Standards Mapping

DLCS25.HS.1

Compare and contrast a generalized algorithm in pseudocode and its concrete implementation in a programming language.

• 6.5 Algorithms in Computing

DLCS25.HS.2

Translate pseudocode, flowcharts, or other planning tools into multiple programming languages.

• 6.5 Algorithms in Computing

DLCS25.HS.3

Explain the characteristics of algorithms, including speed, accuracy, and storage requirements.

• 6.6 Comparing Algorithms

DLCS25.HS.4

Model and adapt classic algorithms, including sorting and searching, to solve computational problems.

• 6.7 Linear Search
• 6.8 Binary Search

DLCS25.HS.5

Decompose problems into component parts, extract key information, and model levels of abstraction in complex systems.

• 5.12 Levels of Abstraction
• 7.3 Plan and Design

DLCS25.HS.6

Compare different data compression algorithms by analyzing their main features, including their compression speed and whether they preserve data exactly (lossless) or reduce data quality for higher compression (lossy).

• 2.13 Compressing Data

DLCS25.HS.7

Create software solutions using libraries and application programming interfaces (APIs) that demonstrate code reuse.

• 13.4 Modules, Packages & Libraries

DLCS25.HS.8

Compare and contrast the major categories of machine learning, including supervised, unsupervised, and reinforcement learning. [AI]

• 10.8 Intro to Machine Learning
• 10.9 Supervised Learning
• 10.10 Unsupervised Learning
• 10.11 Reinforcement Learning

DLCS25.HS.9

Compare and contrast fundamental data structures and their uses.

• 6.1 Basic Collection Types
• 6.2 List Methods
• 6.3 Dictionaries
• 6.4 Comparing Data Structures

DLCS25.HS.10

Develop and use a series of test cases to verify that a program performs according to its design specifications.

• 5.13 Testing Your Code

DLCS25.HS.11

Utilize an iterative and incremental software design process, including learning from mistakes, to improve a program.

• 7.2 Software Development Life Cycle
• 7.3 Plan and Design
• 7.4 Develop Round 1
• 7.5 Test
• 7.6 Develop Round 2

DLCS25.HS.12

Improve existing code by restructuring (refactoring) it to enhance readability and/or increase efficiency without changing its overall behavior.

• 5.7 Comments
• 5.8 Refactoring For Readability
• 5.11 Functions and Return Values

DLCS25.HS.13

Select and utilize effective debugging techniques to correct problems in software.

• 5.14 Debugging Strategies

DLCS25.HS.14

Create a complete program to solve a problem or explore personal interests, using a text-based programming language.

• 7.2 Software Development Life Cycle
• 7.3 Plan and Design
• 7.4 Develop Round 1
• 7.5 Test
• 7.6 Develop Round 2

DLCS25.HS.15

Design and implement a program that processes user input, applies relational and logical operators within conditional logic, maintains program state, and produces appropriate responses.

• 7.2 Software Development Life Cycle
• 7.3 Plan and Design
• 7.4 Develop Round 1
• 7.5 Test
• 7.6 Develop Round 2

DLCS25.HS.16

Create interactive data visualizations to help others understand real-world phenomena. [AI]

• 8.8 Interactive Visualizations
• 9.1 Data Dashboard

DLCS25.HS.17

Verify the validity of a dataset by identifying missing, out-of-range, inconsistent, or invalid data and distinguishing these from statistical outliers using basic measures such as range, mean, or standard deviation.

• 8.5 Data Cleaning

DLCS25.HS.18

Correct or remove entries containing missing, out-of-range, inconsistent, or invalid data from a dataset to prepare it for analysis.

• 8.5 Data Cleaning

DLCS25.HS.19

Utilize data analysis tools and statistical methods on a dataset to discover useful information, identify patterns, or make an informed decision.

• 8.10 Statistical Measures

DLCS25.HS.20

Create and utilize models and simulations to help formulate, test, and refine a hypothesis.

• 5.15 Simulation

DLCS25.HS.21

Update an existing model to address flaws and improve precision.

• 10.13 Improving a Model

DLCS25.HS.22

Analyze how network infrastructure impacts the speed, reliability, and scalability of services.

• 3.7 Network Devices

DLCS25.HS.23

Explain how security protocols in networked systems protect or expose data and assess the risks associated with IoT devices and cloud services.

• 1.6 Cybersecurity Essentials

DLCS25.HS.24

Explain the tradeoffs when selecting and implementing cybersecurity recommendations, balancing cost, performance, usability, and security.

• 1.5 Personal Data Security

DLCS25.HS.25

Summarize the mechanisms and purposes of various tracking technologies and identify strategies to manage them.

• 1.2 Personal Data and Collection

DLCS25.HS.26

Investigate the purpose of and relationship among various computer security measures.

• 3.9 Network Communication

DLCS25.HS.27

Create a personal cybersecurity plan incorporating the CIA Triad *(confidentiality, integrity, and availability)* to safeguard sensitive information and ensure its trustworthiness and accessibility.

• 1.6 Cybersecurity Essentials

DLCS25.HS.28

Investigate the motivations behind hacking and examine the associated ethical considerations.

• 1.4 Cyber Ethics and Laws

DLCS25.HS.29

Appraise the trustworthiness of new or unfamiliar resources in order to make safe choices when downloading, installing, and using software.

• 1.7 Common Cyber Attacks and Prevention
• 2.9 Application Security

DLCS25.HS.30

Compare alternative computing architectures, including cluster and quantum computing, to classical computing systems.

• 2.12 Alternative Computing Architectures

DLCS25.HS.31

Explain the interactions between application software, operating systems, drivers, and hardware.

• 2.3 Operating Systems
• 2.5 Comparing Operating Systems
• 2.6 Compatibility

DLCS25.HS.32

Compare and contrast the common metadata elements of various file types.

• 2.6 Compatibility

DLCS25.HS.33

Develop and implement troubleshooting strategies to identify and correct problems with computing devices.

• 4.2 Troubleshooting Methodology

DLCS25.HS.34

Research and explain the impact of computing technology on career pathways across different industries and career fields.

• 4.1 Communication is Key!

DLCS25.HS.35

Research and share information regarding current AI applications in various career fields. [AI]

• 12.1 AI Across Industries and Careers
• 12.2 Exploring AI-Specific Career Paths
• 12.3 Looking Ahead at Careers & Applications
• 12.4 Project: Future of Work
• 12.5 Careers and AI Unit Quiz

DLCS25.HS.36

Analyze the implications of data privacy and consent for making informed decisions about personal data security.

• 1.2 Personal Data and Collection

DLCS25.HS.37

Identify and evaluate the consequences of technology-related laws and policies, including those addressing privacy, accessibility, and intellectual property.

• 11.7 AI Governance and the Future of AI

DLCS25.HS.38

Analyze the ethical issues related to AI technologies and evaluate their societal and ecological impacts. [AI]

• 11.1 Effects of Using Biased AI
• 11.2 Hallucinations and Security Risks
• 11.3 Deepfakes and Misinformation
• 11.6 Environmental Impacts of AI

DLCS25.HS.39

Predict the transformative effects of hypothetical future technologies. [AI]

• 10.2 Human & Artificial Intelligence

DLCS25.HS.40

Follow Americans with Disabilities Act (ADA) standards to design digital artifacts that reduce barriers caused by the digital divide, disability, or bias.

• 7.1 Accessibility and Usability

DLCS25.HS.41

Research and report potential dangers and unintended consequences of over-reliance on AI tools. [AI]

• 10.1 How to Use AI Tools Safely
• 11.2 Hallucinations and Security Risks
• 11.3 Deepfakes and Misinformation
• 11.6 Environmental Impacts of AI

DLCS25.HS.42

Explain how systems learn user preferences and behaviors to deliver personalized content and targeted advertisements. [AI]

• 10.7 Who Builds AI?

DLCS25.HS.43

Investigate the mental health risks associated with excessive technology use, including social isolation, anxiety, and depression, and develop strategies to mitigate them.

• 2.11 Health Impacts of Technology

DLCS25.HS.44

Evaluate the usability of software applications for broad audiences by considering feedback from real-world users.

• 7.1 Accessibility and Usability
• 7.5 Test

DLCS25.HS.45

Identify a problem best solved through human-machine collaboration, decomposing it into tasks suited for each.

• 10.2 Human & Artificial Intelligence