses of computing affect people and communities socially and economically. Use real-world examples to consider different perspectives and consequences. |
| CSS.4.b.h.4 | Examine the reasons behind rules and policies that guide how we use technology - such as the Children's Online Privacy Protection Act (COPPA) to protect kids' privacy, acceptable use policies for safe online behavior, and copyright laws to respect creators' rights. |
| FUT.1.a.h.1 | Compare and contrast early computing devices and how they influence emerging technologies. |
| FUT.1.b.h.1 | Compare different historical computing innovations and their effects on present-day society and the natural environment. |
| FUT.1.c.h.1 | Evaluate how people (e.g. diverse and underrepresented groups), organizations, and governments have shaped computing innovations and their impact on society. |
| FUT.1.d.h.1 | Evaluate policies and legislation designed to encourage ethical innovation and minimize societal risks associated with technology. |
| FUT.2.a.h.1 | Demonstrate how emerging technologies (e.g. artificial intelligence, virtual reality, automation) enable new forms of experience, expression, communication, and collaboration. |
| FUT.2.a.h.2 | Design a user interface (e.g. web pages, mobile applications, animations) to be more inclusive and accessible, minimizing the impact of the designer's inherent bias. |
| FUT.2.b.h.1 | Compare and debate the positive and negative impacts of computing on behavior and culture (e.g., smartphone usage, online reservation services, artificial intelligence, emerging technologies). |
| FUT.2.b.h.2 | Develop criteria to evaluate the beneficial and harmful effects of computing innovations on people and society. |
| FUT.2.b.h.3 | Describe how emerging technology could improve an existing solution by offering new approaches, features, or insights. |
| FUT.2.c.h.1 | Evaluate the impact of equity, access, and influence on the distribution of computing resources in a global society. |
| FUT.2.d.h.1 | Evaluate scenarios involving copyright, patents, or open-source software to determine how intellectual property rights impact innovation, collaboration, and ethical computing. |
| FUT.2.e.h.1 | Evaluate the negative impacts of electronic communication on personal relationships and evaluate differences between face-to-face and electronic communication. |
| FUT.2.e.h.2 | Create a list of practices that individuals and organizations can use to encourage proper use of both electronic and face-to-face communication. |
| FUT.2.f.h.1 | Analyze how artificial intelligence works, and evaluate its applications - including strengths, limitations, and ethical considerations - in real-world contexts. |
| FUT2.f.h.2 | Evaluate the societal impact of artificial intelligence usage. Students investigate and debate issues such as algorithmic bias, surveillance, intellectual property, and accountability. |
| FUT.3.a.h.1 | Evaluate how computing skills align with personal interests and career goals by investigating how professionals apply computer science in various roles and the impact of those careers. |
| FUT.3.a.h.2 | Explore postsecondary education, industry certifications, and training pathways comparing how professionals apply computer science in their work. |
| FUT.3.b.h.1 | Develop and showcase computational solutions that reflect real-world industry practices and collaborative problem-solving methods. |
| FUT.3.b.h.2 | Debate ethical challenges in emerging technologies and defend positions using professional codes of conduct and real-world examples. |
