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Standards Framework

for CSTA MS

45

Standards in this Framework

Standard Description
MS-ALG-PS-01 Design an algorithm that includes variables of multiple data types to solve a problem or express ideas.
MS-ALG-PS-02 Model a given algorithm with a flowchart or pseudocode that includes a combination of control structures and procedures.
MS-ALG-PS-03 Verify the accuracy of an algorithm for given inputs.
MS-ALG-PS-04 Justify whether a problem is best solved using procedural instructions, rule-based logic, data-driven methods, or a combination of these approaches.
MS-ALG-PS-05 Use AI tools to generate outputs that assist in solving a computational problem.
MS-ALG-ML-06 Hypothesize how a machine learning model generates classifications or predictions.
MS-ALG-ML-07 Investigate ways to improve the accuracy of a machine learning model and reduce bias by refining the quality of examples and nonexamples in the training data.
MS-ALG-ML-08 Evaluate the features and limitations of a machine learning model.
MS-ALG-IM-09 Evaluate which human-centered design principles are present or missing in existing computing technologies.
MS-ALG-IM-10 Examine evidence of beneficial and harmful impacts, ethical issues, and biases of algorithms encountered in daily life.
MS-ALG-IM-11 Modify an algorithm to address a specific societal impact, ethical issue, or bias.
MS-PRO-PD-12 Use procedures to structure code for clarity and reusability.
MS-PRO-PD-13 Use reference documentation in program development.
MS-PRO-PD-14 Justify the importance of attribution and intellectual property when developing computing technologies.
MS-PRO-PD-15 Develop a program utilizing inclusive collaboration practices.
MS-PRO-VD-16 Use variables of multiple data types to store, access, and manipulate data within a program.
MS-PRO-RD-17 Analyze the roles of iteration, selection, variables, and procedures in a segment of code.
MS-PRO-RD-18 Analyze AI-generated code for accuracy and usability in a programming project.
MS-PRO-TR-19 Use systematic strategies to test, refine, and document changes to a computing technology to meet the intended purpose.
MS-PRO-TR-20 Refine a computing technology based on user feedback to improve its usability and accessibility.
MS-DAT-DC-21 Evaluate how different levels of precision and granularity in data collection affect accuracy, storage, and analysis.
MS-DAT-DC-22 Explain how data and its associated metadata can be used to answer questions.
MS-DAT-DC-23 Use a digital tool to sort, filter, group, and summarize structured data.
MS-DAT-DC-24 Analyze options to address data quality issues.
MS-DAT-DI-25 Use computational tools to identify relationships among variables in a dataset and make classifications or predictions.
MS-DAT-DI-26 Create data visualizations to show how different design choices can impact the interpretation of the same data.
MS-DAT-DI-27 Summarize a data investigation process, including potential biases, limitations, and supporting evidence.
MS-DAT-IM-28 Explain the benefits and risks of allowing personal data and metadata to be collected and used in datasets, including issues of data ownership, privacy, and sovereignty.
MS-DAT-IM-29 Analyze how decisions made at different stages of working with data can lead to biased data, misleading conclusions, and compromised AI models.
MS-SYS-HW-30 Examine differences between computing systems based on user needs, system requirements, and potential societal, environmental, and ethical impacts.
MS-SYS-HW-31 Describe computing devices used in various industries, their basic functions, and how they are used to accomplish tasks or solve problems.
MS-SYS-SE-32 Explain the effects of not using the CIA Triad when working with data.
MS-SYS-SE-33 Evaluate common types of cyber attacks and preventions.
MS-SYS-NT-34 Model how information in a network is broken down into packets, transmitted between devices, and reassembled.
MS-SYS-NT-35 Explain how the resilience of the internet depends on interconnected devices and their roles and functions within the network.
MS-SYS-IM-36 Collaborate to improve the design of a computing system to meet the needs of diverse users.
MS-SYS-IM-37 Examine how access to computing systems can vary based on personal and social factors, such as physical ability, geographic location, socioeconomic status, and age.
MS-SOC-HI-38 Compare the roles of individuals, communities, organizations, and governments in shaping computing technologies across major eras in computing history.
MS-SOC-HI-39 Analyze intended and unintended impacts of historical computing technologies on society and the environment.
MS-SOC-ET-40 Evaluate when it is appropriate to use AI and other emerging technologies to solve a problem based on their capabilities, limitations, and environmental impacts.
MS-SOC-ET-41 Evaluate how design decisions in emerging technologies influence user experiences differently across different communities.
MS-SOC-ET-42 Debate ways an emerging technology impacts the social, cultural, and environmental issues in local communities.
MS-SOC-HU-43 Analyze how the decisions humans make when using computing technologies have ethical and social consequences.
MS-SOC-CE-44 Analyze how workers in different careers use computational thinking to solve real-world problems.
MS-SOC-CE-45 Evaluate how automation in technology can create or replace jobs and change how people work.